Re-Think Health Podcast Series Episodes

Maria Palombini: Hello everyone, and welcome to the IEEE SA Rethink Health podcast series. I’m your host, Maria Palombini. I am the Director of Healthcare and Life Sciences Global Practice here at the IEEE SA.

This podcast puts industry stakeholders from around the globe on the spot to answer an important question, how can we rethink the approach to healthcare with the responsible use of new technologies and applications that can afford more security, protection, and sustainable, equitable access to quality care for all individuals?

We are delighted to bring you season five, the Rise in Demand for Telehealth, Equity, and Accessible Technologies and I’m delighted to say we’re presenting this in collaboration with the American Telemedicine Association, the ATA. The ATA is a nonprofit organization completely focused on advancing telehealth, committed to ensuring that everyone has access to safe, affordable, and appropriate care when and where they need it. Enabling the system to do more good for more people, and we all love that.

So you can learn more about the IEEE Rethink Health podcast series and tune into our four other seasons on ieeesa.io/healthpodcast. Or you can just scroll through the Rethink Health podcast channel.

So many of you out there might have heard this term are consumers of healthcare. The term was coined back in the 1930s, and in simple terms, the concept makes sense. We as patients are consumers of healthcare. are consumers of healthcare can mean different things to different people. However, the concept has been fueled by both a transformational mind shift in the idea of empowering patients to take control of their health data and the rise in demand for a retail shopping-like experience when it comes to healthcare services.

Many have argued that this concept of “consumers of healthcare” has been fueled by the growth of the use of telehealth services. No doubt we see a rise in the use in demand for telehealth, including the growth of RPMs (Remote Patient Monitoring services), RTM (Remote Therapeutic Monitoring devices). This concept of bringing hospitals to the home and more.

However, the rise does not reflect everyone. A late 2020 study published in the journal Population Health Management examines telehealth uses inequities during the pandemic. Essentially found what we already all know people in urban areas where doctors in care facilities are already in plentiful supply, were more likely to use telehealth solutions than those in rural areas.

And the same was true of people in wealthier versus less affluent locales and neighborhoods. So in season five, we are bringing technologists, researchers, clinicians, advocates, and a host of other stakeholders who will discuss this rise, demand, and need for telehealth, along with the growing concern to adjust the challenges prohibiting equitable access for especially the most vulnerable populations.

Since this is a special season as it is a collaboration with the ATA, our guests will be a selection of speakers from the 2023 annual conference, upcoming March 4th to the sixth, 2023 in San Antonio. And for those of you who are not familiar with the ATA, they always host a large annual conference every year.

So if you miss this year’s 2023 conference, You can definitely catch next year’s 2024. We’re going to hear from these experts on advancements of accessible technologies and infrastructure in progress and policy developments, as well as how much more is needed to have a more comprehensive approach to accessibility and equity in the telehealth system.

So before we get started, IEEE, nor the ATA, endorse or financially support any of the products or services mentioned by or affiliated with our guest experts in this season, five. Guests are invited to participate to offer opinions and perspectives representative of their own knowledge and experience.

So with that out of the way, now it’s my pleasure to welcome Dr. Joseph Kvedar, immediate past chair of the board of the ATA. He’s a professor at Harvard Medical School, and he’s also an editor of NPJ Digital Medicine. Dr. Kvedar, welcome to the Rethink Health Podcast.

Dr. Joseph Kvedar: Thanks so much for having me, Maria. I’m delighted to chat with you today.

Maria Palombini: I am so excited to get into this interview with you, so we’re gonna jump right into it. And you know, just because we’re audio only on podcasts, I like to humanize the experience for our audience, so, you have had a highly reputable career as a board-certified dermatologist, having completed your residency at Massachusetts General Hospital and are now currently a professor at Harvard Medical School. You are an early pioneer and continue to advocate for telehealth adoption. You’ve authored some interesting books, the Internet of Healthy Things and the New Mobile Age, How Technology Will Extend the Healthspan and Optimize the Lifespan.

You also do an interesting blog called C Health, which provides your insights and vision of connected health. So my question to you, as an early pioneer, can you share with us what drove your interest and passion for telehealth? What did you see in it at a time, let’s say 30 years ago, that others perhaps could not see?

Dr. Joseph Kvedar: Well, thanks for the question. It, it, it perhaps will sound a bit quaint, and you have to take yourself back, uh, listeners and, and then if you’re, If you’re a younger person, you have to imagine a world where the largest hard drive was 30 megabytes. The first digital cameras were one megapixel. It was a different world.

We didn’t think about moving things around. We were just starting to see something like the Netscape Navigator come in. So in that context, I was, uh, Assigned really as it turns out, by, by, uh, chance a project to look at this new technology called digital imaging. And would it be of diagnostic, uh, caliber in dermatology?

And it was really during a clinical trial in the early to mid-nineties of that tool that I had. Uh, it was like a light bulb went off one day, and I thought if you could separate. The mental, uh, intellectual activity of a provider from where the patient is. You could just open up all kinds of opportunities to change healthcare, access, quality, and efficiency, and I never really looked back.

Um, I had at the, in the beginning, I, I thought I was probably, this is the part that really answers your question. I, I thought I was among the last to have that, uh, Insight when, of course, I wasn’t among the last, maybe among the first, and so I thought, let’s get going and, and we sort of, I assembled a team and got some early funding from the hospital and started moving forward and, and sort of have pursued it since.

So the work’s not done, uh, as, as you point out, it’s, there’s still plenty to do, but we’ve, we’ve also come a long way in 30 years.

Maria Palombini: That’s, that’s, um, that’s awesome. And I think this really embodies the spirit when we say, how can we rethink the approach to health using these kinds of tools? But you started it a little bit earlier than the rest of us, so that’s what’s really exciting about it.

Okay, so, uh, I hear that you recently launched the ATA new podcast series, entitled Health Virtually Uncensored. So welcome to the world of podcasting. Um, maybe you could share with our audience, um, the mission of the series. Like what are the main points you would like to get out and hoping to use this medium, like to really emphasize or bring awareness to, uh, things of that nature?

Dr. Joseph Kvedar: Thanks again for that, uh, for that question. You know, audio, as, as you, you’ve talked about audio only already in this, in this interview, audio is such a special medium. I, there are lots of stats, and I don’t have all of them at my fingertips, but people will listen to a long-form podcast all the way through.

Uh, whereas if, you know you’re lucky on, on a, on a video, on Facebook or, or a. A tweet that you get, uh, 30 seconds of, of a viewer’s attention. So there’s something about the medium that’s very, very charming and, uh, intimate. Uh, you’re right next to someone’s ear. Um, and so with, with that in mind, I, I looked at our industry, and of course, it is ATA so we’re, we’re always, uh, bringing in people to talk about things that are on our minds at ata, whatever’s topical at the time, but there’s also.

The, the, the title is very deliberate and, and it’s, I think one of the things we’ve suffered from in, in our field over the years is people for whatever reason have tended to over, um, state a little bit their successes, whether that be through numbers of consults or revenue dollars or whatever their thing is.

So I wanted to bring in people that could really. And, and, essentially ask some hard questions too, like, what, what really needs to happen? Where are we really? What? And so we’ve done one episode, we have one coming out in, in a week or so. We’re gonna record a couple more at the annual conference. I have done podcasting before.

I, I love it as a tool and as a way to get the word out. So very excited to see it launch and, um, and move forward. And, the first one got a lot of, uh, attention. So we’re off to a good start.

Maria Palombini: That’s great. I agree. Way.

Dr. Joseph Kvedar: Uh, if I could, I just, um, the one thing that I realized after we launched, uh, I’m, I didn’t pick this up before, but if you wanna find it on Apple Podcast, your, your best to search either my last name, K V E D A R, or health.virtually.uncensored. It’s, it’s, uh, we probably have to change that, but it’s, if you just put in health or health, it won’t come up. So, and you can also find it on the ATA website. So we, we’d love for, have people, uh, rate, review, subscribe, et cetera. And, and thanks, for the plug.

Maria Palombini: Yes, absolutely. I think whenever we can get good information out to our listeners, I’m all, I’m all for it.

So, uh, definitely everybody, you podcast lovers, uh, please be sure to check it out. All right, so we’re gonna get to some good stuff. Why are we here? Right? What are we gonna talk about? It’s really important, so, yes. You know, uh, some have opined or argued that 90 to 95% of healthcare interactions by the year 2030 will be non-face-to-face.

This is pretty significant, but, uh, through our experience or your experience at the ATA in your research, you have written and advocated for making telehealth a permanent part of care delivery by creating a system of omnichannel care that includes both in-person and virtual care. So can you share with us how real this 90 to 95% number can be looking at some of the continued challenges, which I know you’ve written about as well, having with payers and disbursements, this confusion around policy and overall, not a very comprehensive rate of adoption from patients?

Dr. Joseph Kvedar: Yeah, that’s a great question. So, I guess I’d start by saying 90 to 95% seems quite aspirational to me. And, and I’ll quickly add that, I’m not sure why people aspire to numbers like that, right? Mm-hmm. The answer should be what is the right way for you as a patient to get your care in the moment? If it is the best way for you to get your care is through a chatbot.

Or through an urgent care facility If for a video visit you, you early referred earlier to remote patient monitoring, um, the point is you should have access to all those channels, and they should be, um, you should be using the one that best suits your need at the time. I, I don’t know why anyone would aspire to have 95% of our care delivered virtually.

Um, there, there are times when. Patients and or doctors really want to see you in person. There’s a reason why that’s special too. So it has to be balanced. Um, and I don’t know the right number. It’s interesting. I follow the Fair Telehealth tracker, um, which tracks the percentage of healthcare claims. Um, and it’s about 5% now of all claims or telehealth, just for quick comparison, before the pandemic about 0.2% were, were, so it’s, it’s been significant, it’s been consistent, uh, uh, for at least a year and a half.

Now that it’s about 5%, again, I don’t know if that’s right. That might be low, but 95% might be high. And either way, I think what we want to do is figure out. The best way to deliver care is, as we’ve said, telehealth is about access. It’s about efficiency, it’s about quality, and you as a patient have to be cared for in a high-quality way no matter what channel you use.

Maria Palombini: Absolutely. I think it’s really important. Uh, and I think it’s a good point. It’s like, what’s the best model that works for you, and what do you need to get? So totally, uh, an important point to get across. So, uh, getting, talking about access and obviously making sure people can have access to, to care. You know, we all know that there’s an inequity in the traditional healthcare system of care and delivery that has carried over naturally to the telehealth domain.

Many have argued that it’s. Simply because rural and marginalized populations don’t have adequate digital access infrastructure to use telehealth or digital health services. Would you agree or disagree that if the global community came together and just said, Hey, we’re gonna fix this issue of lack of digital access, would we really solve the problem, and would they, the patients utilize the telehealth system or maybe is the problem a bit larger and complex?

There is an issue of trust that seems to always fly under the radar, like trust, um, by marginalized populations in the healthcare system. I know this is a major area of interest to you in, in the work, in the research you have done. So maybe in your perspective, how can telehealth bring some trust into the healthcare system to mitigate this issue of inequity or fear of utilizing the technology and these services?

Dr. Joseph Kvedar: Well, well, Maria, let’s unpack that a little bit. There’s a lot in that and, and you sort of answered your own question in a way that, so, so the first, the first part is about, uh, extending broadband. Let’s pretend that we had a magic wand and we could put broadband in everywhere. Uh, you’re quite right that that is a step.

It’s necessary, but not sufficient. It’s not gonna solve the problem without it. It’s hard to solve the problem, but with it, the problem still may exist. Trust is part of it. Uh, digital literacy is part of it. Affordability is part of it. Um, and so the Ata I, I’m quite pleased with our, our CEO, Ann is a wonderful leader, and she pulled together, uh, over a year ago, a group on diversity, equity, and inclusion and telehealth to tackle this issue.

Because as much as people might say that telehealth and you, you cited a study earlier, um, Led to some inequities. We would argue that it could be a digital divide-crossing tool if employed in the right way because again, it extends access. And so many of those individuals we’re talking about could be urban, could be rural, doesn’t necessarily mean.

But having access, if you gave it to them in a way that was, uh, acceptable, uh, uh, would, would be I think an exciting thing. So that’s one thing we’re working on in terms of trust, you know, you’re quite right. I’ve, I’ve been thinking about this. I actually just published a blog on it, and I intend to talk about it at the annual meeting coming up in about a month that you referenced.

Uh, when I started out, I used to bristle at, at, uh, folks saying, um, Well, I guess this, this new technology that you’re talking about would be okay for a, for a patient who didn’t have access to a real doctor. Um, and I would get so annoyed at that because of course I was a believer from day one and an evangelist and trying to say, not only is it good for rural, it’s good for urban, it’s again, it’s another channel.

It’s not perfect, and it’s not the only channel, but it’s another channel. So, Um, that signaled to me early on, and I didn’t really articulate it this way, but it signaled to me that there was this sort of lack of trust that somehow, and it still exists, uh, there are many layers to it, but that somehow when you use a virtual channel to deliver a service like this, that, that there’s a, uh, an erosion of trust could be because.

You know, the old adage, no one knows you’re a dog on the internet, right? It could be because there’s an un sort of lack of familiarity on the internet. There’s a, there’s a randomness to it. Um, I often tell the story of a doctor who I was told by a friend, so I, I assume this is a true story since, but a doctor who took.

Uh, a video call with a patient with sitting on the beach with no shirt on, you know that individual, a man mm-hmm. Would never go to the office, I think with no shirt on. Right. Why, why do people feel like they can do that? So, I know I’ve been babbling a bit. There’s a lot to it. There’s a lot to uncover and trust, and again, it’s something that we’re gonna be focused on in 2023 at ATA.

So looking forward to unpacking and peeling back the onion and trying to fix it.

Maria Palombini: Hmm, absolutely. I think just overall anything trust in an internet or virtual environment, you just can’t help but have that complexity around it. Um, we see it in every, obviously, healthcare is naturally an area, but we see it in every other industry as well.

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Okay, so healthcare, consumerism. We as patients are consumers of healthcare, and there’s just been this theory of discussions, research papers more recently, and this idea of patients being empowered, uh, to take the driver’s seat of their health data and care, um, especially now that more and more they’re expected to pay out of pocket, um, for their services.

And a great deal of this is fueled by the convenience of the telehealth experience. We know where patients are, likening it to an online shopping experience. I mean, Giving your work, um, what is your perspective on this topic? Um, do you envision maybe a future with a full swing reversal where patients are completely in the driver’s seat, like complete medicine being, you know, patient-driven, um, and commanding that retail-like experience where they’re no longer waiting 30 minutes to see a doctor?

It’s like, I’m here, you service me now. Concepts, right? There’s like all this discussion, um, taking the full ownership of their healthcare, I mean, Where do you think telehealth kind of plays the, the best role in this mind shift?

Dr. Joseph Kvedar: Well, you know, this is another great, uh, thoughtful question I, I reminded of, of, uh, again, back, back in the day when I started, uh, doing this, uh, another trend that was, was happening early in, in my, in my career of, of, uh, telehealth was the trend of patients, um, looking things up on the internet.

And at the time, a lot of doctors kind of blanched at that. People would bring in printouts, To the doctor and the doctors would get very upset with him. Uh, we u at that time, we all sort of felt like, what, what’s between the patient and me? Is that big thick textbook on the shelf? My education, my, uh, use of a certain linguistic when I talk.

Uh, all of that sort of creates, um, a little bit of mystery around the role of being a doctor. Uh, and, and so some of that still exists. And I think it always will, like, you know, there are some professions, if you need an attorney, you need an attorney. I don’t, unless you’re trained as an attorney, it gets to a point where you, you need that expertise.

Unless you’re trained as a physician, at some point, you’re gonna need my judgment, and it’s citizen science that can only take us so far. But with that said, I think we are in an era, and increasingly where patients are in the driver’s seat. They’re voting with their feet on various types of health plans, whether it be virtual first or uh, et cetera, where they feel like if they need a certain service, they’re gonna get it.

And the other example I would give on this is all of these, uh, I would call ’em maybe carve-outs, but, but services like, uh, where you could get birth control filled on, on a, uh, website or you could get your, um, Uh, erectile dysfunction medicine on a website or there, there’s again, many of them, a lot in behavioral health.

And the idea behind those is simply pointing out that there’s a market need for, to make certain, what I call transactional services. You don’t need to get birth control filled. You, you don’t need a whole lot of relationship with a doctor. You just need to make sure it’s safe, and you get the prescription.

And, um, there are those snippets of care. If we as traditional healthcare providers were providing the service in a way that suited everyone, those companies wouldn’t be succeeding. So they’re meeting a market need, and I think we have to look at it that way and rethink how we deliver.

Our services. So again, long-winded answer, we’re, we’re in the middle of that journey. We’ll never get to the point where it’s totally like retail, I don’t think. Mm-hmm. But we are going towards a place where patients have much more control, and that’s a good thing.

Maria Palombini: Absolutely. And just for our audience, if you notice Dr. Kvedar said rethink. So it is an important part of our process in the healthcare system. There you go. Alright, so as you mentioned, and we talked about the annual ATA 2023 conference is upcoming in a couple of weeks, uh, from March 4th to the sixth, and obviously it’s gonna be in San Antonio. Um, and you also just mentioned a few moments ago that you’ll be presenting an important keynote on the value of building trust in the telehealth system.

But also the ATA is celebrating an important milestone. It’s 30th anniversary, which may shock some of our audience to know that telehealth has been around for more than 30 years. Um, so maybe you can share, um, your perspective on this important milestone. How much has changed? Obviously being an early pioneer and obviously seeing the evolution and really how much has been realized that was originally predicted versus what has really come to pass.

Dr. Joseph Kvedar: Yeah, again, love the question, and I’ll be, I, I promise you and your listeners that I won’t be, be too, sort of reminiscent of the good old days. Um, but one of the things I like to use as an analogy when this kind of question comes up is, and if you’ve seen the original film Blade Runner. Uh, there’s, there’s a lot of interest in that.

So that film was shot, I think in 1980 or so. Mm-hmm. And, and it allegedly took place in 2020. So, uh, at the time, that was 40 years in the future, we had things like flying cars that, that hasn’t come to be, but, but there was a scene where, uh, uh, the, the main character has a video conference, and what I find fascinating about that is, They got the video conference part, right?

But he went to a payphone to do it. Uh, there was no notion that you’d be carrying this thing around in your pocket that had a network, uh, video, uh, uh, storage, all of that rolled in, you know, photography, all that rolled into one tiny device. So those are some of the things that I think really have changed the world, the I, the iPhone and.

And the interface that Apple created, which of course was immediately adopted by Android, that sort of changed everything because it made it easy for people to interact with this tiny computer in their hand and do all these things. And we just don’t even think anymore about how important mobile is.

Search was a similar kind of advance, uh, just having browsers and being able to do work through browsers. Uh, having software in the cloud. I mean, there are so many examples, and I think in the last 10 years, wearables, uh, as well and, and the connectivity and the feedback that wearables give you. So that’s, that’s a little bit of a game-ish.

I’ll, I’ll give you that, but, but when I look back at the beginning and what’s funny about it was at the time, any, any point along the 30 years, what we, we thought we had. The right technology to do the job. And typically in healthcare, we’re always behind the technology. So, you know, in the beginning, we had these big, two, two companies were, were, uh, prominent VTEL and PictureTel, these big CRT displays with big, uh, codex underneath them, $70,000 a pop.

You had to run three ISDN lines. It was a nightmare. But we thought that was great and people did it. Uh, and again, 30 years fast forward and you’ve got it in the palm of your hand. You can connect anywhere wirelessly, and it’s different worlds. So all that said, it’s been remarkable, and yet as you and I have said, telehealth isn’t probably where we need it to be yet.

We still have a long ways to go to get it in that proper omnichannel world that we’ve talked about, and we look forward to, uh, those challenges and getting ’em right as time goes on.

Maria Palombini: Absolutely. I think it’s, uh, continuously evolving and emerging, uh, technology and domain. So, uh, I think we’re getting ready for this conference, right?

I’m gonna be there. I’m looking forward to it, but, uh, maybe from your side, you can share with our audience who may be coming, who may be thinking about coming. What are you, what are some of the technologies or issues or areas that you think are going to be covered at this series conference that maybe people, something new that maybe people should be like maybe keeping their eye on anything that maybe is caught your eye so far?

Well, I can’t necessarily speak to new technologies only because they show up on the exhibit floor usually, or, or in some of the research. Uh, we do have a very strong research track with posters and presentations, highly curated. Um, we have a lot going on on the exhibit floor in terms of. Uh, uh, supplier presentations and, and new things going on, trying to attract a lot of, uh, early-stage companies to show their wares as well.

And we have an innovators challenge, so there are a lot of ways, to get new stuff in. Um, but some of the themes, one of them is going to be, uh, this has been on our minds for two years, and it’s, or three, and it’s, uh, not going away, which is just extending. All of the regulatory environment is in the right direction to allow us to keep delivering this care.

Uh, we now have a window till the end of 2024 for most things, but because it’s an election year, we think we’re gonna really have only a year to try to get that, uh, extended further. So that will come up. Um, you know, this idea of omnichannel comes up, and that’s gonna be. Uh, a prominent one. We have an executive invited session for a whole day where people are gonna talk about, uh, you mentioned, we both mentioned, um, excuse me, equity, equity is a big focus of ATA So, so those are some of the themes. Again, it’s, uh, it’s a little bit like a com, uh, like a street, uh, uh, fair. There’s so much going on in a good way. So come learn. Meet people, um, in, in San Antonio is, is just a lovely place.

Maria Palombini: Absolutely, especially this time of year. Um, so, uh, you know, we’re coming through the close, and you know, Dr. Kvedar you have already given us so much insight. Um, perhaps you can share with us one final parting thought, um, and with our audience, share with them, you know, maybe something when it comes to the challenge, the issue. The need to gain wider adoption. You know, I think, um, these kinds of challenges take a village.

I don’t think no one person or one group can solve ’em. So, you know, what can we do as a technologist, a researcher, clinicians? Mm-hmm. Um, or any other, someone who’s committed to seeing the process, you know, become more trusted and ethical and equitable for all.

Dr. Joseph Kvedar: Sure. I thank you for the opportunity.

I, I mean, I, assume, that the IEEE audience is going to be people who are keen on innovative technologies, and my message to those folks usually is to simplify as much as possible, get, get as much feedback from end users in your, in your dev, um, development as possible. Unfortunately, when we have engineers devise.

Tools that other engineers, like, sometimes they don’t go as far in the marketplace as quickly as, as we might like, because people are, they’re, they’re, that’s, those people are really smart, and most of the folks they want to design for aren’t as smart as them. So just be really thoughtful about making things, uh, easy to use, intuitive, um, and exciting.

Uh, I think there’s a, you know, this technology nowadays, whether it be wearables or. Other, uh, apps, et cetera. The ones that are winning are ones that people just delight in using. And, uh, and I think we can make healthcare delightful in, in that way.

Maria Palombini: Absolutely. Um, so thank you, uh, Dr. Kvedar for joining me today. Um, this has been a really, really insightful conversation.

I wanna thank the ATA for collaborating with the IEEE Healthcare Life Science Practice to bring this special season five of Rethink Health, um, to you, our global audience. Um, you can learn more about Dr. Kvedar and his research, his blogs, they’re all available on, um, joekvedar.com and I’ll spell that for you all joekvedar.com. Just for all of you out there. Many of the concepts in our conversation today, um, are addressed in various activities throughout the IEEE Standards Association, healthcare, life science practice, and its, you know, standards and pre-standards, um, programs. The mission of the practice is to engage multidisciplinary stakeholders around the world, to have them openly collaborate, build consensus, and develop solutions in an open standardized means.

Um, we have activities such as wearables and medical IoT, interoperability, intelligence, and transforming telehealth paradigm industry connections programs, which are really addressing the many things around equity, accessibility, feasibility, privacy, security, interoperability by design, all these challenges we’re seeing, um, pervasive in our healthcare, uh, in our telehealth system.

If you wanna learn more about all of the activities, visit ieeesa.io/hls. So a special thanks to you, the audience. Uh, we invite you to share this podcast with your colleagues and networks to help get this information out, um, to those who want to make a difference and contribute to overall better healthcare.

We wanna thank you for joining and keeping doing the great work you are doing to improve our healthcare system. Be sure to tune in to our other episodes of season five, in which we’ll have some exciting speakers, um, from 2023 at the annual conference. Um, stay safe and well until next time.

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Maria Palombini
Hello everyone and welcome to the IEEE SA Rethink Health Podcast Series. I’m your host, Maria Palombini, Director of the IEEE SA Healthcare and Life Sciences Global Practice. This podcast takes industry stakeholders, technologists, researchers, clinicians, regulators, and more from around the globe to task. How can we rethink the approach to healthcare with the responsible use of new technologies and applications that can afford more security protection and sustainable equitable access to quality care for all individuals?

We are in season four of the podcast series. You can check out our previous seasons on ieeesa.io/healthpodcast.

As we all know the result of the recent pandemic, the term telehealth has become one of the most frequently used ones, and it does not appear to be going away soon. The reality is the way we see telehealth today will look very different tomorrow. It’s manifesting in many different forms. It’s more than what we commonly see as a doctor/patient exchange on an audio/video platform.

It continues to grow, especially with RPM devices, Remote Patient Monitoring devices. The telehealth experience has changed the patient’s expectations on healthcare services. They’re relating it more to a concierge level, online retail experience: convenient, appropriate, and personalized.

And then there’s this growing RPM space. There’s so many different forecasts when it comes to RPM. Anywhere from U.S. 150 billion dollars by 2028 to estimates that 40% of patients will utilize one or more of these types of devices at one given time. But here’s one thing for certain, regardless if we’re talking telehealth, mobilized health, RPMs, the future of delivering healthcare is not confined to a facility and it will need to be patient-centered.

So season four, of this podcast series, Telehealth’s Quantum Leap into Patient-centered Care, talks to the innovators. These are the winners of the IEEE SA Telehealth Virtual Pitch Competition, the industry leaders, clinicians, and other researchers who are at the forefront of driving innovations with solutions on accessibility, human factor design, flexibility, interoperability, security, inclusivity, and any other necessary ingredient to migrate telehealth care to a patient-centered care system.

So a short disclaimer before we begin, IEEE does not endorse or financially support any of the products or services discussed by our guests in this series.

It is my pleasure to welcome Sanna Gaspard, CEO of Rubitection, Inventor of the Rubitect Assessment System to our conversation.

Hi, Sanna, welcome to our podcast.

Sanna Gaspard
Thank you for the opportunity. Looking forward to talking to you today.

Maria Palombini
I’m excited to have Sanna here with us! Rubitection garnered the first place position in the entity category of the IEEE SA Rethink the RPM Machine Competition.

So Sanna, before we get to the core of your innovation, tell us a little bit about you. You’re CEO, you’re an inventor of this solution, what drives your passion in your work? How did you get here?

Sanna Gaspard
What really drives my passion in my work is being able to innovate to improve healthcare. I have a PhD in Biomedical Engineering with a specialization in Medical Device Development and Commercialization. I came to that after thinking about being a pre-med to become a doctor and realizing that wasn’t the best career for my personality and what I wanted to do. I decided I really wanted to still have an impact in healthcare, but maybe on developing the technology that doctors use. And so now I’m just passionate about getting the technology out there to help caregivers and patients.

Maria Palombini
I think it’s fascinating because I’ve interviewed physicians who are migrating over to IT and Technology Design because they felt like, well, this is really what I wanted to do.

So we often hear that starting a company in this space derives from some sort of personal experience. Somehow they may have been afflicted, a family member, or something they came across doing university research. Is there a personal story behind bringing this innovative RPM approach to wound care? What was the vision and impact you imagined that it could have for patients?

Sanna Gaspard
So the personal story was really driven more by my desire to want to improve healthcare as a career than personal experience with the condition. I came across a condition while I was in grad school. At the time I was looking for a project where I could develop technology to improve care, but I really wanted to focus on something that was a healthcare problem, that was very common, but being overlooked.

And so when I learned about bed sores and I went and researched it, I found that it was killing like 60,000 people every year, affecting 2 million people per year, but the assessment approach was really still something that was manual where technology could be used to improve that assessment to save lives.

And so that was really what drove me to do that, I wanted to make sure that I spent the time on my PhD doing something that I could translate out to improve care and really address a real healthcare problem.

Maria Palombini
Absolutely. So it’s interesting, we often hear you need thicker skin to survive in this world. And in this case, you just mentioned 60,000 people die from complications due to bedsores every year, people think, oh, it’s just a little condition, but it does take people’s lives. That’s one person every nine minutes, so it’s pretty significant and over 55% of nursing home residents die from bed sores within six weeks of onset of the wound.

We all may have elderly relatives living in nursing homes, this is something we all have to consider. So let’s get to the core of the interview of how this RPM innovation can start to really have an impact.

Can you share the types of research, maybe some modeling in the years that worked, that went into developing this product? What would you say in your research was the most interesting piece of information that came through in this R&D phase?

Sanna Gaspard
The most interesting piece of information I would say was twofold. One, how long the problem was outstanding. There’s comments back to Florence Nightingale and I think even possibly some references in Egyptian literature to these wounds and bed sores. But there was no real solution at the time. And that was partly being driven by legislation and policy partly because a lot of the costs for those wounds was being covered by the insurance companies and Medicare. But as they’re providing primary care and the patient develops a wound, they would still get additional payments for that care. So for me, that was a striking thing that was driving a lot of the lack of innovation in this space. There was a longstanding need.

The other thing that really caught my attention was the importance of correlating the technological platform to the clinical environment and how important that would be. So when I first learned about the issue, I went and researched all the different technical logical approaches you could use like ultrasound spectroscopy ,temperature and tried to match that against the user needs in that environment to see what would be the most appropriate. And I found that really was an interesting exercise in terms of like someone who’s interested in developing tech, you can’t just go and say, oh, I think this is a tech I want to use or the technological platform I want to use to solve this problem. You really have to cross check it around what the users need and how it would integrate into that environment around usability and ease of use. That was a lot of the early work I did that drove the direction of the technology in terms of development.

Maria Palombini
There are many different skin conditions from eczema to bed sores to wound care. How does the RAS system work to identify the abnormality? And at the same time, how can it indicate what exactly is the abnormality? Like it’s a diabetic ulcer, it’s a bed sore, it’s a wound, whatever it may be.

Sanna Gaspard
The Rubitect Assessment System, abbreviated RAS, is essentially a device that helps to assess the skin to identify chronic inflammation or conditions in a dermatology space or in the wound care and surgical space. So in a dermatology space, it could be used for things like rosacea, eczema, eventually, maybe things like skin cancer for early screening and in the wound care space, we’re looking at diabetic foot ulcers, pressure injuries and surgical wound monitoring.

It essentially includes a software system that you can monitor data on and a device that you place onto the skin to make measurements of the skin, to identify areas of inflammation. So you place a device on the skin. It makes a measurement predominantly using optics, and then you get an assessment following that measurement about low, medium, or high risk or gives you a diagnosis.

And you can then share with your primary care physician to get an updated care plan or to understand the next steps in the care plan. Our real goal with that system is to really support effective early assessment to prevent the progression of advanced wounds or to help patients in a dermatological space, either do early assessment to evaluate treatment effectiveness based on the prescriptive treatment that their doctors provided so that they can support care compliance and using the system, or get a new prescription if that product is not working. On the wound care side, it’s catching it early to prevent advanced wounds that can be deathly.

Maria Palombini
Very interesting. So we’re trying to get ahead of the game here.

Sanna Gaspard
We’re trying to get ahead of the game and empower people.

Maria Palombini
One of the key features that you presented in the competition is that the data collected is interoperable with medical health records, which for patients, that’s a great opportunity. How have you seen physicians and caregivers use the data collected about the patient to sort of alter their care, to make it better and how does the data collected actually integrate into their patient’s medical chart?

Sanna Gaspard
So right now, we’re still in R&D. So we haven’t fully launched the product, but when we launch it, we depend on having an EHR integration. From a remote patient care standpoint, the measurements they do at home to provide a risk assessment or to do care planning and management would be sent back to their primary care physician.

Where they would confirm the data, confirm the care plan, and then also be able to save that in the EHR. When using an acute care setting, it would just be an inherent part of the EHR as they’re using the system. The data’s then also stored in the EHR for later data analysis or reporting and documentation.

Maria Palombini
We mentioned nursing facilities and long assisted living facilities. So one of the population sets that this may benefit is naturally the aging population. However, when we think about the aging population, they’re not usually considered the most digital and or trusting of these types of technologies.

What has been your experience or in research, being able to reach this age demographic, to utilize the RAS system, to trust it, to want to use it? What are some of the lessons that you might have learned through this engagement?

Sanna Gaspard
I would say some of the lessons I’ve learned through this engagement oftentimes is that you have to go through a family member or you have to go through their adult child.

Oftentimes their adult child is the person providing care or the nurse is the person providing care. So the main part of targeting this population is going through their care provider or their primary care provider, or the person who’s managing that care. And then basically working with that person to either explain the importance of the problem or how the technology can really help support them in managing that care.

But oftentimes getting access directly to those potentially elderly patients can be difficult, because you really can’t necessarily go to them directly. You have to go find their care provider.

Maria Palombini
Trying to turn caregivers into advocates for the use of this technology in order to help this area of the population.

Sanna Gaspard
Yes, exactly. And finding those caregivers in either advocate groups or finding those consumer targets in a home setting can be difficult. You’d have to go through the primary physician or the primary care provider. Basically go that way.

Maria Palombini
When we think of the pool of patients, it’s more than just the aging, because we’re talking a wide swath of wound care issues, other issues, diabetics. How do you see your technology being patient-centered? And when we talk about patient-centered it could be a point of accessibility, inclusivity, feasibility, adaptability. Is there a population of patients that you can better serve with this technology that perhaps could not be reached or accessed or included before when it comes to RPM opportunities?

Sanna Gaspard
We’re working on a skin health assessment tool that has applications in dermatology, in wound care, and surgery. In all of those fields for patients who have chronic dermatological conditions like psoriasis or eczema and even skin cancer, oftentimes, they would have to come into the office to get an assessment, or they were sending pictures or using really crude technology to try to document their condition to eventually share that with the doctor when they went into the office. Also true for patients with wounds so that when the patient goes home, their family members and caregivers are told here’s the care plan to help prevent this person from getting a wound but then they only see the doctor once the wound develops. So that makes prevention and early detection really difficult.

So really in each of those market segments, we are providing an access to a level of care that wasn’t available before, unless you went into the doctor’s office. So now you can have in-home monitoring to monitor changes in the skin to catch things early, share that with your physician, get an updated care plan, then catch things at an earlier stage when they’re least costly and the easiest to treat.

Maria Palombini
That’s a fascinating point. Because as a caregiver, you call a doctor and how you articulate something is not going right in a medical way. So I think this is a fascinating area because that is one of the caregiver’s biggest concerns. Can I take care of this at home? Am I capable of doing this? How about if something goes wrong? You get all these questions, right?

Sanna Gaspard
Exactly. And then in talking to caregivers in the home setting, another thing that comes up is like, as you’re responsible for that care for your loved one, your parent, your grandmother, maybe even a disabled child or someone with a chronic health condition, you’re trying to do your best to manage the care and manage your life. And when they get something that’s preventable, like bed sore that can be really severe. There’s a lot of guilt and shame associated with that oftentimes because they feel responsible and we really want to just help empower caregivers to understand that without technology, it is really hard to do that early detection and then to empower them to feel like they have the tools to prevent some of the chronic complications of a bed sore so that they can feel confident in the care that they’re providing in managing that care.

Maria Palombini
Absolutely. That’s a great benefit for caregivers out there. For sure.

As a tech startup, would you think of any technical standards, policies, opportunities, or something in place that would’ve made the development of this product go faster, easier. And after going through this process, what areas have you identified would open the doors to innovation in the telehealth space? And in your opinion, what would be the best way to address it?

Sanna Gaspard
One is funding because you need funding to be able to develop the technology. And I think having technical organizations that can support technical founders in getting access to funding or providing funding as investors or grants would be already a great start.

And I think also from a medical standpoint, technical standards around EHR integration would also be really helpful in meeting that HIPAA requirement because there’s so many ways, it’s usually customizable to each person’s technology, but having really clear standards about how you have that healthcare integration with each EMR systems would go a long way. Because all of the EMRs are slightly different, how you communicate with them in their platforms. And so it makes tech development with EHR integration very cumbersome and expensive.

Maria Palombini
So it’s almost like a tech entrepreneur mentorship sort of way of helping tech engineers. One being able to understand how to source and get funding as needed as they’re developing the product. But also understanding what tech guidelines are out there that maybe no one knows about, because we tend to always uncover these things and even say, okay, they’re not existent, but maybe this is something else you can use.

So I agree. I think there could be some definite guidance from people in that role before, and probably can point you in a faster, easier way to get to the answers you’re looking for.

Sanna Gaspard
Yeah, I would agree with that.

Maria Palombini
You’ve given us some really interesting insights, especially when it comes to this whole area of therapeutic on the health side and the opportunity of supporting the caregiver for which we don’t see too often in a lot of RPM devices. What is something that you would like to share with our audience? It is a diverse group. We have technologists, we have people in the clinical field. We have researchers, regulators, policy people, whoever’s listening to this podcast. What would you like to share with them when it comes to really understanding developing technologies under the context of patient-centered care?

Sanna Gaspard
I think the most important thing is that it takes everybody. Technology can’t be created in a vacuum. As someone developing technology, I need access to healthcare providers. I need access to the caregivers and patients to understand what their needs are. In terms of the clinical providers, I need access to them to understand clinical integration and use cases and how to ensure that the device meets usability requirements and also clinical integration requirements. Policy makers usually end up driving things around pricing and large market drivers that affect adoption around reimbursement or medical policies for use or requirements for use in reporting that really end up driving clinical adoption. And also things around regulatory issues like the FDA. So it really takes everybody and there should be really more groups where that brings together a diverse group of stakeholders that technologists can access in one place. So like right now, if I wanna talk to a doctor, I have to go and find a doctor. Then I have to go and find the patient in a different location. And I have to go find the stakeholder from a policy standpoint in a different location. There’s not one place that you can go and get a holistic view of the problem to get the perspectives of each major stakeholder in one setting.

Maria Palombini
I can see that, but that’s also symptomatic unfortunately, of the healthcare system, right?

Sanna Gaspard
It doesn’t have to be fragmented. I mean, people have historical data of their images of their personal life and we can’t manage to get longitudinal data of our own health.

Maria Palombini
That’s a very good point. Sanna, thank you so much for joining me today and sharing all these exciting insights.

Sanna Gaspard
Thank you as well for the opportunity. I enjoyed talking to you, and if anybody wants to reach out, they can shout to me at [email protected].

Maria Palombini
Absolutely. If you guys wanna learn more about the Rubitection Assessment System and about Rubitection in general, you can visit rubitection.com. And you can learn all about Sanna as well and her advisory team and all the other information that’s on there.

Many of the concepts we talked about with Sanna today are addressed in various activities throughout the IEEE SA Healthcare & Life Science Practice. The mission of our practice is engaging multidisciplinary stakeholders and having them openly collaborate, build consensus, and develop solutions in an open, standardized means to support innovation that will enable privacy, security and equitable, sustainable access to quality care for all.

And these are activities such as WAMIII: Wearables and Medical IOT Interoperability Intelligence Incubator Program, and Transforming the Telehealth Paradigm Industry Connections Program. And there’s a whole host of others in Decentralized Clinical Trials, AI, Digital Therapeutics for Mental Healthcare. So if you’re interested in learning how you can get involved or think about instantiating an activity, you can visit our practice website at ieeesa.io/hls.

If you enjoyed this podcast, we ask you to share it with your peers, colleagues on your networks. This is the only way we can get these important discussions out into the domain is by helping us to get the word out. Be sure to use #IEEEHLS or tag us on Twitter @IEEESA or on LinkedIn, IEEE Standards Association.

I wanna do a special thank you to you, the audience for listening in. Continue to stay safe and well until next time.

Maria Palombini
Hello everyone and welcome to the IEEE SA Re-think Health Podcast Series. I’m your host, Maria Palombini, Director of the Healthcare and Life Sciences Global Practice here at the IEEE Standards Association. This podcast series takes industry stakeholders, the technologists, the researchers, clinicians, regulators, and more from around the globe to task, we ask them how can we rethink the approach to healthcare with responsible use of new technologies and applications that can afford more security, protection, and sustainable, equitable access to quality care for all individuals?

We are currently in season four, but you can check out our previous seasons on ieeesa.io/healthpodcast. So we all know as a result of the recent pandemic, the term “telehealth” is frequently used and it does not appear to be going away soon. The reality is that the way we see telehealth today will look very different tomorrow.

And it’s manifesting in many different forms. It’s more than what we commonly see or think as the doctor/patient exchange on some sort of audio or video platform. We look at innovations in RPM, remote patient monitoring. We look at how telehealth experience has changed even the patient’s expectation on healthcare services relating more to a concierge level, online retail experience, convenient, appropriate, and personalized.

And with this growing RPM space, there’s so many different forecasts when it comes to it anywhere from U.S. 150 billion by 2028 to an estimate of 40% of patients may be utilizing one or two of these devices at one time. But one thing is for certain, regardless if we are talking telehealth, mobilized health, or RPMs, the future of delivering healthcare is not confined to a facility. It will need to be patient-centered.

So season four of this podcast series, Telehealth’s Quantum Leap into Patient-centered Care, talks to the innovators, which are the winners of the IEEE SA Telehealth Virtual Pitch Competition, the industry leaders, the clinicians, and other researchers who are at the forefront of driving innovation with solutions on accessibility, human factor design, flexibility, security, inclusivity, and any other necessary ingredients to migrate telehealth care to a patient-centered care system.

A short disclaimer before we begin, IEEE does not endorse for financial support any of the products or services mentioned by or affiliated with our guest experts in this series. And now, it’s my pleasure to welcome Dr. Shayan Vayas, Senior Vice President and Medical Director of Clinical Operations at Teladoc Health.

Shayan was also a judge and advisor on the IEEE SA Rethink the Machine: Transforming RPM into a Patient-centered Care System Virtual Pitch Competition. And he’s also a participant in our Transforming the Telehealth Paradigm Industry Connections Program. Welcome Shayan.

Shayan Vyas
Thank you very much, Maria. It’s a pleasure to be here with you and IEEE listeners.

Maria Palombini
Before we get started to the core of the awesome work that’s going on at Teladoc, Shayan, you started with a successful career as a physician and you transitioned to virtual care and IT design. What was the catalyst for this change?

Shayan Vyas
Being a critical care physician, I’m at the frontline with the team, treating the sickest patients in the hospital. It’s the most vulnerable time for patients and families. This experience taught me a lot about obviously medicine and really the patient experience, but also mortality. As we think about how technology transsects patients, physicians, and clinicians, it significantly helps them, but it also can overburden them.

Furthermore, clinical care or even just bedside medicine is a model of one to one. I deliver care, clinician or nurse delivers care one to one and that’s not scalable. Even during my early training, when I was doing missionary trips as a young clinician, I wasn’t well experienced and I was still learning the art of medicine.

I wasn’t typically seeing bread and butter illnesses. And at this time, I really started to begin valuing and using technology. Phones started having the capabilities of doing video visits pretty easily and it’s become part of our everyday life.

That moment when I used the device to be able to call my mentors and my coaches back home during these trips, I realized this could be a catalyst. This could be a transition of how one to one can be one to many; how others can be impacted if I’m in another world, another country delivering care, and I’m able to connect to specialists and mentors back home, how can this affect the patient?

Technology can redefine the world we live in. We’ve seen that with innovators like Steve Jobs, Bezos, think about that with healthcare. There’s gotta be a way where we can take IT design and virtual care and just redesign the world that we live in, in healthcare.

Maria Palombini
Absolutely. I remember we were having a meeting one day in our telehealth group, and you just said something in passing, but it caught my attention. And I remember you vividly saying that tides have turned. No longer is the patient’s health experience like beholden to the times when you go to a doctor’s office and you have to sit there for hours, waiting for them to let you in. Like a patient’s demands are changing. And they want that concierge level experience as they get with retail. So how do you see telehealth overall, trying to meet that changing need?

Shayan Vyas
Patients are patients, but in this context, let’s say the word consumers, right?

So patients/consumers, they’re bringing their everyday expectations from other industries into healthcare. They’re intersecting their experience when they shop online or they stream a movie or even buy an airline ticket into healthcare and other industries. That experience that they enjoy and have the flexibility of doing in entertainment or shopping or whatnot, they’re starting to expect that in everything that they do. When’s the last time the listener actually went to the airport to buy a ticket? When’s the last time the listeners actually went to a store and rented a movie? That haul has changed. Even more, if you’re outside of a very large city, like New York, I’m in now, when’s the last time you actually flagged down a cab or you drove to a restaurant to carry out? Those things, they’ve revolutionized the world we live in. They can be done on an app or a browser. And that same consumer experience is what folks are craving when it comes to healthcare.

Consumers/patients, they don’t wanna wait in waiting rooms anymore. They don’t wanna wait six weeks for their PCP to send them to a specialist. Telehealth is just the beginning of this transformation. It allows that one to many that I described earlier, but more importantly, it’s starting to meet the bend of what consumers are demanding. I think this transformation of healthcare is just getting started. The in person aspects of medical care or going to the doctor will be held for the very few life threatening procedural needs.

I really believe that the tide has changed in that healthcare historically was built around the doctor, my waiting room, my parking lot. You’re gonna go on my terms, it’s changed to the patients. Patients now can schedule visits, they can go and look up what medical school I went to and what my press community score is. They can now shop around and that power is obviously well deserved. Consumers should know where they’re walking into. They have the right to choose what movie they wanna see, they can see the reviews and what others have said about it. The same thing should be in healthcare.

The tides have changed.

Maria Palombini
Absolutely. I think we get caught up in everything and sometimes we don’t realize that because innovations are coming out so fast, we lose sight of some of these things.

So Teladoc is one of the top 10 telemedicine companies founded in 2002. There’s rankings all over on the internet, but it’s always in the top 10 and that’s 20 years ago. The world really wasn’t talking about telehealth, nowhere near at the level we do it today and it’s actually only the publicly listed telemedicine company. So obviously the pandemic catapulted, the use of telehealth out of necessity. However, Teladoc was already on its way.

Do you find that Teladoc’s success is founded on its principle, that it’s a patient-centered platform?

Shayan Vyas
Absolutely. 20 years ago when Teladoc started, our physicians were actually breaking the law. We were taken to court and we ended up counter suing my home state, the board of medicine there.

And we changed the way society and law looked at a physician and a patient relationship. We did that because it was all about the patient-center. We wanted patients to have access to healthcare 24/7 without having to leave their home. In my mind, that ruling and the fundamentals of our company changed the balance of the physician “owning” the individual patient.

And it allowed now the patient to really understand and own their journey when it comes to healthcare, their choices, their flexibility. This is a transformation in not only just the law, but medical economics, and the fundamentals for consumers, obviously that propelled us to be the first publicly traded company and really the largest virtual company in the world.

It’s all about the patient. We have to deliver high level quality care. That’s an expectation that is a basic need in healthcare. Patients deserve to get the highest quality of care, but changing the principle around and delivering a platform that the patient can control was fundamental.

Maria Palombini
I think often we see innovations coming out and it’s all about, oh, the next best shiny thing. And it can do this and that, but we lose sight that we’re still serving the critical need of the patient. And I think this is really interesting. So for all you out there, Telehealth Doc, this was just released publicly. They signed a partnership with Northwell Health. And for those of you outside the New York Metro area, Northwell Health represents, one of, I think, New York’s largest healthcare provider. And the goal is to better provide access to virtual care across its enterprise. So we definitely focused on the patient, but one of the things, when we think of telehealth services, we think it’s easy, right. You just plug into a platform, turn on the mobile device and let’s connect and, obviously have the doctor/patient experience.

What are the considerations for the workflow from a physician’s perspective that must be changed to accommodate this transition to virtual care?

Shayan Vyas
A comment on Northwell, they have one of the greatest CEOs in the healthcare world ever. Very great organization. Over 18,000 physicians. They’ve been practicing telehealth for a long time.

When it comes to accommodations to transition to virtual care, there are multiple consumers that are using the platform. There’s the health system. So the administrators from the health system need to have data. There are physicians and now nurses and all kinds of clinicians are working. So we’ll use the term clinicians and then there’s the patient. There’s the IT team.

And so all of these consumers need to be thought of. So when we first started out, as mentioned previously, we built a platform really around the patient, but now there’s multiple end users that need to be thought of. You gotta think about those that we just mentioned. And in terms of thinking about how to transition everything to virtual care, the bar to virtual video visits is very low.

There are many ways to do a virtual visit now. You can do it essentially for free now with any app, to connect with grandmother or to connect with colleagues around the world. That bar is now very low. Everyone has a video platform. The bar to scalability is very hard. The bar to interoperability within multiple EMRs.

I think Northwell has 22 hospitals, 830 facilities, the integration in and out of the firewalls and in all the data systems that they’re using, that’s the hard part. And then when you multiply it, we have over 600 health systems around the world that we work with.

That is really hard in terms of just the individual physician’s perspective to replicate the in person experience or has to make it much easier.

Physicians are wasting a lot of time today with stuff that is not really adding value to the patient, the care they’re delivering, or even the ROI that the health system is investing in. And so when we think about adding video conferencing, it’s not just that. You have got to amplify the ability for folks to be able to practice at the highest level of their license.

Maria Palombini
It’s very interesting that you mentioned that because I was talking with Dr. Keith Thompson, who’s also part of the Telehealth Program and he said almost the exact same thing from a clinician perspective. As doctors we’re getting in all this administrative action outside of actual care action, helping the patient because of all these changes in workflows. And he was saying that this is where it’s really important to understand what the doctor needs to focus on and what the patient needs to focus on. And then let the experts handle all that other stuff.

Shayan Vyas
Here’s the reality, right? As an intensivist, I have a different perspective than an ambulatory physician, but even as an intensivist, I spend maybe 10% of my time at the bedside. The other 90% is I’m a data clerk. I’m entering data into an accounting ledger. It’s not making patient care easier. It’s not making the care safer.

It’s really a billing machine. And when you talk to my ambulatory colleagues, they’re doing the same thing, right? They’re spending minutes. I think that the average family practice doctor spends eight minutes with a patient. And they spend 30 minutes just charting and documenting and clicking here and there. As a consumer, I would rather a clinician spend 30 minutes with me and then the eight minutes doing the charting that adds no value to the system, but is where all the money and the transaction occurs.

Maria Palombini
I’m sure patients would agree with you 100% on that point.

So as we move towards greater adoption or use of virtual care, more acceptance, how do hospitals best negotiate the balance of patients expectations for home care versus hospital facility care? They are significantly different, but we still have patients’ expectations when they’re not doing well. So how does that balance work out?

Shayan Vyas
Maria, this is a great question. So let’s take a step back. The origin of modern day telehealth started really with employers and health insurances. They wanted to figure out a financial way to lower the delivery of care. The emergency room versus a telehealth visit is significantly cheaper for everybody. Significantly easier if you can get your symptoms and your illness resolved that way. That’s really where it started. It was really around the payers. Regarding hospitals, they get paid for beds and heads. It’s a very common term. We’re in a fee for service world. And the best way to get paid is when you have a head inside a bed.

When you look at health systems like Northwell Health, Kaiser Permanente, Intermountain, they have moved out of this fee for service world where they no longer are getting paid based on every procedure they do. The fee for service industry itself has plagued healthcare. You go to a surgeon, they’re gonna operate on you because they get paid that way.

That’s the way the model was. There was no value incentive for a surgeon not to operate on you. And so as we move from this fee for service world and to this value based world, that’s where we start to move the needle. The financial incentives now to actually do what’s in the patient’s best interest, try to deliver on this expectation that consumers or patients have in home care versus hospital care.

That’s where we start to see the needle move as more and more health systems start to develop MA plans and they start to take financial risk. They’re starting to think about how they can move away from bricks and mortar care to virtual care. That’s easier for everybody, it’s cheaper for everybody. And that’s how it’s gonna happen.

I think health systems are gonna have a hard time to be honest, trying to deliver full based virtual care when they’re fee for service. It’s not the same. It’s dollars to pennies when you meet in person versus you see me in virtual, in that fee for service world, but in that value based world, as long as I deliver the care, no matter if it’d be virtual or in person, delivering that care is what it’s at.

Patients are expecting that virtual visit when they go to the doctor or they have a surgery and they wanna do that visit. It’s a standard that a patient expects. But again, there’s a balance of getting paid and when health systems and physicians are getting paid more in person than virtual visits, then that’s a challenge.

It’s hard to move the financial needle that way. But as health systems and CMS are starting to push really for this value based care will really exponentially propel telehealth and virtual care.

Maria Palombini
I think that’s a really important transition that I think the whole industry needs to better evaluate and keep an eye on. I often say, and I talk about this with many different volunteers here at IEEE SA about the future of telehealth looking very different than it does today. And as a physician, why is it important to embrace the migration towards virtual care? The idea of bringing healthcare outside of the facility to the home and can it really improve patient outcomes? Can it actually better serve patients across the board?

Shayan Vyas
Before virtual care or even telehealth or remote patient monitoring, the standard for any of us was to go into the doctor, the bricks and mortar doctor. What did we learn from that? We learned that those that had access got better care. The proof is here. Everyone knows about DNA and genetics and hereditary diseases. Today 60% of health outcomes are determined solely by one thing. Do you know what that one thing is? Zip code.

Maria Palombini
Interesting.

Shayan Vyas
Not your DNA, not how long your parents lived, not the cancers that are in your family, but zip code is the primary determiner of your health outcome.

That’s fundamentally flawed. For those that live in a poor area, rural area, those determinants, what we call social determinants of health, access to fresh groceries, clean food, all of those things, high education, good paying jobs. Those are all social determinants of health, but when it comes down to access and one’s health, it was zip code.

And so as we think about this migration of virtual care, no matter where you live in this country, no matter where you live in this world, you can get access to Mayo Clinic. You can get access to. Kaiser to Northwell to all of these health systems. And that’s changed the game when it comes to access.

As we think about this embrace migration towards virtual care, I think that patients are gonna get better outcomes. That’s just the start of it. So there’s factors out there like the digital divide, not every American has access to high broadband, but those are being addressed. When we think about 60% of one’s health is determined by just your zip code.

We can change all that with virtual care.

Maria Palombini
Wow. Just the zip code. It’s so astonishing to think about. And I think this leads to my next question on health equity. Especially as there are marginalized populations without access to healthcare for a whole myriad set of reasons, but telehealth technically should reach those who are the hardest to reach. So in your view, how can telehealth equitably reach the patients who are currently not included in the healthcare system? What do you see as some of the challenges that need to be addressed so that telehealth could be a viable platform to close this healthcare gap?

Shayan Vyas
I think this is the golden question that a lot of CEOs, health systems, and those in the ecosystem are trying to address. We mentioned one of those barriers is zip code, but also the digital divide. Almost two out of 10 Americans don’t have access to broadband. Telehealth equity needs to address that.

It’s one of the main reasons that we merged with Livongo almost two years ago. Livongo was the first publicly traded chronic disease management company. What made them very successful and continues to help us grow is that all of the devices within that are sent to the patient doesn’t matter if they have access to broadband or not.

Why? Because they’re cellularly enabled. There’s cellular chips in the device, right? So glucose is checked for diabetics. The glucometer is the device that actually checks the glucose. Those devices have cellular chips in them. So we are automatically connecting these patients no matter where they are cellularly.

As we think about those that don’t have access. You gotta design it. We’re talking to the future entrepreneurs, engineers of the world. You have got to think of the basic connecting blocks when it comes to patient care. And so that was an MVP. Livongo started to make sure that the devices were all suddenly connected.

When you think about the scale of what we do at Livongo, we are now able to predict what folks’ glucoses will be, or predict mental illness for patients. And so, that’s the full spectrum that needs to really be addressed when you think about a viable platform that can help close the healthcare gaps.

Maria Palombini
I think that’s really interesting and I think you started the segue to my final question. You’ve given us so many great insights and talking to you is always an educational experience.

Any final thoughts, Shayan, about what you would like to share with our audience as it comes to really developing virtual care technologies under this context of patient-centered care; maybe it’s a call to action or a call to think about innovation in a different way.

Shayan Vyas
First off, Maria, thank you. I appreciate the invitation. I hope so far that it’s been insightful for your listeners.

Here’s my call to action or innovation: spending in the United States’s Healthcare System doubles every 13 years. The healthcare industry today is over 3 trillion (U.S.) dollars. If we continue, we’re gonna destroy the economy. There will be no social security, no retirement, the investments that we’re trying to make in our infrastructure, in our children’s lives, that will all be robbed to pay for healthcare. And so we have got to jump on this. I’ve never been more excited about healthcare and innovation. I’m excited. I believe in Moore’s Law, that technology dramatically increases in power and decreases in cost and that’s what gives me hope.

As you and I continue to age and when we get sick one day, we would love that technology to be “Uber” easy, right? Travis Kalanick with Uber, Elon Musk, Jeff Bezos, and Steve jobs- they were able to transform the world we live in into just a new experience that 10 years ago, we wouldn’t have even experienced.

I remember my mom would tell me, don’t get into somebody’s house that you don’t know. We do that with Airbnb. My mom also told us not to get into a stranger’s car. Now we’re calling strangers to pick us up. And so if you think about how those transformative leaders really recreated the world we live in, I’d love for your listeners to stay curious.

Think about equity when it comes to all people and don’t accept the status quo. The way we do something today is not okay. Think about how you can transform the world. If you stay curious and you have that open mindset that you want to help everybody, not just the financially well off, and you really challenge what we do, why we do this today, don’t accept those things.

So I hope that’s motivation and I’m looking forward to watching IEEE help a lot of startups and entrepreneurs. And I appreciate the opportunity. Thank you, Maria.

Maria Palombini
Thanks, Shayan, this has been really great. It’s really interesting you mentioned aging. We just started an activity for telehealth around robotics to support the aging, healthy, and assisted living for the exact same reason. I think we are expecting our aging population to outpace our younger generations, for sure.

Again, special thanks to you, Shayan, for joining me today, it’s been an absolute insightful experience.

Shayan Vyas
Appreciate it. Thank you.

Maria Palombini
And for all of you out there, if you wanna learn more about Teladoc Health, you can visit teladoc.com

Many of the conversation concepts we had here today with Shayan are addressed in various activities throughout the Healthcare Life Science Practice. The mission of the practice is engaging multidisciplinary stakeholders and have them openly collaborate, build consensus, and develop solutions in an open standardized means to support these goals around innovation that will enable privacy, security, and equitable, sustainable access to quality care for all.

Programs such as Transforming the Telehealth Paradigm, WAMIII, which is Wearables and Medical IOT, Interoperability, and Intelligence, and a whole host of other things on Decentralized Clinical Trials and Digital Therapeutics for Mental Healthcare.

If you wanna learn more about these projects and all these different activities, you can visit our practice website at ieeesa.io/hls. If you enjoy this podcast, we ask you to share it with your peers, colleagues in your networks. This is really the way we get these important discussions out into the domain is by you helping us to get the word out. You can use #IEEEH LS or tag us on Twitter @IEEESA or on LinkedIn @IEEE Standards Association when sharing this podcast.

I wanna do a special thanks to you, the audience, for listening and continue to stay safe and well until next time.

Maria Palombini
Welcome everyone. This is the IEEE SA Re-think Health Podcast Series. I’m your host, Maria Palombini, Director of Healthcare and Life Sciences Global Practice here at the IEEE SA. This podcast takes industry stakeholders, the technologists, researchers, clinicians, regulators, and more from around the globe to task.

How can we rethink the approach to healthcare with the responsible use of new technology and applications that can afford more security protection and sustainable equitable access to quality care for all individuals? You can check out our previous seasons of the podcast series at ieeesa.io/healthpodcast.

So as a result of the recent pandemic, the term telehealth has become a frequently used one and it does not appear to be going away soon. The reality is, the way we see telehealth today will look very different tomorrow. It’s manifesting in many different forms. It’s more than what we commonly see as the doctor/patient exchange on an audio/video platform. It can be so much more involved with innovations in RPM (Remote Patient Monitoring), mobile health, hospital at home, and many different areas. The telehealth experience has changed the patient’s expectations on healthcare services. They’re relating it more to a concierge level, online retail experience: convenient, appropriate, and personalized.

And there’s the growing RPM space. So many different forecasts when it comes to RPM, anywhere from U.S. 150 billion by 2028 to estimates of 40% of patients utilizing one or two of these devices at one time. But one thing is for certain, regardless if we’re talking telehealth, mobilized health, RPMs, the future of delivering healthcare is not confined to a facility and will need to be patient-centered.

Season four of this podcast series, “Telehealth’s Quantum Leap Into Patient-Centered Care,” talks to the innovators, winners of our IEEE SA Telehealth Virtual Pitch Competition, the industry leaders, clinicians, and other researchers who are at the forefront of driving innovation with solutions on accessibility, human factor design, interoperability, security, inclusivity, and the other necessary ingredients to migrate healthcare to a patient-centered care system.

So just a short disclaimer, before we begin, IEEE does not endorse, advocate, or financially support any programs, services, technologies mentioned, or affiliated with any of the experts who have appeared in this series. And with that out of the way, it is my pleasure to welcome Ronald Pulivarti, NCCoE (for those out there, National Cybersecurity Center of Excellence), Healthcare Program Manager and Nakia Grayson, NCCoE IT Security Specialist. The NCCoE is part of the National Institute of Standards and Technology, NIST. Welcome, Ron and Nakia!

Nakia Grayson
Thank you to IEEE for inviting us to do the podcast interview. And thank you, Maria, for hosting the interview. We are so excited to be here today!

Ronald Pulivarti
I’ll echo that. Thanks a lot for having us and to the IEEE community. We appreciate the opportunity to do this podcast with you, and hopefully we’ll be able to engage deeper and we can get some great learning from our conversation.

Maria Palombini
Absolutely. I think for our global audience out there, this is gonna be a great experience. Before we get to the core, the technology, what’s going on. I like to humanize the experience for our listeners, right. We’re all in a virtual world. So Nakia, you started out in a different role while at NIST and then transitioned to an IT Security Manager.

What inspired that change? What do you love about the work you are doing now?

Nakia Grayson
Before we begin, Ronald, I would like to just say that opinions we are going to share in this podcast are our own and not the opinions or positions of NCCOE and/or NIST. So to answer your question, yes, that’s correct. I started off in a different role at NIST and actually in an administrative role and later transitioned into IT Cyber Security role in 2018.

For my undergraduate studies in college, I majored in criminal justice. When I graduated, I really wanted to bridge my education and knowledge of the legal system with a career in technology, policy, and privacy, because since I’ve, you know, found all of those areas, I was already fond of those as a teenager. While working in a lead administrator role at NIST, I went to graduate school for Information Technology and while in school I became really interested in data protection and cyber security risk management and how both of these play a very important role in protecting and safeguarding the nature of critical infrastructure and privacy and sensitive data.

I really love working on this. NIST gives me the opportunity to work alongside world class talent and industry experts to tackle and solve the most complex problems in cybersecurity and privacy.

Maria Palombini
Excellent. Well, Nakia. We have a lot in common because I also did my undergraduate in criminal justice, but again, I didn’t go that path either. But an unbelievable opportunity to be working at the forefront on cybersecurity issues.

So, Ron, how about you? I understand that you’ve had an exciting professional background working in organizations, such as Health and Human Services ,the HHS. What have been some of the most exciting areas of your work? What would you say are some of the major compliments you have seen during your tenure?

Ronald Pulivarti
It’s quite interesting. I’m a technology nut, so one of the things that I’ve always actually noticed when I started at HHS is I was the guy picking up the support phone. So from understanding the nuts and bolts to actually managing these ecosystems has been such a great opportunity. I’ve been able to launch myself throughout different agencies within the HHS space. I was able to contribute and strengthen the technology foundation so that we could grow. And one of the big things that I felt like I was able to provide in this space was my technology experience. I see something and I think five years to 10 years ahead on where we should actually be. And I think one of the things or opportunities that I enjoy doing was taking a look at the current snapshot on where things are, and actually contributing and making a significant impact within the government space so that we can advance and we can grow and strengthen the government technology, workspace, and ecosystem.

And I enjoy it each and every day.

Maria Palombini
That’s awesome. We all know that we have to love what we do otherwise it really will feel like a job. And then that is not the point.

All right guys. For our audience, you got a little insight to our background and to the things that really motivate our guests today.

So let’s get to the core. Nakia, we hear about all kinds of risk in the remote patient monitoring ecosystem. What are some of the major risks you are seeing that can no longer go unaddressed? In simple terms, what exactly are we up against?

Nakia Grayson
Some of the major risks that we’re seeing in the RPM ecosystem, speaking from an organizational standpoint that can no longer go unaddressed, is when HDOs deploy RPM solutions.

These solutions are architecture that includes several components across the HDO, the telehealth platform providers, and the patient’s home. So each of these environments is managed by different groups of people and often with different sets of resources and technical capabilities.

So risk can cut across the architecture and the different methods by which one may mitigate those risks. And it can vary based on the complexity of these. So while HDOs do not have the ability to manage and deploy privacy and cyber security controls, they do oftentimes retain the responsibility to ensure that the appropriate controls and risk mitigation are applied.

So in simple terms, a lot of data is being transmitted back and forth across various platforms which can lead to access points to cyber criminals . So we need to ensure that we have the appropriate controls in place. The safeguard systems look deeper in the current infrastructure as technology advances, ensuring that we also have education training for our patients.

Maria Palombini
Yes. I think that’s a very important point, Nakia, because we all think that it can just be a simple apply, a patch and let’s move on. We really need to talk about the whole scope of what it takes in security. And that includes educating patients, because a lot of them might be completely oblivious to what’s going on.

So Ron, we’re seeing growing trends of non-clinical, let’s call ’em consumer-issued health IOT devices, being utilized by patients. They share with their health providers. With this new integration, what kind of security and privacy risks are to be considered?

What are some possible solutions? Do we rely on the healthcare delivery organization, the device maker? Who needs to step up and start creating some solutions here for all this data in these devices.

Ronald Pulivarti
Very good question, Maria. One of the things that we all need to really consider and think about is that as these devices are evolving, they’re constantly listening to us, right?

So understanding exactly the use of it and what we’re using it for and applying that privacy and security standard on how you wanna communicate outward. So understanding your surroundings is a critical aspect of that. And all of the groups need to be involved from the technology provider, from the HDO, even from the consumer.

Understanding the layout as we do every day rely on our technology IOT devices to turn on lights, we rely on it to turn on and adjust the thermostat. These are constantly pinging in our whole household. One of the most important pieces for our project, our remote patient monitoring project in our appendix E in our practice guide, we actually talk about the benefits of these IOT devices.

We provide the device capability mapping, the device capabilities that support these functional evaluations. But one of the big things that we really need to factor in is what means of communication are we using this device for and what safeguards can we put in our own house with communicating, whether it’s medical information, personal information, when you’re talking to your bank. You have to utilize that space to ensure that if these devices are constantly listening to you, where is the safest part in your house, that safe house? And you could actually have these communications without exploiting any information that you have.

As Nakia pointed out, there are bad actors every day. We’re constantly fighting them. So using those steps, I think in place to understand that there’s a constant chatter that’s happening in the background. Where is that safe place in your environment where you could actually utilize these devices to ensure that you’re safe and you’re properly communicating things without necessarily having someone intercept something in some form or fashion?

Maria Palombini
And that’s absolutely a great point because I think in this world of everything “smart:” smart thermometer, smart this, we talk about ease and convenience and all these great things, but patient beware, right? You have to understand that all this “smartness” also comes with a lot of insecurity.

And so the same way you won’t leave your front door open, we really shouldn’t leave these kinds of things so open and vulnerable as well.

So Nakia, Ron, sort of, he did mention the guide. So I know that you all released this Securing the Telehealth Remote Patient Monitoring Ecosystem Practice Guide. Our team, the IEEE SA Transforming the Telehealth Paradigm Group, read it once it was released. We saw it was a bunch of great diverse companies involved in helping you guys create this project.

So can you share with us the supporting laboratory project around it? What was the idea? Was it tested in the lab environment to actually get to the final guide? Share with our audience the making of this guide.

Nakia Grayson
We get so pumped up when we have the opportunity to share our work. It’s great to hear that IEEE has found our work very useful. So the use of healthcare delivery organizations, HDOs, rely heavily on telehealth and remote patient monitoring (RPM) capabilities to treat patients at home. That has increased.

And some of the reasons why, is because RPM telehealth service is convenient and cost effective for all parties. And that’s the HDO, the telehealth provider, and patient. And one thing that we always want to share is that there are many actors in the RPM environment and that’s the HDO, the telehealth provider, and the patient.

So in our practice guide, we assume that the HDO’s engaged with a telehealth platform provider that is a separate entity from the HDO and patient. The telehealth platform provider managed distinct infrastructure applications instead of services. The telehealth platform provider, they will coordinate with the HDO to provision, configure, and deploy the RPM components to the patient home. Also assure secure communication between the patient.

We analyze the RPM ecosystem risk factors by applying methods to describe and our NIST risk management framework. We leverage the NIST cybersecurity framework and our NIST privacy framework, and other relative standards to identify measures to safeguard the ecosystem. In collaboration with healthcare technology and telehealth partners.

We built out a RPM ecosystem and a laboratory environment to explore methods to improve the cyber security of a RPM. So we brought in different technology from vendors to build out this lab. In our practice guide, we make a note that the application of people, process, and technology is very important in having that risk mitigation strategy.

So in our practice guide, the benefits that we stress is that we want to help an organization ensure the confidentiality, integrity, and availability of a RPM solution and enhance patient’s privacy and limit HDO risk when they are implementing a RPM solution.

Maria Palombini
I know that the telehealth guide was really thinking about the RPM in this environment. And this is where we are right now, but we know the trend. We hear it coming about bringing hospitals to the home and everybody’s thinking, this is the future. But how can the work of this practice guide be either applied in some form to address what we think is going to be a huge appealing, uh, cybersecurity appetite for the hospital at home concept?

Ronald Pulivarti
We’re a non-regulatory agency, right? So our practice guides are free for using it as a guidance for especially our targeted audience of these small and large scaled organizations. The way our practice guides are carved for folks to use, we have three different volumes in our practice guide.

We have our Volume A, it really talks about our executive summary of our remote patient monitoring. Then our Volume B is pretty much good for the actual overall architecture. It provides our approach, the architecture, the security characteristics. And then Volume C is really our how-to guide. We provide detailed instructions, how to implement our solution.

One of the things you touched on that’s very important is what was it back then to where we’re going to now. Telehealth is gonna be a very near to never going to go away type of technology. We’re gonna be utilizing this forever until something else new pops up. But I would highly encourage the folks to visit our website.

Our website is nccoe.nist.gov. So it’s nccoe.nist.gov. We have our practice guides that are listed for folks to take a look at and our remote patient monitoring practice guide is there. And Nakia has touched on it, it has valuable bits and pieces of information on the types of work that we’ve actually done specifically for this project.

Maria Palombini
Absolutely. Actually this podcast series, season two was all about cybersecurity and connected health. And all of my guests from around the world really never said it outright, but every time I asked them the question, it seemed like more, they were addressing the issue in the form of mitigation of risk in the connected health system.

So when we talk about cybersecurity talking more security or the mitigation of risk? The idea of a solution that someone’s going to develop someday can never be breached. Is that too much pie in the sky idea?

Nakia Grayson
I really like this question. As we sometimes look at these things as being different, we believe that we’re talking about the same thing. They work in conjunction. So privacy and security work hand in hand. Cyber security is more focused on the physical devices and privacy is focused more on the data.

But I think we’re talking about the same thing. You just really want to get to what is the best thing that we’re trying to provide? What are the solutions that we’re trying to assure that HDOs and small companies can do? And one thing that we mentioned is our practice guide is a great tool to be used to improve cyber security and posture and potential data risk when it comes to the telehealth ecosystem.

Maria Palombini
Absolutely. We didn’t go too much into privacy in this conversation, but they do go hand in hand for sure. Ron, what do you envision as the next best steps in attempting to better secure and protect this RPM ecosystem? We’re seeing more devices enter the healthcare sector with all these cool, smart features such as AI at the edge, that are not only gonna do monitoring, but at some point they’re going to make autonomous decisions without a human intermediary. So I imagine the risk level just goes up a little more in those kinds of scenarios.

Ronald Pulivarti
That is absolutely correct. One of the big and most important pieces here with the project and as we’re entering into new devices in our own home or different environments is understanding those risks with that architecture. We provide our privacy framework, cyber security framework, our risk management framework.

There are so many opportunities for learning to understand that level of risk. And one of the other pieces here is ensuring that your HDO as you partner with the right telehealth platform provider to extend that privacy and cybersecurity control deployment management and efficacy. One of the things that are out there is we’re constantly evolving in technology.

So you need to consider future technologies that can augment data communication safeguards. Also Maria, I will end off on this last note, which is important. Our website, we are actually pushing more and you touched on the word AI. We’re exploring so many different capabilities that are out there within the national cybersecurity center of excellence that consumes not just our remote patient monitoring piece, but we have different areas within our center. We have 20 active projects, for example, over at our center that we’re constantly looking for collaborators in. So one of the things that when, and if folks get the opportunity is again, check our website and look underneath the security guidance tab. And you have different areas by different sectors that we are looking for collaborators in.

We publish information out. We look for feedback as your comments are very valuable for us to constantly improve our information as we’re rolling it out for consumption. So take a look at that underneath again, the security guidance tab, we have different sectors that are available and as we’re evolving in different types of technologies and those areas of interest, we have our practical, usable, repeatable guides that are there and also we love feedback. So there’s a community of interest distribution list under each of these sectors. Do register. Be part of our experience to help improve our current infrastructures that exist today.

Maria Palombini
Absolutely. Last season was AI for Good Medicine. We had so many great different use cases and ideas there. We’ll make sure our guests and our audience are aware of these other opportunities at the NCCoE.

You guys have shared so many great insights with us already. You know, the guide I think is awesome.

I’m gonna pose this question to both of you and I’ll ask Nakia to go first. Any final thoughts you would like to share with our audience as it comes to developing remote care technologies under the context of patient-centered care? Any interesting upcoming projects, plans of action? Things just to think about in general? What is your parting final thought Nakia ?

Nakia Grayson
So I would say that if you haven’t already checked out a RPM Practice Guide 1800-30, we definitely would encourage everyone to read it, check it out. And if you have any project ideas to contact our team. We would like to mention that when we published our RPM practice guide, we also published two tip sheets focused on telehealth. One is for the patient and one is for the provider. Each tip sheet includes a couple of strategies on what each can do. As far as the patient, the provider, to mitigate cyber security and privacy risk or other telehealth services.

And I’ll turn it over to Ron to share about upcoming projects.

Ronald Pulivarti
Thanks, Nakia. Yeah, Maria, we’ve actually had two great virtual workshops. We had one just recently was the virtual workshop on our smart home integration project. The turnout was phenomenal. We had a lot of speakers. We had technology providers, health delivery organizations there to contribute, and we had an open panel discussion. That was wonderful.

Aside from that, we also had our exploring solutions for cybersecurity of genomic data. That was a two day workshop we had. We provide a lot of information for individuals that are registered in our community of interest for each of our different sectors, register! As we have more and more virtual webinars, and hopefully sooner than later physical workshops together. We send out communications and we post it on our website. So register for a community of interest so you’d be notified whenever we have our webinars or workshops. You will also get the opportunity to be part of our draft guidance for the public to consume and provide feedback. You’ll be notified whenever we need comments. So please do so. A lot of these projects that we do here, we try to make it very informative for people out there that actually need to have some type of guidance or some type of framework.

And because we’re such an organization where we rely on collaboration, it’s very important to get people to get involved with us. So once we’re in our labs, once we’re together, we can really do a deep dive and really figure out where these problems reside in which we can actually provide some type of output for a solution that folks outside of our lab can actually, um, use.

Maria Palombini
Absolutely. I mean, I subscribe when I get those updates as well. The IEEE SA volunteers and various projects have responded to NIST calls for feedback and that kind of thing. So for our audience, whether you’re with us or you’re on your own, definitely we are in many ways involved in trying to help the overall global community address these big challenges that we’re facing.

Ron and Nakia, thank you so much for joining me today. It’s been an absolute pleasure.

For all of you out there. If you wanna learn more about all the work going on at the NCCoE at NIST I say, all roads lead to the website, nccoe.nist.gov. All the information, as Ron and Nakia mentioned, is free for you guys to consume. I think it’s a great resource if you’re in this space, whether you’re technical, you’re innovation, you’re a clinician. I think it’s valuable for anybody to read it.

A lot of the concepts we talked about today are addressed in various activities throughout the IEEE SA’s Healthcare Life Science Practice.

Our practice is really engaging multidisciplinary stakeholders from around the globe who openly collaborate. They build consensus and develop solutions in the form of open standardized means to support innovation that will address these issues of privacy, security, and equitable, sustainable access to quality care for all.

Some of our programs: Transforming the Telehealth Paradigm Industry Connections Program and WAMIII, which is where both Medical IOT Interoperability Intelligence cuts to the core of a lot of the discussions we were having today. If you’re interested in learning about these projects and all the other areas we’re involved in, you can visit ieeesa.io/hls.

So if you enjoy this podcast, we ask you to share it with your peers, your colleagues, through your network. This is the way we can get these important discussions and ideas out into the domain, is by helping us get the word out. Be sure to use the #IEEEHLS or tag us on Twitter @IEEE SA.

Special thank you to our audience for listening in, continue to stay safe and well until next time.

Maria Palombini
Welcome to the IEEE SA Re-Think Health Podcast Series. I’m your host, Maria Palombini. I am Director Healthcare and Life Sciences Global Practice here at the IEEE Standards Association. This podcast takes industry stakeholders, technologists, researchers, clinicians, regulators, and more from around the globe to task.

How can we rethink the approach to healthcare with the responsible use of new technologies and applications that can afford more security, protection, and sustainable, equitable access to quality care for all individuals. You can check out our previous seasons on ieeesa.io/healthpodcast.

So as a result of the recent pandemic, the term telehealth has become a frequently used one and it does not appear to be going away. The reality is the way we see telehealth today will look very different. Telehealth is manifesting in many different forms. It’s more than what we commonly see as the doctor patient exchange on an audio/video platform.

It is so much more than that and continues to evolve with innovations in RPM, remote patient monitoring. The telehealth experience has changed the patient’s expectations on healthcare services. They’re relating to it more of a concierge level of online retail experience: convenient, appropriate, and personalized.

And then there’s this growing RPM space. There’s so many different forecasts when it comes to RPM, anywhere from 150 billion U.S. Dollars by 2028 to estimates of 40% of patients using one or two more of these devices at one time. But one thing is for certain, regardless if we are talking telehealth, mobilized health or RPMs, the future of delivering healthcare is not confined to a facility.

It will need to be patient-centered. Season four of this podcast series, Telehealth’s Quantum Leap into Patient-centered Care, talks to the innovators, the winners of the IEEE SA Telehealth Virtual Pitch Competition, the industry leaders, the clinicians, and other researchers who are at the forefront of driving innovation with solutions on accessibility, human factor design, flexibility, security, inclusivity, and all the other necessary ingredients to migrate healthcare to a patient-centered care system.

So just a short disclaimer before we begin, IEEE does not endorse or financially support any of the products or services mentioned by or affiliated with our guest experts in this series. It is my great pleasure to welcome Dr. Keith Thompson, Chief Medical Officer of NuraLogix Corp to our conversation.

NuraLogix was one of the nine finalists to make it to the pitch round of the IEEE SA Re-think the RPM Machine Virtual Pitch Competition. NuraLogix is an AI-powered solution for instant health and wellness data from your smartphone. I love this line on their website, so I’d like to share it with you all. It says: take a selfie to know you’re healthy.

And obviously Keith will share with us what that means. But in the meantime, one of the reasons why I really enjoy having Keith on this podcast is that he is co-leading a Pre-standard Work Stream, entitled Virtual Care Lexicon in the IEEE SA Transforming the Telehealth Paradigm Industry Connections Program.

So Keith, welcome to our podcast!

Keith Thompson
Thank you. Great to be here today. Really appreciate this opportunity.

Maria Palombini
Keith, you have a very well-established career in primary care as a family physician. You are an advocate for utilizing virtual care and telehealth to reach patients. You have demonstrated passion in helping patients in everything from WONCA, the World Organization of Family Doctors, but really what inspires you about the opportunities of virtual care? Most doctors are slower to technology adoption and you seem to embrace it so well. How did you get involved?

Keith Thompson
Thanks, Maria. I’ll be honest. I was really a late bloomer to technology and I jokingly say at this stage of my career I haven’t a lot of time left, so I have to make the best of it, but just seeing the advancement of technology and where workflows were going and how we were embedding this into our day to day encounter just really fascinated me. And obviously you start to see ways of doing things better.

Maria Palombini
Like they say, better late than never. So I’m so glad you migrated to it.

Keith Thompson
Yeah, absolutely.

Maria Palombini
So can you just briefly share with our audience the goal of the work that you had started with the virtual care lexicon work stream? Are you looking to standardize and how will it positively impact the future of telehealth and virtual care?

Keith Thompson
I came to IEEE as a clinician. So just to clarify, I’m not an engineer by any means, but love what it has done just hanging out with this group. It’s an interesting combination of the humanistic and sort of the artisan form of interacting with patients, but that zero room for error and an effort to try and make things perfect. The lexicon that was started really under the IEEE Telehealth Industry Connections that I came to, not really knowing what I was getting into, initially, it has become what started as an attempt to define telemedicine, both technically and use cases and specifically terminology.

And I see where we’ve moved more recently is into that realm of culture and linguistic appropriate services. How do we make this encounter better for the people that we’re trying to engage? And so how we can use that ICT, you hear that term Information Communication Technology, using it in healthcare, but an effort to connect both the materials for health and device literacy, the other area we’re getting into. It’s connecting those educational materials on a system like GUDID, the Global Unique Device Identifier Database, and there’s really a disconnect there. So we realized the first step within the lexicon, we hope to eventually get to a PAR in this class or culture linguistic appropriate services and, or the health and device literacy. Both of those are getting traction.

We’ve begun to explore some collaboration here in Canada, actually with indigenous communities. There’s some interest in the language resurrections and the standards that might result in making that telemedicine encounter culturally safe for first nations. And this is a huge part of what’s going on here in Canada, as we’re in the midst of reconciliation within our indigenous community.

So a project like this within our lexicon really might not only provide an output for standards around connectivity and databases. And what would this look like? So we can share that information with others, attempting to do this, but here in Canada, be incredibly healing, part of a supportive measure just to make telemedicine or virtual care culturally appropriate specifically for indigenous communities.

Maria Palombini
I think that’s a fascinating project and it can transcend many different ways across geographic and other aspects as well.

You went from doctor to Chief Medical Officer of a cutting edge technology company. So NuraLogix uses AI and machine learning, and it offers patients this ability to take a selfie and determine their level of wellness. Just for our audience, what exactly is it monitoring? What area of the population pool does it really serve and what makes this platform so unique?

Keith Thompson
I’ve recently come to NuraLogix and my background was within telemedicine. I’m a primary care doc first and foremost. So my day job is seeing patients. So my side gig was boring and trying to get some telemedicine endeavors off the ground.

We had a working relationship with NuraLogix and I was immediately fascinated. I was like, wow, this takes telemedicine to the next level. Being able to grab patient parameters and some biometric measures within that encounter. So the technology is a novel form of RPPG called Transdermal Optical Imaging and TOI is our trademark terminology. So by capturing blood flow, using that principle of reflected light, we’re not just measuring one region with TOI. We’re actually measuring 21 regions in the face and each region of the face acts differently. Your cheeks behave differently than your nose and your forehead.

So we’re able to capture that pulse wave form and then do feature analysis using machine learning models that are trained on 40,000 patients. And we can capture those patterns in the data sets that allow us readings on over 40 to 30 or more parameters for patients being scanned. So we’re able to capture vital signs, metabolic biomarker risk, cardiovascular risk, mental health stress related to HRV variability, and metabolic risk for diabetes of lipids. So our blood pressure is really our crown jewel. We are engaged with the FDA in a pre-submission. So our claims on this measurement still have to be validated as we get into that territory of class two medical devices. So you’ll see a disclaimer everywhere for investigational purposes only.

That’s really why we’re about to start clinical trials. We’re pretty confident with the technology. We’ve published data verifying that we can meet the ISO 81060 standards. And so can claim accuracy on that. And we have also published some data on our biomarkers of mental stress. The population that we’re serving really the intended use is to screen for risk factors and chronic disease states, under the care of a physician.

We’re not trying to replace the lab or replace the doctor encounter, but just build that awareness. So our solution can really identify if you’re at risk for cardiovascular, hypertension, diabetes, mental stress, heart rate variability and so many metabolic risks as well that we capture.

We’re soon going to launch hemoglobin A1C, an elevated morning fasting blood sugar. So it’ll be a classifier model. Yes, no. Are you above or below a certain level? And if you look at the World Health Organization, it really identifies hypertension type two diabetes and mental stress. Those leading causes of morbidity mortality.

You can see that we’re focused with our solution on those major epidemiological indicators for NCDs, you’ll hear this term Noncommunicable Diseases, and that’s really the big push. So we want our platform hopefully to be available to as many people as possible so they can understand and just be aware of their own health risk.

And we hope to identify those populations at risk before disease develops or its related complications. So the first step in health literacy really is awareness and that’s where we intend our tool to be used.

Maria Palombini
I think that’s really important. And I think you already touched on a misconception that we often hear, oh, I’m using these wearables and it’s monitoring me. So maybe I don’t need to see the doctor as often. And it’s like, no, this is supposed to be in support of.

Keith Thompson
Yeah, yeah.

Maria Palombini
So yeah, important. And it comes right from the doctor’s mouth. We hear a lot about patient centered care and patient centered this in the healthcare system. So when you think of remote patient monitoring devices, systems transforming, or trying to get to this patient-centered care system, where do you think there’s more attention needed or innovation needed to really transition RPM into a true patient centered care model?

Keith Thompson
Honestly, so many things come to mind. I think for me, and really I have to give IEEE and some of the mentors I’ve been working with credit for this, but the first thing that comes to me is equitable access. So what we’ve seen such a digital divide in society is we become more technology based. Yet those social determinants of health in which you hear about have really also become digital determinants of health.

They’re one in the same. The UN declared internet access as a basic human right, almost 10 years ago and we’ve made great strides in improving connectivity in internet access, but there’s still significant disparity, especially within those low middle income regions and marginalized populations where it’s either complex care needs, high urban density or folks with disabilities.

So the application of monitoring systems to the patient point of care, I think will move care closer to the patient in terms of capturing data. But then what sort of ecosystem and workflow are we creating in conjunction with the physicians embedded into that remote patient monitoring workflow and will we see the need for physicians in that workflow at all?

Will patients still want some sort of humanistic attachment and I’ve been diving into a thought leader here; she’s since passed away Ursula Franklin. She was an archeologist by trade, but released a whole thought process around technology. And she talked about technology being either prescriptive, right?

There are rules that you must follow or humanistic or holistic. And really medicine, when you think of it, certainly primary care, is holistic. So how do we combine those two things? And how much can we transfer over to the technology side and at what cost are we losing the holistic aspect? Also, just to comment that healthcare access really is only 25% of those health outcomes. In other words, getting access to healthcare doesn’t solve those issues around social determinants of health, which play a far bigger role in health outcomes. So improving those social determinants is needed, providing the technology or access to care just with technology may not achieve that end result or outcome that we’d expect.

So I think remote patient monitoring also points us to an era of high volume and low physician touch, which I say physician specifically, because there’s another technology thought leader here, Marshall McLuhan kind of another philosopher. He said that the age of technology will be the age of do it yourself.

That’s so true and we see as the knowledge in technical skills are now prescribed or advanced to systems. It could be a Google search to determine my symptoms or at some point AI or machine learning control of robotic surgery or diagnostic systems we’re already seeing. I think there’s a lot of unanswered questions as things go forward, but equity of access for sure is a key ingredient we have to maintain.

And I think that’s what IEEE and SIGHT and HAC have really been focused on and really passionate about. And it’s been great working with this group.

Maria Palombini
Absolutely. It’s really interesting though, you mentioned the social determinants of health. In season three, AI for Good Medicine, I actually interviewed the CTO of Closed Loop AI and one of their core projects on COVID 19, like the effective risk and outcomes was using data of social determinants.

The idea was to really look at the social determinants rather than just therapeutic risk based factors that really improve the outcomes.

So we prefaced this a little bit, but there’s a lot of misconceptions around, you know, remote patient monitoring devices. You know, patients are not going to adhere, the data can’t be validated, this thing is only gonna do so much. When you think about it, what do you see or what do you think is one of the biggest misconceptions when it comes to the concept of telehealth, whether it’s from a patient perspective, a physician perspective, the payers, or any other stakeholder in the process?

Keith Thompson
I think I may be biased from where I am as a physician, but for me, the biggest misconception might center around workflow. For telemedicine to be truly sustainable for physicians and payers, for that matter, it needs to be efficient and optimized in terms of workflow. So this means it supports both patients and providers so that they’re both literate and trained in the pre-visit, during the visit, and post-visit follow-up. What does that workflow look like? How much can we do digitally? Via surveys, questionnaires is a translator needed, is connectivity appropriate? What digital modality is best video or telephone, and does a patient have access to that modality?

I feel there’s some misconceptions maybe from payers, just how much time is involved in a good telemedicine encounter. So even without telemedicine, EMRs (Electronic Medical Records) have significantly increased physician admin burdens, right? The time we spend, we see so much greater integration of technologies to improve the depth of that encounter and using virtual care tools, but we increase the clicks, the log ons several minutes added to that encounter. So how do we cover that added admin time with limited healthcare budgets? So we’re expanding the non-clinical part of that encounter. There’s a disconnect really between the system designers and payers and patients’ and providers’, real world experience.

So payers, providers and patients that digital journey that everyone goes through to access and provide care experience firsthand, go through it. Co-design is so important. Right? So what’s the actual experience for all these actors coming into the system?

Maria Palombini
Absolutely. And I think these are all relevant points, because we all think, oh, we have a new technology tool. It’s gonna make everything go faster. But the transformation is not just the technology, the digital side of it. It’s the whole process that has to be aligned with it. Otherwise maybe we’re just making more work for all of us in the process.

So I often say, I write about this, I talk about it that the future of telehealth will look very different than we see it today.

As a physician, I think for you, why is it important to envision a potential future of mobilized care? We hear about the tele ICU in the future, the mobile urgent care units, but this idea of bringing healthcare to the home, how do we really see it improving patient outcomes?

Keith Thompson
It’s an interesting question, Maria, and I think the question really challenges us to look more closely at telemedicine virtual care and its applications under the same lens that we would use for other interventions, i.e. Pharmacoeconomics right. We talk about human economic outcome or health economic outcome research and cost benefits, cost effectiveness, cost utilization cost minimization.

So cost minimization, assuming that the outcomes are equal, but we can deliver care cheaper or maybe there’s benefits in terms of lower hospitalization. So you can see moving patients into home. Absolutely, one or two days saved from a hospital admission saves thousands of dollars or reduced ER visits. Cost effectiveness is more in actual natural units. So would an intervention, lower blood pressure, and there’s studies on this, right? By partnering with patients digitally, you can prompt them to take their blood pressure meds, to exercise, behavioral change, and we can see effective gains. Lastly, cost utilization, that’s quality adjusted life years, and that’s harder to put a dollar value on, right.

Is that ease of, of access, not having to travel to the doctor and, and all that. That’s convenient. So I think we have to be careful that not all care transitions to virtual in a cost effective manner, we might, for example, see physicians order more needless tests to compensate for that insecurity, a lack of an exam.

And some studies have hinted at this. On this angle, patients might feel that seeing more than one physician just due to ease of access. And I had that counter, you know, with a patient coming to see me and saying the video assessment wasn’t really an exam doc. I needed somebody to listen to my lungs. Right. So we had two visits that could have been done in one. I think we’ll need to apply a little tougher if you look at the economic lens and it makes everybody cringe because we know the convenience. We know the patient’s love of, of ease of access and lower costs for physician encounters. For sure. But in the global economy, what does it look like?

Yeah, we may have to be careful.

Maria Palombini
Yeah, absolutely. We kind of just touched on this before, but we hear of oh, we’re bringing healthcare into the home. Right? Do we really still need doctor’s offices and hospitals and you sort of just led into that. But the real question is, how is that dynamic changing in this area of healthcare? Right? Like thinking of the hospital as the place to go for care.

Keith Thompson
There’s so many forces at play here. And certainly there is in the medical system and physicians, especially in primary care, we want continuity and longitudinal relationships. The patients want convenience of access in some ways opposing forces. Right? So I, I believe the hospital’s always gonna be the go-to for surgical treatments, radiotherapy, for example. But days in the hospital will no doubt be shorter. And I think the post-operative timelines move into the home with less inpatient time. So the question, or perhaps the danger is, is going more into remote patient monitoring and home based care. How far is a physician interaction with its patients removed from that digital ecosystem?

You saw one of my recent posts on LinkedIn, right? With an RPM system that got hacked. You could do a whole thing on security. I’m sure. All the actors weren’t notified, but the poor docs and nurses involved for that remote, fetal heart monitoring, the system was down.

Nobody knew. Patient didn’t know, physicians weren’t notified, and there’s gonna be a really messy lawsuit as a result. The other part to this, how much of that face to face is therapeutic, and really can’t be replaced by a digital workflow. And I’m not sure we know the answer to that yet, but there’s one person that can tell us and that’s the patient. Just, as I mentioned before, about Ursula Franklin, you know, that prescriptive force of telemedicine and remote patient monitoring becomes so strong that this becomes now the only way of doing things. And so i.e. that digitally and remote patient monitoring fewer face-to-face visits, but how holistic and compassionate is that healthcare system, will it be at that point?

We can, yes, have ISO 9000 perfection and supersede that need for human touch and interaction with patients, you know, how far do we go and who knows, certainly this is where we need to dig down. I think a bit more and perhaps further research on patient reported outcomes and satisfaction and not just healthcare dollar saved.

Maria Palombini
Absolutely. And I think it’s an important point that we always talk about stakeholder trust and everybody thinks well, will the patients trust the process and the device, but we also need the doctors and the clinical workers to trust it as well. And so if workflows are not designed to best mitigate risk for all the parties involved, then we’re gonna continue to have this question of trust.

Keith Thompson
I wish honestly, every one of my colleagues could at least do a couple of stents in some of our meetings to learn about that issue. I trust that my device is measuring properly. I have no idea the standards and the protocol for that trust. And I can think differently about calibration now and how I approach, you know, just simple measurements.

Maria Palombini
So we’re kind of leaning into this question here and I think you mentioned it as well earlier on, this question of health equity, right. We know there’s marginalized populations without access to healthcare, or very limited access to healthcare or understanding of the healthcare process. So telehealth technically right should reach those who are the hardest to reach.

Keith Thompson
Yeah.

Maria Palombini
So Keith, in your view, how can telehealth equitably reach the patients who are currently not included in the healthcare system. What do you see as some of the challenges that need to be addressed? Obviously you mentioned the language was one, but that telehealth could be a viable platform to try to close this healthcare gap.

Keith Thompson
As I mentioned earlier, those social determinants become digital determinants. They become one in the same in my opinion, but apply that technological access to a marginalized population doesn’t unto itself, improve an outcome. Certainly, access I think is the cornerstone. We’ve gotta have a secure line into those communities and it should be a basic human right just as clean water and food security. And beyond this, I think then we look to focusing or leveraging community health workers within those communities. You know, we’ve had some presentations here with IEEE Public Health Foundation of India and Dr. Aaron Jose and their telemedicine program.

Look it up, doing some great work, partnered telemedicine with community workers, right. To be that line in. We partnered at NuraLogix with LaFiya to put telemedicine kiosks into remote regions of Nigeria. What’s interesting about that platform is the solar panel that they put in that community is being used as a resource to provide some micro economies that might be the alternative business model, because really the issues move away from solving the connectivity to solving those social innovations and business models to support those regions. So there’s no longer value in the model of just selling devices and multiple units to providers or consumers rather, how do we fund a single device and platform and scale to regions needing support for tens of thousands of patients without access to primary care. The technology’s great, but we really have to keep our eyes on the ball I think on the sustainability and business model, because it’s certainly talking about compassion and humanitarian reach. I think you’re sort of assuming that it’s for free and it’s, you know, NGO and it’s a philanthropic offering, but there’s ways to do it right. That we can support communities with technology and help them sustain themselves.

Maria Palombini
Absolutely. Very, very good. All right. So Keith, you’ve given so many insights. I think your perspective as a physician working in a really technical environment is really, really refreshing. Any final thoughts you would like to share with our audience? It could be technologists who are embarking in virtual care technologies or already there and looking at this context of patient set and care, it could be a call to action, a call for attention and innovation.

Keith Thompson
Yeah. You know, really honestly, just to say thank you to you and IEEE, right? That industry connections and SIGHT, this organization has been an incredible mentor and inspiration for me.

I’ve said that combining engineering design with zero error and medical humanitarian applications, right? Compassionate care here has been an incredible journey. So call to action. Get involved in this organization, if you can, you’re gonna grow personally and professionally. And I guarantee, you know, become a better person just by helping address those needs of humanity using technology and last thanks to NuraLogix for supporting me in this right.

They’ve encouraged me, no questions asked. I love it. So great. I really appreciate Maria. Thank you.

Maria Palombini
Thank you, Keith, you always got so many great insights, your passions, and, you know, for humanitarian causes and just overall, just your empathy for patients. It’s just very refreshing.

So thank you for taking the time and being part of this podcast today.

For all of you out there, if you wanna learn more about NuraLogix, you can visit nuralogix.ai. If you would like to get involved in the work stream, Keith mentioned virtual care lexicon, or other aspects of the IEEE SA Transforming the Telehealth Paradigm Incubator Program, visit ieeesa.io/telehealthic.

Many of the concepts we talked about today with Keith are addressing so many different activities here at the IEEE SA Healthcare Life Science Practice. You know, the mission of the practice is engaging multidisciplinary stakeholders, such as Keith and they openly collaborate. They build consensus and develop solutions in an open standardized means to support innovation that will ultimately help us achieve the goal of privacy, security and equitable, sustainable access to quality care for all.

Activities such as the Transforming the Telehealth Paradigm, the WAMIII, Wearables and Medical IOT, Interoperability Intelligence are just naming a few of the different activities here. And if you wanna learn more, how you can get involved, there’s no cost to join these activities, you can visit ieeesa.io/hls.

If you enjoyed this podcast, we ask you to share it with your peers, your colleagues on your networks. This is the only way we can get these important discussions out into the domain is by you helping us get the word out so you can use the #IEEEHLS or tag us on Twitter @ieeesa, or you can tag us on LinkedIn @IEEE Standards Association when sharing this podcast.

So a special thank you to you, the audience, for listening in today and continuing to stay safe and well until next time.

Maria Palombini
Hello everyone. I am Maria Palombini and I am the Director of the Healthcare and Life Sciences Practice here at the IEEE Standards Association and welcome to the Re-think Health Podcast Series. This podcast takes industry stakeholders, technologists, researchers, clinicians, regulators, and more from around the globe to task: how can we rethink the approach to healthcare with the responsible use of new technologies and applications that can afford more security protection and sustainable equitable access to quality care for all individuals? You can check out our previous seasons on ieeesa.io/healthpodcast.

So as a result of the recent pandemic, the term telehealth has become one of the most frequently used ones and it doesn’t appear to go away soon. The reality is that we see telehealth today will look very different tomorrow. It’s manifesting in many different forms. It’s more than what we see in the doctor/patient exchange on an audio video platform. It continues to grow with the proliferation of RPM devices, remote patient monitoring devices.

And we see that the telehealth experience is really being changed by the patient’s expectation on healthcare services. They are more relating it to a concierge level of online retail experience, convenient, appropriate, and personalized. With the growing RPM space, there are so many different forecasts when it comes to this, it could be U.S. 150 billion by 2028, or that more than 40% of patients will be utilizing one or two of these devices at one given time.

But here’s one thing we know for certain, regardless if we’re seeing telehealth, mobilized health, or RPMs, the future of delivering healthcare is not going to be confined to a facility and it will need to be patient-centered. So season four of this podcast series, Telehealth’s Quantum Leap into Patient-centered Care talks to the innovators.

These are the winners of the IEEE SA Telehealth Virtual Pitch Competition. We talk to the industry leaders on the platforms leading the way, clinicians, and other researchers who are at the forefront are driving innovation with solutions on accessibility, human factor design, flexibility, security, inclusivity, and more.

These are all the necessary ingredients to migrate telehealth care to a patient-centered care system. Before we begin just a short disclaimer, IEEE does not endorse or financially support any of the products or services discussed by our guest experts in this series. With that out of the way, it is my pleasure to welcome Pramuka Sooriyapatbandige, a final year undergraduate student at the university of Jaffna in Sri Lanka, specializing in electrical and electronic engineering.

He’s a student member of IEEE and he also placed first in the student category with his project, Multi-purpose Health Monitoring Bracelet in the IEEE SA Virtual Pitch Competition: Rethink the Machine – Transforming RPM in a Patient-Centered Care System. Pramuka, welcome to our podcast.

Pramuka Sooriyapatbandige
Thank you

Maria Palombini
Pramuka, before we get to the core of the innovation, we like to share with our guests a little bit about the person behind the technology. So can you tell us a little bit about your research work and how you and your team came together to develop this project?

Pramuka Sooriyapatbandige
Yeah. With the COVID 19 pandemic, Sri Lanka University started to explore possible supports that could be contributed to manage the pandemic situation in the country. And during this period, we also needed to identify the research project to fulfill the requirements of our undergraduate course.

And this is when Mr. Valluvan, who is our current supervisor, proposed the idea of RPM, and we started working together. It seemed very time appropriate and aligned with our research interests. Also, we were able to get the assistance of Dr. R. Surenthirakumaran and Dr. Sivasothy, who were already contributing to some of the university’s initiatives during the pandemic time. They helped us develop the concept further.

Maria Palombini
Excellent. I find that most of the time, when I talk to technologists/entrepreneurs, there’s always a motivation, like a life story or some sort of passion that drives them to develop this innovation, this technology. Can you share with us maybe something you and your professor, your team members, something that was the real motivation to really take this project to the level and try to make it accessible to the underserved populations in developing regions?

Pramuka Sooriyapatbandige
The motivation for this project comes from what we saw and experienced around. Globally, non-communicable diseases, cardiovascular diseases, cancer, diabetes, and chronic respiratory diseases account for over 70% of deaths. And three quarters of all NCD deaths occur in lower and middle income countries. And nearly 85% of global premature deaths from NCDs are reported in these countries, whether developing countries, Sri Lanka faces similar issues as other low middle income countries, where some problems are unique to Sri Lanka. NCDs are estimated to account for 75% of total debts in Sri Lanka with nearly one in five people dying prematurely from NCD.

These NCDs tend to be of long duration and have characteristics of insidious onset, chronic clinical manifestation, and long-term disability in the face of poor control. And most patients with NCDs are diagnosed in later stages, particularly after developing serious symptoms or complications. So in October, 2015, the United Nations Interagency Task Force on NCDs conducted a mission to Sri Lanka and it concluded that epidemic of NCDs has become a serious economic and public health issue in the country. And it’s fueled by tobacco use, unhealthy diet, alcohol consumption, and physical inactivity. The health system of Sri Lanka is considered a highly successful low-cost model. It is widely accessible and it has services offered by the public healthcare system, are free at the point of delivery, and other factors like wide coverage, female literacy have resulted in remarkable health indicators in the country. However, strengthening primary healthcare with comprehensive community based and family focused care, it’s the solitary solution to address the existing health issues in Sri Lanka.

So we believe that home-based monitoring of the essential health parameters is very important and that growing technology should address this need. So we thought our solution would be suited for this purpose. So this is actually the motivation behind our project.

Maria Palombini
Very fascinating and very important. So now we’re gonna get into the core of the innovation. We know for patients with chronic NCDs, non-communicable disease conditions, without easy access to healthcare, RPM, remote patient monitoring devices may be the lifeline they need to minimize risk of urgent hospital visits or other unplanned clinical visits and especially when we’re in developing regions, it’s not like there’s hospitals and clinics easily accessible to your “fingertips,” as we say. For individuals in developing regions RPM devices that are accessible (and accessibility can come in many different ways) can be a significant contributor to improving their health.

So Pramuka, what stage is the multipurpose health monitoring bracelet? Is it a concept or is there a prototype, have you had any testing in the form of a pilot done with it? What are some of the findings? What’s actually going on with this particular product right now?

Pramuka Sooriyapatbandige
Currently, we have the proof of concept prototype and we are in the process of making the final prototype, which is pilot-ready.

Maria Palombini
Can you share with us the type of research you all did, the modeling, maybe levels of work that went into actually refining this proof of concept prototype? And what would you say was the most interesting piece of information that came through in this research and discovery phase of the product?

Pramuka Sooriyapatbandige
Certainly. At first we looked into the requirements and it was quite a challenge as we had minimum exposure to the biomedical field. When identifying requirements, we had to study the vital signs, how they’re measured and existing technologies. We also looked into existing RPM solutions. As we were looking into developing a wrist wearable device, we realized that all our measurement requirements could not be fulfilled by the wrist wearable device alone.

And this is where we came up with the capability to connect add-on devices. Initially, we intended to measure a set of limited measurements and vital signs. But we were astonished that the capability to connect add-on devices would give our device the unlimited expansion of measurements, making our device the hub or centerpiece of a remote health monitoring system.

For the development, we followed the modular approach where we developed and tested different functionalities separately and later put them together as one device.

Maria Palombini
That’s fascinating. So you all are developing a device that’s accessible, right for a developing region, but also now it’s scalable.

So, can you explain how it can interoperate with other devices, such as a pulse oximeter, a blood pressure cuff? Does it require that a specific type of device can connect with the bracelet or is it the multi health monitoring bracelet that can work with any device by any manufacturer?

Pramuka Sooriyapatbandige
When building the multipurpose health monitoring bracelet, we studied the capability and size of the sensors that can be used for medical purposes. And if the sensor cannot be accommodated within the bracelet or measurement cannot be made at the wrist, we tried to use wireless connectivity, such as Bluetooth to connect the measurement device and bracelet. Therefore the bracelet gets the capability to include additional medical measurements. So when using BLE wireless connection, BLE generic attribute profile (GATT) is a better choice.

It is standard-based and this profile helps interchange data between two BLE devices. Manufacturers can implement those profiles to communicate with MHMB, for example, already some profiles, blood pressure, heart rate, pulse oximeter, insulin delivery service, low-cost profiles are available in BLE standard organization and existing devices can be easily modified to include this capability.

Maria Palombini
Great. Obviously we see so many new devices coming into the market, but unfortunately they don’t really integrate with many other things or they’re not scalable or extensible. So this is really important. I think this can be a significant attribute, especially to a population who doesn’t have so much access to healthcare.

Pramuka, one of the biggest challenges we see in remote patient monitoring, is the issue of accessibility. And like I said earlier, accessibility can mean a whole bunch of things could be from a point of view that people can’t afford. It could be that people don’t know how to use it, because it’s too technical. It could be a whole bunch of things. So I know that you mentioned that one of the main features of the MHMB is that it is accessible, especially to individuals in developing regions where they don’t have easy access to healthcare. So in helping that population of patients, what makes it so accessible?

Is it that it doesn’t require high frequency bandwidth, like consumption of data or internet, or is it something that can easily communicate? It’s very easy to use. What makes it accessible for this population?

Pramuka Sooriyapatbandige
Our device stores data locally when not connected to the internet and pushes to the cloud, as soon as it is connected again. So during this period, local analytics, which run on the device can help alert the use of abnormal measurements. So it performs basic functionalities, even in the absence of a network connection. And the device is simple. It does not require any special training. Also it does not have a display and requires minimum attention from the wearer, therefore minimizing its impact on the daily lifestyle of the wearer. I should also mention that we identify our device as a low-cost device.

Maria Palombini
Fascinating. We know that there’s a whole market of consumer driven fitness wellness devices that they say they can track your heart rate, your blood pressure, your activity level, your oxygen level. It can do all these things. What makes the MHMB different? Why a physician and/or a patient should trust that this device can be utilized to help their clinical health outcome.

Pramuka Sooriyapatbandige
This is a good question. First of all, we recognize MHMB as a clinical device, rather than a fitness or wellness device. It is a part of an entire remote health monitoring system, unlike most fitness and wellness devices. It is developed focusing on clinical requirements as its primary function. And we intend to release and get the approval of relevant authorities to identify it as a medical device.

And most importantly, MHMB has unlimited measurement capabilities due to their ability to connect add-on devices via the MHMB to a single health monitoring platform, which is not afforded by any other device.

Maria Palombini
I think this is a very important distinction, especially for patients and physicians to know this as well.

Were there any technical or data standards, if applicable, that would have made aspects of developing this concept faster or easier? After going through this process, were there areas where you would say, had we had this, it could really open the doors to innovation and especially in this RPM telehealth space? In your opinion, if there’s still these challenges, what may be one of the best ways to address it?

Pramuka Sooriyapatbandige
Yeah. The standard communication protocol among devices generating medical data would have helped make the process of development more convenient and efficient. Also a common development platform specifically designed for medical and health monitoring purposes would further open doors to the innovation in telehealth space.

An open source development platform would be able to get community contributions to accelerate the process of developing remote health monitoring devices.

Maria Palombini
I’ve heard before that the open source platform is a really important aspect for tech developers.

Pramuka, you’ve given us some really interesting insights. This is a fascinating concept prototype. We definitely are interested to see and to know when you’re going to do your pilots and how the outcome comes. But in the meantime, are there any final thoughts you would like to share with our audience? When it comes to developing technologies, specifically, if you’re going to target underserved patients in developing regions?

Pramuka Sooriyapatbandige
The key is to have the right partners and parties with the objective of taking these technologies to the underserved patients in the developing regions.

This could include the state sector, NGOs, or even commercial organizations. Affordability of the technology or device is another key factor that needs to be considered. This needs to be considered together with a scale of deployment. And I believe that healthcare is a fundamental requirement of all people and telehealth is the key contributor to making healthcare accessible for all. Healthcare systems must be reoriented to address NCDs. Today’s universal health coverage offers a global vision for healthcare systems. Achieving universal global coverage primarily depends on people-centered primary healthcare. All the more important, in the context of rising rates of NCDs affecting high income and low and middle income countries alike. In other words, to be effective, health systems must be rooted in the communities they serve and be able to not just prevent and treat NCDs, but also improve wellbeing and quality of life.

Maria Palombini
I think that’s a very important point that you’ve shared with our audience, and I hope that they embrace it when they’re developing their technologies or trying to deploy a device in those regions. Pramuka, a special thank you for joining me today.

Pramuka Sooriyapatbandige
Thank you very much. It was a wonderful opportunity for me as well, joining this session.

Maria Palombini
For all of you out there. As I mentioned, Pramuka is an undergraduate student in Sri Lanka. If you would like to see his actual pitch video from the IEEE SA Competition or any of the other winners and finalists, you can visit ieeesa.io/telehealthcomp. You’ll see highlights from the competition and everything about that.

Many of the concepts that Pramuka brought up today, we address in various ways throughout the IEEE SA Healthcare and Life Science practice. The mission of the practice is engaging multidisciplinary stakeholders and having them openly collaborate, build consensus, and develop solutions in an open standardized means to support innovation that will enable privacy, security and equitable, sustainable access to quality care for all.

Some of these activities that we have such as incubator programs for WAMIII, Wearables in Medical IOT, Interoperability, Intelligence, and Transforming the Telehealth Paradigm are addressing the many things that we discussed today from accessibility to security, to integration, to interoperability, to scalability, to extensibility.

And these groups are volunteers from all over the world, trying to build frameworks for potential global standards to address these issues. If you would like to learn more about these projects and many of the other practice activities you can visit our website at ieeesa.io/hls.

If you enjoy this podcast, we ask you to share it with your peers, colleagues on your networks. This is the only way we can get these important discussions out into the domain is by you helping us to get the word out. When you are using the podcast and sharing it with your colleagues, please reference #IEEEHLS or tag us on Twitter @IEEESA or on LinkedIn @IEEE Standards Association when sharing this podcast information.

I wanna thank you, the audience, for listening in today. I wish you all to continue to stay safe and well until next time.

Maria Palombini
Hello everyone and welcome to the IEEE SA Re-think Health Podcast Series. I’m your host, Maria Palombini. I am the director and I lead the Healthcare and Life Sciences global practice here at the IEEE SA. This podcast series takes industry stakeholders, technologists, researchers, clinicians, regulators, and more from around the globe to task and we asked them: how can we rethink the approach to health with the responsible use of new technologies and applications that can afford more security, protection, and sustainable, equitable access to quality care for all individuals, you can check out our previous seasons on ieeesa.io/healthpodcast.

As a result of the recent pandemic, the term telehealth has become one of the most frequently used terms and it does not appear to be going away. The reality is the way we see telehealth today will look very different tomorrow. Telehealth is manifesting in many different forms. It’s more than what we commonly see as the doctor/patient exchange on an audio or video platform and it continues to grow with the use of RPM, remote patient monitoring devices. The telehealth experience has changed the patient’s expectation on healthcare services. They’re relating it to more of a concierge-level retail experience: convenient, appropriate, and in-person.

There is a growing RPM space. There are many forecasts about RPM devices- anywhere from US 150 billion by 2028 to estimates that 40% of patients will be utilizing one or two of these devices at one given time. But there’s one thing for certain, regardless if we’re talking telehealth, mobilized health or RPMs, the future of delivering healthcare is not confined to a facility and it will need to be patient-centerED.

Season four of this podcast series, Telehealth’s Quantum Leap into Patient-centered Care, talks to the innovators. These are the winners of the IEEE SA Telehealth Virtual Pitch Competition, the industry leaders, clinicians, and other researchers who are at the forefront of driving innovation with solutions on accessibility, human factor design, flexibility, interoperability, security, and a whole host of other necessary ingredients to migrate healthcare in the form of telehealth to a patient-centered care system.

So a little short disclaimer, before we begin: IEEE does not endorse or financially support any of the products or services discussed by our experts in this series. And with that out of the way is my pleasure to welcome JC Ren, Assistant President of CMI Health, Inc. Hi, JC!

JC Ren
Hi, Maria. Thank you for having me. It’s an honor to be here.

Maria Palombini
Absolutely. So JC and CMI Health are the producers of a device called AsthmaGo. It’s an RPM device. AsthmaGo is a HIPAA-compliant asthma solution that consists of smart home use medical devices, a mobile app, and a physician dashboard. AsthmaGo is a great innovation.It placed third in the IEEE SA Re-think the RPM Virtual Pitch Competition.

So we’re gonna get to the details of the innovation because innovation comes with a solution. But before that, JC, can you tell us a little bit about you? You’re Assistant President at CMI Health. What drives your passion to work at this organization?

JC Ren
So CMI Health is a startup company. We specialize in medical devices, both clinical and for consumers, and we are a relatively small team but we really make a big impact in the industry. And then to all of our customers, it’s really a great industry to be in healthcare as well as we are highly involved in the telehealth and the RPM sector. So it really feels good to know that our products are helping people and improve their life quality, improve their medical outcomes.

It’s a good feeling to read all those customer reviews online, like the Amazon store to learn about how our products improved their life.

Maria Palombini
Absolutely. You know, I’ve interviewed quite a few innovators, especially the entrepreneurs and there seems to always be a human story behind their innovation, their products. When it comes to AsthmaGo, can you share with our audience, what was the driver behind the development of it? Was this shaped by perhaps a co-founders own experience with a friend or family member or maybe something they were exposed to while they were doing undergraduate work at a university? What was the driving motivation of bringing this product to the market?

JC Ren
I first started to learn more about asthma when I was in grad school. I did a small project when I was at Georgia Tech. It was a children’s hospital project with child asthma. That’s how I started to recognize this huge population, how severe it is. But the actual story behind this is one of our partners had a conversation with his golf buddy and his friend has a son with asthma. He’s really worried about his son’s sleep because sometimes there might be an attack or sleep disorder caused by the asthma condition. So he’s really worried that he cannot fall asleep. He has to get up and see his son so he really wanted something to monitor closely every night. During the sleep you wanna know his son is okay so both him and his wife feel safe.

Maria Palombini
Unfortunately, we hear more and more about children suffering from asthma for many different reasons. And of course, I imagine that brings a lot of stress to parents everywhere in the world.

So to our audience, now we’re gonna get to the core of our interview, the innovation. Just food for thought: RPM, remote patient monitoring, is more than just a device and a telemetric way of transporting information. It has to be a care system that is built around not only the patient’s therapeutic condition, but also their social and other home determinants. And JC just started to allude to an exact use case when it comes to children in the home and fear of quality of life and worrying. Your child is not breathing right. And all these kinds of other issues. We know that according to the World Health Organization, asthma affects an estimated 262 million people.

And that was in 2019 and caused 461,000 deaths. So this is not something that we can just push to the side, right? It is a non-communicable disease that affects both children and adults equally. So JC, how does AsthmaGo support this very large and diverse population of patients?

JC Ren
Asthma is like a typical chronic disease, so being like a chronic patient. So it’s more like a lifestyle. Everything in your life is being influenced by the conditions and there’s such a huge population. So we keep in mind that the key concept is we want to help the patient to manage asthma at home. That’s where they spend most of the time- at home.

But at the same time, they have to fight this condition. If it’s managed properly, it can minimize the impact. So we are empowering the patient and putting them in the driver’s seat of asthma management. So to accomplish that, we use this simple and very user-friendly mobile app. Because, everyone has a smartphone and that’s becoming part of everyone’s lifestyle.

So we just use the mobile app. So making it like the morning routine or something that is at their disposable anytime, anywhere. And then we also have those over the counter devices that’s really affordable and easy to use and to care that way they can do the test anywhere. And then know their vital readings so they can know early, if anything goes wrong, if they need to use a medication, they need to see the doctor by doing all that very conveniently and right out of your pocket solutions.

We can prevent a lot of the exacerbation and ER visits from happening, greatly improve their quality of life, and reduce the cost.

Maria Palombini
Absolutely. I think that you’re right. It’s a really good way of saying that asthma is a chronic condition and it’s just not gonna go away with a simple antibiotic. It’s living with a lifetime condition.

So you mentioned this a little bit before in your intro, when you were doing your studies, you were exposed to people with asthma, children. Can you share with our audience a little bit about the types of research, the modeling, and the years of work and time that went into developing this product? And in that research, what would you say was the most interesting thing that came out through this research and development phase of this product?

JC Ren
So let me start from our company, how we get started. One of the founders, he has 30 years of experience in the medical device industry, particularly in the respiratory area, like CPA machines, things like that.

We started in the oximetry business, like oxygen monitoring before we developed this product. We do a lot of sleep apnea monitoring because the patient’s oxygen will fall rapidly during sleep because their breathing stops. So the solution can develop from there. We have some manufacturing partners that are specialized in spirometry devices and they try to make something that’s very affordable and easy to use at home because we found it’s really difficult for the patient to manage this condition at home. Most people rely on doctor’s visits maybe once a month or so and that’s clearly not enough. So we have developed this spiraling device, that over counter spirometry, and we developed it, using a different technology that’s a pressure sensor different from the traditional turbine, which is derived from a hospital grade desktop unit. And at the same time, it’s easy to use and to maintain lower cost than the common units in the market.

So that’s how we developed one of the key devices to bridge the gap and appeal to a huge population without compromise, like accuracy or reliability. That’s how it starts and we also combine our specialty, right? Oximetry, so the patient or the child can be monitored continuously throughout the night, lowering the risk or the parents worry that something may happen during the night.

Maria Palombini
Absolutely. This is a nice segue to my next question. So we know that asthma is a common chronic disease among children, unfortunately. And like you said, parents are worried, right? They’re worried about when they’re sleeping and they’re getting enough oxygen. Obviously there’s a lot of concern there, but we also know that children are traditionally not the best at patient adherence- they’re children. They’re like, I don’t wanna wear this thing. I don’t wanna touch this thing. Their mind is in a million other places. So how do you find children using this product? Do you find that they’re compliant, that they’re using it correctly? They’re using it at the specified times they need to use it? Do you find that parents are not complaining? Oh, my child doesn’t like to use this thing. WHat are you finding in that specific area of opportunity and working with children?

JC Ren
Yeah. So we actually have this in mind during the whole kind of development process. So for example, our spiral link spirometry device has a really nice and narrow mouthpiece opening.

So that’s gonna be easier for the children to blow into it. And also for the oxygen monitor. Our oxide watch, we have a kids version. So for adults, they have a big finger sensor, but we have those little fingers with nice colors, like a bright blue color or pink color for the kids and with a tiny little finger sensor.

So our product has age groups and also for the children. We’re also working with some groups, trying to set up studies for children, to see their compliance and to see the best way to improve adherence. And then the outcome. There are many ways to get there, like things that appeal to children, like better UI design of the app, or even like the daily routine testing, more fun things like those. We don’t have the final product yet, but we are in the kind of active process of developing.

Maria Palombini
There are so many devices we talked about, they’re coming into the market in many therapeutic areas, many different applications and so on, but we’re seeing sometimes this one hit, I call it a one hit wonder approach, right?

We’ve developed this device. We put it on the market. It’s a monitoring device. It can connect to an app. It can collect and transmit data. And then we have to wait. The next version comes out for it to do the next thing. And you start to talk about, this is the interesting point of your particular innovation.

It’s scalable and extensible. And I wanna get your point of view when you were developing this RPM device, why did you find it important to have that in the product design and how did you feel that would best serve the patients that you’re trying to help?

JC Ren
Yeah, I think the key concept and the thing we always think about is the patient. So our goal is driving the patient, motivating the patient, making everything accessible and then convenient. So they have everything they need and they can do it very easily. And then, we don’t focus on one specific device. We think about it as a whole concept, the whole idea, a solution to help people with asthma.

So one thing we keep adding different devices. So it’s like different tools for the patients at home, at their disposal. For example, like a brace trainer because managing the disease testing is one thing the recovering/training exercise is another important part of this condition like chronic disease and also like inhaler, counter.

So many of these will play a critical part in the patient’s life. So we can try to make their life easier, not only just focusing on one device. We’re focusing on the patient and also with the API and SD case of our devices, all these great devices that we have are not only available to us. It’s literally available to everybody. So say like another company, like RPM or telehealth group, they have a specific need. Whether it be for seniors, for children and they have some other great solutions and our device is available to a company like this so they can make these great user friendly devices as part of their solution.

We are also helping the patients like the end user and also the industry, so many other companies. There’s a lot of different solutions and products available for different scenarios.

Maria Palombini
When you think of the patients that can benefit from the technology CMI has developed, how do you see it being patient centered from a point of view of accessibility, adaptability, flexibility, or those areas of interest? What are some of the outcomes you have seen with the ability of doctors to have access to the real time data coming from these devices to enhance the patients’ care?

JC Ren
If you think about the patient care, especially for this chronic disease, actually the patient can spend 90% of their time with themselves at home or with family, not with a doctor. So they are responsible for the most part, for their own care. The patients are actually the best caregiver for themselves. If they’re equipped with the correct tools, mindset, and the knowledge. We want to bridge this gap of traditional patient care. Traditionally it’s like taking photos. Patients go to doctors once at a time, but the doctor only sees photos of the patient. They don’t know what happens at home. Maybe there’s an asthma attack. There’s some trigger or some feeling the patient doesn’t even know themselves. They cannot describe it or they forget when they’re at the doctors. With telehealth and RPM solutions, like our AsthmaGo, it’s more like taking a movie that’s continuous. It records everything that happens all the time. And the doctor now has access to this movie. So the trend is very clear. They will know a lot better about the patient. Maybe the medication is not bad or maybe some other factors like weather or activity influence the condition. So it’s a lot easier for the doctor and the patient to improve the outcome, because the patient is responsible for their own care. So we try to give them the best they can have at home so they can take charge. That’s what we say, that we put them in the driver’s seat. And by doing that, we are actually promoting early prediction and early intervention. So we believe that’s the best way for all this type of chronic disease, because there’s no severe tax ER visits that will result in better quality of life and better outcome and lower cost.

Maria Palombini
Absolutely. I agree. I mean, I think that there’s so much here, you know, the opportunity for patients to definitely take control of their condition, you know, using great tools, such as these and others out there.

I talk to many different tech entrepreneurs, a very exciting opportunity to hear from them. And they always mention to me, in the development phase or in the research phase, they’re like, wow. Had this technical standard or data standard been in place, it would’ve been a huge help or policy sometimes be written in such a way it would’ve made things a lot easier.

So my question to you is after going through this development process and going through this whole experience, what are some of the things that you guys experienced? If we had this, it would’ve made it easier. And how do you see that potentially opening the doors to innovation in this RPM space? If that challenge still exists, how do you guys think maybe there’s a better way to address it?

JC Ren
This is a big topic. Maybe I’ll just talk about one part of it. That’s the connectivity. That’s the fundamental basis of telehealth. We want the doctors or the nurse caregiver to be able to access patient data, be able to communicate and provide care remotely.

So connectivity is key. The IOT device that’s equipped with Bluetooth technology, wifi cellular. That’s really important. And throughout our development process or the years in business, we also find out the cellular starts to play a more important role and then become convenient compared with Bluetooth and wifi. Because sometimes you’re dealing with little kids or seniors. Sometimes we have to skip the mobile connection due to personal reasons. But cellular connectivity can really close somefinal mileage. For example for seniors, for like remote areas, things like that, with no wifi.

And we are actually moving toward a lot of cellular enabled devices and then trying to keep all of our patient customers connected wherever they are.

Maria Palombini
I think that’s a really good point. I think keeping patients connected and we hear connected healthcare everywhere, keeping them really connected means more than just connecting them to their device and that’s it. It’s the whole experience across the continuum of care.

So JC, I think you’ve given us some really interesting thoughts. I mean, obviously you guys are tackling a significant global chronic condition through the use of this. Are there any final thoughts you would like to share with our audience as technologists who’re looking to develop a device in the RPM space to even go into some support of chronic conditions or just this idea of design mindset, patient-centered care. What advice or thoughts would you share with our audience on that?

JC Ren
Maybe just some quick points for both patients and for doctors, you’ll find a lot of great innovations and great convenience.

If we can try new things, try new technologies. I know it’s typical in the healthcare industry, because we have many hospitals and doctors. They prefer more traditional ways of doing things. We’re gradually moving toward the technology trend, but we are still years behind what actually the technology develops, but we are heading toward the right direction, especially as we are in the COVID situation in the future post COVID.

And we have a lot of these great regulations, reimbursement, everybody starts using and accepting the idea of telemedicine, telehealth using their mobile and doing things they are not able to do before at home. And suddenly we’ll find out, oh, that really makes our life easier.So, yeah that’s what I want to add.

Maria Palombini
Absolutely. So for all of you out there, trying to get into the telemedicine space, you have to think about patients from multiple different ways, just not their clinical therapeutic condition. And that’s a really important point. So JC thank you for joining me today. It’s been an absolute pleasure, hearing more about AsthmaGo.

JC Ren
Thank you, Maria, for having me.

Maria Palombini
If you wanna learn a little bit more about AsthmaGo and overall CMI Health, you can visit cmihealth-inc.com. If you like to see the finalist pitch videos from the Rethink the Machine Virtual Pitch Competition, they’re available on the event website at ieeesa.io/telehealthcomp.

Many of the concepts in our conversation with JC today are addressed in various activities throughout the healthcare and life science practice here at the IEEE SA. The mission of the practice is engaging multidisciplinary stakeholders and having them openly collaborate, build consensus, and develop solutions in an open standardized means to support innovation that will enable privacy, security and equitable, sustainable access to quality care for all.

There’s so many different activities here, such as WAMIII, the wearables of medical IOT, interoperability and intelligence global incubator program, the transforming the telehealth paradigm industry connections program and all of these different areas of accessibility, human factor design, seamless connectivity are all being addressed by our volunteers.

So if you’re interested and you wanna learn more about these projects or all the other additional projects, which I didn’t even get a chance to mention, you can visit the practice website at ieeesa.io/hls.

If you enjoyed this podcast, we ask you to share it with your peers, your colleagues on your networks. This is the only way we can get these important discussions out into the domain is by you helping us to get the word out. You can use #IEEEHLS or tag us on Twitter at @ieeesa or on LinkedIn at IEEE Standards Association when sharing this podcast.

Special thank you to the audience for listening and being here with us today. Continue to stay safe and well until next time.

Maria Palombini
Hello, everyone! Welcome to the IEEE SA Rethink Health Podcast Series. I’m your host, Maria Palombini and I’m the Director of the IEEE SA Healthcare and Life Sciences Practice. This podcast takes industry stakeholders, technologists, researchers, clinicians, regulators, and others from around the globe to task: how can we rethink the approach to healthcare with the responsible use of new technologies and applications that can afford more security, protection, and sustainable, equitable access to quality care for all individuals. This is an ambitious task, but this is one that we are definitely committed to.

We’re going into our fourth season of the Rethink Health Podcast, and you can look at our other seasons at ieeesa.io/healthpodcast.

So we’re getting into the question of telehealth. As a result of the recent pandemic, the term telehealth has become one of those most frequently used and it does not appear to be going away soon. The reality is that we see telehealth today and it’ll look very different tomorrow. It’s manifesting in many different forms. And it’s not commonly, as we know it, just the doctor and patient experience in some sort of audio/video platform. It has become so much more than that. And I’m sure you’ve heard the term remote patient monitoring or RPMs.

The telehealth experience has changed our expectations as patients on what we can expect on healthcare services. By that I mean, we kind of see it almost like a retail experience, right? We want VIP consierge service, we want amenities, and we want convenience.

And then there’s this growing RPM space. These wearables, these bio sensors in, on, or around the human body monitoring us for some sort of therapeutic condition. There’s so many different forecasts when it comes to the growth of RPM, it could be anywhere from U.S. 150 billion dollars by 2028 and to the idea that a patient might be wearing one or more on their body at any given time.

Here’s what we know, regardless whether we call it telehealth, RPM, mobile health, the future of delivering healthcare is no longer just confined to a facility and it will need to be patient-centered. So, season four. We’re calling it Telehealth Quantum Leap into the Patient-Centered Care.

And this gets to the innovators and the innovators we’re talking to are actually the winners of the IEEE SA Telehealth Virtual Pitch Competition. Plus we’ll talk to industry leaders, clinicians and other researchers who are at the forefront of driving innovation with solutions, looking at accessibility, human factor design, flexibility, interoperability, security, inclusivity, and all the other necessary ingredients to migrate RPM into a patient-centered care system.

So before we begin– a short disclaimer: any of our guests on our podcast series, IEEE does not endorse their products, does not financially support them. We just bring them here for their expertise. And without further ado, I’d like to welcome Josh Rabinowitz Co-founder and CEO, of Articulate Labs. Welcome, Josh!

Josh Rabinowitz
Thank you for having me!

Maria Palombini
Articulate Labs garnered the second place position in the IEEE SA Rethink the RPM Machine Virtual Pitch Competition and their work was on wearable devices for remote direct physical therapy application and monitoring. And we’re gonna get to the core of this in just a second, but Articulate Labs has also placed favorably in other industry competitions, including winning the 12th Annual IOT Wearables Technology Innovation Award, plus a host of others.

So Josh, before we get to the core of the work you do, we’d like to humanize the experience for our audience. So can you tell us a little bit about you? You’re a co-founder of articulate labs, really? What drives your passion in your work and how did you get here?

Josh Rabinowitz
I’ll start by answering the second question first. We got into this quite literally by accident. My co-founder survived a near fatal motorcycle accident some years ago that forced the amputation of his right leg. One of the indirect outcomes of that is that he developed osteoarthritis in the knee of the fully intact leg, the left leg, as he was relearning to walk.

He was advised by his orthopedic surgeon to delay surgery and to exhaust all the conservative options available to him. He found physical therapy to be the most effective means of mitigating the pain and dysfunction that existed in his knee, but he wasn’t able to make it to all his physical therapy sessions.

It was not a lack of desire. It was an issue of time. He had work commitments. He had family commitments, the physical therapy clinic was a half hour drive each way from where he lived. It was a really difficult thing for him to be able to budget time for self care.

He’s a control systems and an embedded design engineer. He’s using a therapy at physical therapy called neuromuscular electrical stimulation. He’s like having these electrical pulses run through the quadrants of muscles around that knee to assist with the restrengthening, the retraining process.

But it’s operating on a pre-programmed sequence and he’s wondering why on earth am I driving a half hour to basically move my leg in time with this thing? Why am I following this technology? Why is this technology not following me? Why is it not adapting to me? It’s kind of what started his development process and figuring out can he make this therapy a little bit more intelligent, a little bit more adaptive.

I got involved as someone who has no engineering or medical background. Just one day randomly looking up knee osteoarthritis and discovering, oh, there’s actually 14 million in the us impacted by this. Not to mention the tens of millions of others around the world with the same condition, not to mention hundreds of millions, around the world, dealing with all kinds of other muscular skeletal conditions.

And we found out, one, this is not a unique situation. We were both operating under the impression this was something that only impacted amputees and two, a lot of other people have the exact same issues of time, distance, reimbursement of existing commitments, all making access to physical therapy very difficult. Realizing those things made us wonder whether the thing that you know was kind of being developed almost as a hobby, as a side project is something that we might wanna really consider sharing with others.

Maria Palombini
It’s interesting that you brought up the unfortunate accident with your partner. As I talk to many more startups, I always find that there is a personal passion behind, especially in the healthcare life sciences sector, why they decided to go with this type of RPM product or that kind of thing. And that’s really where the success is. It’s that passion that fuels that commitment. So this is not atypical from what I’ve heard from other co-founders that I’ve talked to.

So you kind of got into a little bit about what Articulate Labs does. What exactly in your words is the vision of bringing this type of innovative approach to physical rehabilitation, to the healthcare domain?

I’ve been through, like other people, physical rehab for different sort of issues and I agree, going to the facility, getting the appointments, waiting for your therapist sometimes they run late, sometimes they don’t, or you can’t get there. There’s like a whole host of issues that you kind of sometimes feel like it’s almost like a job, right?

Josh Rabinowitz
The mission that’s going to resonate with the greatest population, I think, is going to be convenience. When we think about the act of strengthening the muscle that talking about, well, how do we make this easier? How do we make this more convenient? How do we blend this more into the user’s lifestyle? It is somewhat antithetical so much of the ethos that goes into physical fitness.

That part is difficult, but so much of the issues that we run into with regards to access, is a population of people that cannot budget time for self-care, don’t feel like they can, or don’t necessarily know how to start. And being able to effectively augment movement that they’re going through every day with a proven therapy such that steps walking up and downstairs or getting out of a car, can become strength-building repetitions outside of that physical therapy clinic or gym.

You know, now there’s really an opportunity to help improve access, improve people’s ability to care for themselves on a broader, deeper, longer term. My mission would be in finding ways to talk about the process of strengthening rehabilitation of caring for the body as something that’s for everybody to get outside of the stereotypes or concepts that if you’re not looking like someone who’s showing up at one of the Marvel action movies, then why are you even going to the gym? What’s the point? I think there’s a real need to talk about maintaining your body, because this is your primary vehicle. This is your means to functional independence, to in many cases, to goal achievement, whether it’s travel or caring for loved ones or doing things that you enjoy, you’re having the strength to function the way you want to, not the strength to measure up to someone else’s standards.

Maria Palombini
I think the focus on self care comes in many different forms and I think it is important. Now we’re gonna get to the core of our interview, which is about the innovation. So I imagine your team really got into some heavy research. You probably looked at different models and there’s probably years of work and R and D that went into developing this project.

Maybe could share a little bit of insight with us on what that experience was like and what exactly. But more importantly, I’m really interested to hear what would you consider the most astonishing piece of information that came through in that R and D phase of research for the product?

Josh Rabinowitz
I think the main astonishing outcome and the thing that we’ve had the hardest time explaining to others is that there is no average when it comes to figuring out where people need to be or where they want to be. Especially when you’re talking about people who’ve been coping with and in our case, a knee condition, but really anything on the kinetic chain.

So anywhere between lower back and ankle. When you have an injury in one of these places, you have a tendency to develop compensatory movements as a means to reduce pain in that area. So you might think about the folks we’ve seen in our studies, people who are looking to avoid putting weight on their knee or to avoid extending their knee will develop all kinds of strategies to not use that joint.

Whether they’ll pivot on their other leg, they’ll actually hitch the entire half of their body with the affected knee, they will drag the leg with the affected knee, somewhat behind them. All these things are unique to each individual and the way that these things worsen over time is unique as well.

So every happy gait is the same. Every unhappy gait is unhappy in its own way. Attempting to impose a pre-programmed gait sequence on these individuals and forcing them into a template we found, first of all, it was very difficult to actually trigger the right muscles at the right times.

Going with this average, looking more into relationship between specific quadricep bands and the function of the knee joint during movement, you actually run the risk of exacerbating the condition. If you are strengthening without regard to joint laxity or joint alignment, that really created a need to kind of scrap any sort of template based stimulation, and really start with a form of a model of the joint running on the device that is learning from and effectively distilling movements down into just sets of force vectors as a function of femur and tibia position, motion, acceleration, et cetera. And we really try to just meet the patient where they are. Working with physical therapists to calibrate the device to that user’s gait and to determine which muscles we want to trigger at what times of gait, which movements are problematic, that should be addressed by triggering muscle contraction.

That’s our way to personalize treatment. Something that you said at the beginning that really stuck with me: patient centered care. That’s our opportunity to make truly patient centered care versus imposing our own biases as it were about how a person that we’ve never met should walk.

Maria Palombini
Absolutely. We see this sort of challenge actually transcend the entire healthcare domain. It’s putting patients in a box. I think it’s really important the way you guys got to this level of, I don’t wanna say personalization, but maybe there’s an element of precision on how to use the technology to best support helping these patients.

I imagine our audience might be sitting there and saying, wait a minute, does this mean that we don’t need physical therapists anymore? We know that KneeStim, which is one of your products, is not designed to remove the physical therapist out of the process. But I think the real opportunity is in when you guys describe it is intelligent.

So from your point of view, how can KneeStim really enhance the effectiveness of a physical therapist in working with their patients? I imagine the data capture in the tool can access and utilize. Maybe you could talk a little bit from that point of view.

Josh Rabinowitz
Sure. The first thing we’ve said when we’re talking with physical therapists who might have a little bit of that skepticism first, there’s a lot in the electrical stimulation space and two, there’s been a lot of startups that have marched into clinicians’ offices, kicked in the door saying we’re gonna drag you, kicking and screaming into the 21st century without really paying any attention to their wants and needs. So first I wanna say right up front, we get skepticism and don’t begrudge anyone for it.

The way we manage that is by saying, we’re not looking at this as a means to replace physical therapy. We’re basically taking some of the most mindless parts of your work, which is either setting someone up for electrical stimulation or guiding someone through strength-building repetitions.

And we’re trying to automate that and allow at least some of that work to occur outside of the clinic. Then you can talk about this as a means of improving workflow, saving little bits of time with each patient, as a means to increase throughput ways to maintain a level of communication with the patient that’s not present.

That’s a huge issue. You touched on earlier with regards to your physical rehabilitation experience: 70% of the population that’s prescribed physical therapy don’t show up for all their sessions and are not compliant with their home-based regimens. That represents a financial impact to the physical therapist beyond the altruistic drive to do right by their patients.

When you have a patient that’s not showing up, you’re not earning money. You have a patient that cancels or no-shows, now you’ve got the opportunity cost of having scheduled someone that isn’t gonna pay you and delayed someone that would. With a new remote patient and remote therapeutic monitoring based reimbursement codes, there’s now opportunity for the physical therapist to be able to have some level of visibility on user activity that we’ll be able to measure and report things like steps walked, stride speed, knee range of motion. We’d love to be able to provide a granular level of information to make it clear also what’s happening on stair ascent and descent, or sitting up from a chair, other metrics to make it clear whether someone is making progress in their physical rehabilitation, or if they are at risk of back sliding. By having that data collection and analysis process be reimbursable, now there’s an opportunity for the physical therapist or overseeing clinician to be able to earn some revenue on the patients that they’re not getting to see.

Physical therapists have been really deeply impacted by COVID, in general, just by the increasing difficulty with getting people in the door with decreasing reimbursement for services provided. We see this as a way to be able to provide care and maintain communication while still helping maintain the physical therapist’s bottom line.

Maria Palombini
Yeah, I think for physical therapists there’s a lot of opportunity here with access to data, for sure.

I hear misconceptions around connected wearables and from doctors sometimes they’re like, I don’t know if I wanna use this thing. They’ve got some preconceived notions about them and patients they really know about wearables from the point of commercial fitness trackers, Fitbits, you know, your Apple watches and so forth. What have you seen as the biggest misconception when it comes to these types of applications for connected wearables?

Josh Rabinowitz
Really the biggest misconception I see is really less on the patient or provider side, it’s really in the service provider side. There are a lot of companies in the wearable space and the vast majority of them don’t have to be FDA regulated. They don’t have to really be deeply concerned about security. If they are they’re concerned at a really thin surface level, they don’t have to be concerned about encryption. They only pay a small amount of attention to HIPAA. The misconception I’ve run into that’s been the most difficult to deal with is actually finding vendors to work with on some of this development work that are able to meet the standards for security, for privacy, that are coming, not the ones that are here.

We see Europe as an example of where we think might go over here or at the very least it’s a market that we want to enter in the future and we will need to be able to meet standards for privacy. The number of companies we’ve talked with, who claim to do this work and then have really no idea of anything that’s going on, that’s gonna be necessary for a medical device versus a “wearable” or versus a fitness application. And assuming that we’ve done one, so we can do them all. That’s dangerous. We’ve had to push ourselves to learn what these standards are to really understand them. And then to really grill any potential partner that we meet with on how they intend to meet these standards. And more often than not, we’re kind of met with blank stares.

So I think anyone else who’s in this space, or who’s looking to get into this space I think it’s critical to build up a base level of knowledge of security, privacy encryption, and so forth. I don’t know enough to be able to actually affect anything, but I know enough to be able to challenge and to oversee anyone who’s gonna be doing this work on our behalf.

Maria Palombini
That’s really important. You wanna make sure you have the right partners because overall it’s a brand representation and you have to have it be aligned. Very important point.

You started to scratch the surface of this question a little bit when you first introduced Articulate Labs, but you know, the theme of this podcast is patient-centered. The competition was heavily focused on this idea of transforming RPM into patient-centered system. How do you see your technology being patient-centered from a point, whether it’s from accessibility, visibility, inclusivity, or even just the human factor design? Do you see that there’s a population of patients that you all can better reach and serve with this that maybe they were not accessible before, or they were just resistant to the idea of physical therapy? How do you think you guys are really meeting that idea of patient-centered?

Josh Rabinowitz
I think that element of starting with a very basic concept of how that knee joint is functioning and building the model from the ground up with the user’s own kinematics, with the data coming off of the IMUs, being placed on their legs makes sure that the model that develops is exactly what the patient is what they’re doing. That there’s no concept whether at age, gender, physical ability, that it doesn’t create a conception about what someone does or does not need. It is putting a lot of control in the hands of the overseeing clinician to be able to tailor the stimulation timing and location, and also be able to adjust sensitivity, bias stimulation to one muscle over another, as a means to really make sure that this is hitting the right muscles at the right times at gait, or is contracting the right muscles in time with problematic movements as a way to ideally make those movements a bit easier for the patient.

I think one real interesting possibility that we have here for inclusivity and for access is the ability to provide physical medicine care to people in remote or austere conditions. This is certainly something that is already capable with a lot of the remote or virtual physical therapy options out there and we don’t view ourselves as placing any such service like that. What we see with this device is the ability to really augment and make use of someone’s existing movement. So the people who are in these conditions, they may be like an hour away from a physical therapist. They may be doing work that makes it really difficult for them to set aside even 15 minutes to follow along with a guided physical therapy session. With these populations, there’s an opportunity to use their actions, use their movements and get the same strength-building exercise in without requiring the patient to set aside additional concentration, additional time to change clothing, so and so forth. This is something that ideally will blend in seamlessly into the user’s life and we’re passionate about the possibility of having care, not just augment life, but having it be in support of life. The work that you’re putting in while wearing this device, the strength and reeducation of that muscle that you’re going through is gonna be exactly in line with the things that you’re already doing, the things that you want to do, or the things that you need to do.

I think that’s really intriguing to us and represents a way to integrate physical medicine into people’s lives that hasn’t really been approached previously.

Maria Palombini
I think that’s fascinating. I think this goes a lot into human factor design, the adaptability, the feasibility, these are all really important elements when we’re talking about patients and their physical ailment or condition. I think that’s really an important place and a good place to be in getting your product advocated for. You want patients to say this was the best thing that worked for me. So I think you all are on the right track for sure.

When I talk to a lot of tech startups, they say to me, oh, I wish we had a technical standard for this. Or I wish this was already in place because this would’ve made this part of our work a bit easier. So, do you think there was potentially any technical standards, if any, that would’ve been appropriate or data standard that would made any aspect of developing this product faster, more efficient, easier?

And as you went through the process, did you identify any other areas that you said, wow, this would’ve really opened the doors to innovation in our space, in the RPM space, in the wearable space. And what do you think might be the best way to address it or to go about it?

Josh Rabinowitz
I’ll hit the second question first and say any standard that’s out there, it’s nice to have as a guidepost, but for our purposes, it’s got to be either harmonized or at least asynchrony with the FDA’s doing. If we don’t have the FDA on our side, we’re not selling anything to anyone in this country, at least. And furthermore, the FDA tends to be a gold standard adopted by many other countries that have distributors reach out and be interested in buying our devices.

So getting FDA clearance is not just the gateway to the rest of the U.S. It’s the gateway to get into much of the rest of the world. In that regard, I’d say for us having anything around FDA documentation or standards around use of real time operating systems within a medical device, there’s not a lot of that out there that I’m aware of at the moment.

I could be completely wrong here. But we’re only aware of a small handful of medical specific operating systems, none of which wound up being applicable for what we’re trying to do, because we’re trying to achieve real time application of therapy that does not line up with a lot of existing devices in the medical space that tend to be set up boxes with sets of leads or electrodes or some form of input or output that basically relies on the person remaining stationary. Having more wearable technology means having more firmware that’s operating in a really dangerous space. We’re fortunate standards wise that nothing that we’re doing here really has high risk of ending someone’s life.

But that is not the case if you’re developing a pacemaker or if you’re developing a next generation joint implant. So having frameworks in place for the next realm of operating systems and really having frameworks in place for technologies that are going to be semi-autonomous. And understanding what are the bright lines past, which autonomy cannot be allowed.

There has to be fail safes in place to stop AI from deviating in such a way that it leads to a deleterious outcome for the patient or a potentially fatal one. I think those are the places where right now we don’t see a lot of definition. And we have a path that we see to market based on previously clear devices.

But we also recognize that we’re still looking at bringing something that is gonna be relatively unique to the medical device space. So we’re hoping that us punching through will be an opportunity to broaden the discussion about software and firmware development as we get more into wearables as we get more into decentralized care.

I think inevitably need to start putting more faith or energy or authority in technologies that are gonna be assisting people on medical conditions when a clinician’s not physically present.

Maria Palombini
Absolutely, I think the FDA and EMA depending where you are in the world cannot lose sight. It’s really important to be compliant and under their guise when it comes to anything that you’re gonna use in a medical application.

Josh, you’ve given us so many great insights, especially with the application and what you guys are trying to treat. Are there any final thoughts you would like to share with the audience when you say I’m gonna develop technologies under the context of patient-centered care?

Josh Rabinowitz
We’re actually hosting some students right now in biomedical engineering and one of the most disturbing things that come outta that situation is finding out that they’re looking at adapting, what we’re doing to the knee and fitting it onto someone’s hip.

And they wanted to actually physically prototype the dose, not even adding in electronics, not adding in simulation. Just trying to understand how to get a device to fit around a leg and the professor, as we understand it, basically kinda came screaming into the room to knock the materials outta their hands and said, no, you will only simulate this.

You will never build a single item until run this through whatever simulation package you want. And that makes a lot of sense for like an implant. Trial and error is not a viable there. For something like this, if you’re looking at developing a wearable, then yeah. By all means, try it on yourself.

That’s so much of what we had to do in terms of figuring out a form factor, figuring out how to address corner cases that would exist during gaits such as, you know, stamping your foot or sneezing or stepping off of a curb. Those are only things that we are able to figure out solutions to because we are trying this on ourselves.

For one thing, if you’re not willing to try this on yourself, or if you’re nervous or embarrassed or think about the clinician or the patient that you’re gonna be talking to. How on earth are you gonna convince them if you can’t even convince yourself?

The other thing, going back to the concept of patient-centered care and to some extent, the idea of unconscious bias, we didn’t know what this device needed to do until we had the opportunity to approach the subject with a wide variety of people– different age, gender, size, gait abnormality– all had unique points of view about what they needed out of the device that we would not have figured out and this being founded by two men, a lot of conditions or a lot of situations with women with regards to leg shape– the aesthetics, to some extent, the act of shaving your legs, opening up pores, across which current bridge the gap and create pain.

Those are things we had to learn about from others in the course of controlled experimentation, to make sure that we are developing something that other people would actually want, not just what we would want. So much of this, I think really comes down to experimentation, obviously with full respect and understanding of what the standards are imposed by FDA, understanding institutional review board, how they operate such that when you set up this experiment, you’re doing so in a way that’s ethical and safe.

But you’ve got to be able to try this out and discover problems that you would not have come across otherwise. You’re not gonna simulate your way out of it. You’re not gonna guess your way out of it. The best way is just have someone else break your stuff and tell you what’s wrong.

Maria Palombini
That’s an interesting point. I think here, if I may, maybe the moral of this part of the story is that one size does not fit all. It’s really important because you tend to think, oh, it works here. Let’s just apply. Make a little change and put it here. So really glad you drove that home, Josh.

Josh, I wanna thank you for joining me today and sharing this great insight, the innovation, and the dedication to precision therapeutic that you’re building for this pool of patients. Thank you for being here and sharing that with us.

Josh Rabinowitz
Thank you again for having me. I really appreciate the opportunity.

Maria Palombini
If all of you out there wanna learn more about Articulate Labs, you can visit articulatelabs.tech.

Many of the concepts that Josh and I discussed today are addressed in various activities here at the IEEE SA Healthcare Life Science Practice.

The practice really engages industry stakeholders, such as Josh, around the world to come together and bring these discussions forward. As you notice, Josh already started to allude to that there are some concerns and challenges we have to look at when it comes to autonomous systems and the use of AI. They’re great technologies, but we need some more safeguards there. How can we do this in such a way that we’re gonna really open the doors to innovation and not be a barrier and kind of get this elephant out of the room?

So if you’re interested in getting involved in any of our activities, we have WAMIII (Wearables in Medical IOT, Interoperability Intelligence,) and Transforming the Telehealth Paradigm, which are Industry Connections Programs and they’re really getting to the core of all these connected technologies being used in a remote environment to address patient’s needs with privacy security, the flexibility, the human factor design– they’re attacking all these issues. If you wanna find out more about the work of the practice and all these individual programs I mentioned, please visit us at ieeesa.io/hls.

If you enjoyed this podcast, if you enjoyed the conversation or found something useful in this tidbit of insights that were shared with you today, we ask you to share it with your peers, your colleagues, or on your networks.

This is the only way that we can get these important information out into the domain to talk about the important work our volunteers are doing in the Healthcare Life Science Practice. So please use hashtag IEEE HLS or tag us on Twitter at IEEE SA or on LinkedIn, the IEEE Standards Association when sharing this podcast.

I wanna thank all of you for joining us today and listening in, continue to stay well and until next time!

Maria Palombini
Hello, everyone and welcome to season three of the IEEE SA Re-think Health Podcast Series. I’m your host, Maria Palombini and I am the Director of the Healthcare and Life Sciences Global Practice. So our practice is a platform for multidisciplinary stakeholders from around the globe to collaborate, explore, and develop solutions that will drive responsible adoption of new technologies and applications leading to more security protection and sustainable, equitable access to quality of care for all individuals.

Yes, a very ambitious goal, but a very necessary goal. The Re-think Health Podcast Series brings awareness to all of these concepts and a balanced understanding in the use of all new technologies and tools and applications where we may need more policy or standards to drive this responsible, trusted, and validated adoption to enable better health for all. All of our seasons and our podcasts are available on Podbean, iTunes, and other podcast providers.

Season three is titled AI for Good Medicine. And it’s not just about AI. We’re looking at machine learning, artificial intelligence, deep learning technologies, and really looking at how these multidisciplinary experts from around the globe can provide insight as to how do we envision this AI/ML delivering good medicine for all?

The reality is we all want good medicine, but at what price and price really here means in terms of trust and validation in its use. As healthcare industry stakeholders, we’re not just looking for the next frontier of medicine if it’s not pragmatic, responsible and can be equitably valuable to all.

And so we go deep with the technologists in this season, we talk to the clinicians and the researchers and the ethicists and the regulators, and really trying to understand what can be real and trusted impact on using these technologies for improving outcomes for patients everywhere. The reality is can this really help us cut through this health data swamp and deliver better outcomes?

And with that, I like to welcome Sumit Nagpal to our discussion for the true potential of AI in healthcare, helping marginalized populations or helping those, even in the form of the elderly. All these populations that, yeah, they may have access, but exactly how do we reach them in the right way?

Sumit is a serial entrepreneur with a focus on digital health innovation at scale. He has co-founded and grown five companies over the past two decades and has tackled progressively bolder challenges facing our healthcare economies. All his work features common themes: big, bold ideas to help us imagine a better world, incredibly complex processes into simple, approachable and engaging user experiences, implementation models that blend big innovations into the fabric of our daily life. He has honed since the time he has worked with Steve Jobs and NEXT in the early 1990s.

Sumit, welcome to the Re-think Health Podcast Series.

Sumit Nagpal
Thank you so much for having me.

Maria Palombini
I think you have an exciting background, just reading this very short descriptive paragraph. You’re a serial digital health entrepreneur. It’s an opportunity to work with some great tech gurus and renowned companies. Can you share with us what has been the greatest reward and maybe some of the greatest challenges that you’ve confronted?

Sumit Nagpal
Awesome way to start, thank you! Let me start with the greatest reward. It’s the chance to work with smart, motivated, creative, innovative people every day on shared missions. To make a real difference in people’s lives. I’ve been very lucky to have coaches, mentors, colleagues, clients- my heroes who keep me on my toes, challenged me to be and do better, and to be super clear about why we do what we do.

I recently told an emerging partner of mine: the past eight weeks of working with him have felt like yet another MBA. I’m super lucky to wake up every morning, knowing that no matter what, I will get to work with incredible people, grow personally, and help move the world forward. What more could anyone ask for?

Regarding challenges I’ve learned over the past several decades, perhaps too slowly that sometimes the world isn’t ready for even the best ideas. I started a company focused on digitizing medical records before we knew that those would be called electronic medical records.

I started another company focused on joining up people’s healthcare data from wherever they receive care. It’s taken 20 years for that to be legislated into existence. So being able to imagine the future and what’s possible, sometimes that’s called being ahead of your time. Sometimes that’s also called being dense.

That’s both a great challenge and a great learning experience for me.

Maria Palombini
Absolutely. I may have run into this a few times, myself. You know, it’s always exciting to be above the curve and you wanna get to the next emerging thing, but sometimes the world is not ready for it yet. And so there’s always a right place and the right time for everything.

Now you’re in this world of Cherish and you can share with our audience, please, what Cherish exactly is and what it’s doing and what inspired you? What was your vision to bring this to the market?

Sumit Nagpal
Awesome. I’ll introduce Cherish in very simple terms. We build advanced sensors in AI and our job, our goal is to help people like our parents, our grandparents, our kids, many of us who may be living either with health challenges or who may be aging, live more safely and with more joy, wherever they happen to be. So we’re using advanced AI and advanced sensors to go help solve some of the challenges that our populations face.

It’s very clear that healthcare’s coming home. The pandemic has shown us many of the types of health and care services that we can now deliver to people at home that we simply wouldn’t have had the incentive to put in place before the pandemic.

What’s been super obvious to me, however, is that if we can reliably predict rising risk for people before that becomes an ambulance ride, an emergency room admission, a hospitalization, we can take out a whole lot of cost to our economies and also take out a whole lot hardship for our loved ones that they go through when they wind up in these situations.

Being able to do this at scale, at a scale that matters, is the motivation behind Cherish.

Maria Palombini
Absolutely. I think that is big area of interest for us here at the Healthcare Life Science practice is figuring out how these technologies can support this growing aging population, as well as the ability to reach the unreachable. You’ve done quite a bit of work in the digital health sector, talking about advanced AI, advanced sensors. Maybe you could share a little bit with our audience, some of your experience, your research, working with different groups and tech gurus, just to give a little bit of firsthand, what you see in this space and where you see the difference and where maybe potentially see it going.

Sumit Nagpal
AI and ML are really helping create a bit of a revolution in what we can do with technology. Our teams just tying this back to the reason we exist, our teams are working to blend all sorts of signal about everyday life. As people go about their day, make sense of that signal to predict the kinds of rising risk that can help keep people out of ambulances and emergency rooms.

Today, there are rules and algorithms that let us deal effectively with some of the signal, some of the time. An elevated heart rate or a depressed respiration rate, being able to use evidence-based rules, being able to raise an alarm someplace. That’s very well understood. There are evidence-based pathways to work with such data, but when you start deploying the kinds of sensors you find on autonomous vehicles to understand how people are doing.

On the one hand, the scale and the kinds of things you can address just mushroom in scope in size. On the other hand, the complexity as well, mushrooms in scope in size. It’s a whole new ballgame with so much more signal to make sense of that these traditional techniques no longer suffice. So we’re doing things with machine learning in weeks and months, that would take literally years to decipher out of the raw data that these sensors produce.

And these capabilities are auto catalytic. They build upon themselves. It all ultimately translates into time to market and scale for health applications that help real people stay healthy or get care before they become more sick. It all translates into lower cost through preventive maintenance rather than expensive repair jobs.

It all translates into reduced hardship. AI and ML are absolutely indispensable to enable these changes at a meaningful scale.

Maria Palombini
Very pertinent point. I think we hear this quite a bit. We’re seeing all this AI at the edge and all these different devices and there’s just real growth and trends towards there. So I’m very excited to hear that you have seen that and continue to experience it as well.

There’s this aging population that potentially might not have access to caregivers that wanna still be independent, or they might actually be in a living facility, but still need care and there might not be enough human resource to support them. Can you give some examples or case studies in the work you’re doing with Cherish to say this is potentially an accepted way or a very pragmatic way to start supporting that aging population.

Sumit Nagpal
Great question. It’s the essence of what we’re focused on. While I’m not ready to share all the details of what we’re doing, what I can say is that our technology will extend the ability to monitor people’s health and safety into what we call all of life, rather than just in those episodes when you’re in a hospital or when you’re admitted, into all of life.

Just imagine if there had been something in people’s homes or in the places where they live nursing homes, care homes, senior living facilities, at the start of COVID something that detected rising heart rate with depressed respiration. Just those two things, that just happened to work all the time that people didn’t have to remember to wear that people didn’t have to remember to turn on or charge. It was just there, present in people’s lives. That would’ve been the Canary in the coal mine to raise an alarm that so many of our parents and grandparents were not okay. That they had come into contact with the disease. We could have seen this early and taken action sooner, perhaps started treatment where they live before they wound up in ICUs and ventilators or worse.

The same with emerging models of care that help bring eventually hospital level care to the home. Most of these models start with an emergency admission. Someone shows up in an ambulance in an emergency room and these models then figure out rather than admitting somebody to a medical floor upstairs, how do you send them home and then actually admit them at home. Imagine if we could detect that rising risk before that ambulance ride, this happens over and over again every day. Imagine if we could prevent those ambulance rides. Imagine the impact on cost. Imagine the impact on reducing hardship, right? So that’s what we’re working on.

Maria Palombini
That’s amazing. I imagine someone hears that message and it’ll be very welcoming for sure.

When we talk about new technologies, there’s always a multi-generational impact, right? You say, well, new technologies is conducive to this age generation. Usually the older generation, you have a, let’s call it a mixed bag. Some who are very technology savvy and some who like, I will say, my parents didn’t even know how to turn on a computer and there’s no such thing as a smartphone for them. So how are you guys preparing or ascertaining the landscape of that sort of aging population in trying to introduce these technologies and these opportunities to them?

Sumit Nagpal
We have a particularly unique perspective on adoption and engagement. We’re taking approach that recognizes that people don’t wake up every morning to use their digital health app or tool. They don’t wake up every morning to live in it, to keep their gadgets charged, or even to keep them on their bodies.

We’re taking that weakest link of the chain, that human operator and this reliance on somehow them changing their behavior completely out of the equation. People in healthcare love to talk about engagement, patient engagement, in particular. I could tell you anecdotes about people who’ve come from other, very consumer centric industries into healthcare and they’ve asked me, what is this patient engagement these people speak of? We think that’s exactly the wrong thing to try to achieve. People want to live their lives with simplicity, with ease, with joy. Let’s get out of their way. Let’s give them tools that help rather than make them feel bad because they’re not using them or don’t want to use them.

Let’s get outta their way with tools that just work behind the scenes, keeping them safe, raising alarm when needed. That’s how we’re going to actually solve this adoption challenge. And that doesn’t apply just to older people. It applies to everybody. The number of applications that people download and then stop using within days or weeks, we’ve read lots and lots of anecdotal studies about this. We think that the way to address this problem, which really works for all are one of our principles is designed for all. And one of the basic rules of that basic guidelines behind that principle is to not rely on behavior, change, not rely on people in different demographics, using different techniques to be engaged.

We think that’s a slippery slope and a recipe for failure. I hope that gives you a sense of at least our thinking around this whole issue of adoption. We think that older people not being able to adopt technology is a red herring. We think that technology has not been good enough for them to make it a part of their lives.

Maria Palombini
Very good point. We actually just did a telehealth competition on this topic. You know, the ability to say that it’s innovation, but it has to be innovation designed for all. And that was really the idea there. There’s another area that I know about Cherish, just reading some of the testimonials on your website.

One of the areas where we’re looking into is this explosive growth of mental health, digital therapeutics. A lot of it being driven from a commercial sort of, you know, go to this app site and just download it. And we’ll help you with whatever potential disorder you might have from anxiety to post traumatic stress disorder.

But I also know your tool can also help that group. How do you differentiate from what you might be seeing everywhere on TV or on the internet now, and really be able to say, we have a trusted tool that can really support, this population of patients.

Sumit Nagpal
So in this area, I’ll say that we’re still in what I would describe as early days, we see some really incredible applications coming again, without making people work for them or do unnatural things, absolutely not requiring any behavior change. And that behavior change goes all the way to remembering, to plug in something or charge something or wear something. All those things get in the way. We hope to be able to tell you more about this over the next year or two, but to give you a sense of direction, we expect to be able to pick up changes in mood, changes in people’s mental state.

Grandpa’s getting depressed. He’s taking longer and longer to get outta bed every morning. Those kinds of things. We expect to be able to do that over the next few years. And we think that can have a profound impact on them getting them the help they may need getting them the support from their families that may need before that becomes a much worse condition.

Maria Palombini
I’m fascinated by this and I really hope you keep us in the loop on it because we have definitely been looking at some of the nuances around digital mental health therapeutics for the elder population. And this is an area we’re covering in one of our industry connections program called Ethical Data Assurance for Digital Mental Healthcare.

So definitely very interested to see how that progresses for sure. So Sumit, when I say AI for Good Medicine, what comes to your mind and why?

Sumit Nagpal
First thing that pops in my mind is freedom because the pace at which healthcare is evolving to create the kinds of solutions I’m describing is just too slow.

Someone I met more than a decade ago, who’s become both a mentor and a friend to me, he was in the audience when I presented an approach to joining up medical records across a city region, this was in the UK. Then another gentleman talked about another approach. He was as sincere as I was, but he followed his thoughts with a comment that he said, you know, it’s going to take us the rest of this decade, the next decade to put this in place.

And this gentleman who’s become, my friend said, so who’s gonna take care of us and our parents in the meantime, there’s this sense of urgency. And AI is an essential part to answering his question, which is really about getting solutions to market in the here and now. It’s about our parents, our grandparents, our kids, our families.

Those are the people we’re talking about here. And that sense of urgency is what drives us. And so freedom is the ultimate impact of being able to bring these kinds of technologies into the service of their daily lives. I think that word really sums it up.

Maria Palombini
And that would be a first because I’ve heard many different answers to that question and I really appreciate the insight behind that. And I think it’ll give everybody listening, something really to think about.

We all know the healthcare inequity challenge we face globally, obviously, exacerbated during COVID, unfortunately for those who are already disadvantaged, but some have argued that artificial intelligence and machine learning can support fairness, personalization, and inclusiveness in healthcare, really starting to cut at that inequity issue. And then others find that it actually might potentially create more inequity in the healthcare system. I think the populations you’re already starting to work, with with your platform, starts to maybe cut away at that concept, but how do you see it from your point of view?

Sumit Nagpal
I think I’m gonna answer that question with one word, which is scale, but let me take a step back. I’m on the board of an organization called HIMSS, which is the world’s largest membership body that represents health and health IT users and their suppliers. This year, our global conference, which is coming up in Orlando in two weeks, we’re gonna be devoting quite a lot of time and energy to talking about health equity.

Because we are seeing the Gulf between the haves and the have nots continue to grow. And because real biases caused by perception of race, gender, socioeconomic status, they cause real harm to real people every single day. That’s fundamentally indisputable. The scale and pervasiveness at which AI and ML can be put to use to help people is staggering.

Of course, what that means is that our training data has to reflect the diversity of our populations and not include these biases into the infrastructure. This is all quite feasible in the hands of well-meaning self-aware people, right? So I am super bullish about AI and ML, actually being able to reduce health inequity, actually spread this technology into the kinds of things that people use every single day, without them being expensive gadgets that only a few have, and the kinds of things that ultimately become just parts of the furniture and fixtures of the place you live rather than special tools and special gadgets. Again, that only if you can afford.

Maria Palombini
I think that’s a great perception. It’s just fascinating to see. Hopefully that opportunity at scale can really address some of these issues.

All right. So we have a great idea. We have a great technology. We have a great opportunity and a patient population that can utilize it, but we still find that we keep running into some kind of challenge. There’s still security lapses, or we need more open data standards, or just a lack of standards, better policy. What do you think is single most challenging part currently not addressed when it comes to the use of AI applications that continues to cause concern or uncertainty in the trust in those tools and using them, what is it? And what might be the best approach in trying to start addressing it.

Sumit Nagpal
So I saw a video recently that talked about health data interoperability standards, and it was really interesting. The stuff that they were talking about was virtually identical, the same words that were being used 25 years ago. We’re still talking about the same topics when we’re close to sending people to Mars and we’re flying rocketships into the sky, like riding a tricycle, and we’re still stuck in the old ages when it comes to these topics. I don’t think that any of this has to do with not enough standards, not the right standards or not the right public policy, et cetera.

I think those issues are actually utterly business issues and those issues will get addressed when this type of technology becomes more democratized when it becomes more ubiquitous when it becomes more available to people for themselves, rather than somebody having to supply it to them. So there are two ways I can answer your question at least.

One, this notion of engagement and adoption. A lot of people who are building solutions think that their human operators are bad users rather than designing systems that eliminate the need for requiring behavior change. Those will continue to fail. This applies to, as I’ve said, thousands of digital health apps out there today. If you design the need to support a user into an app or a tool you’re designing the app or the tool to require people to need support. That’s just how it is. These challenges transcend all such solutions. They result in AI driven tools that behave even worse. And this applies to all these other topics you mentioned as well.

The other way I can answer this question is about the special challenges that are on privacy and security created by AI and ML. There are bad things that bad actors can do with this always on data about people that are made even more creepy with AI and ML, video data in particular.

The way to address this, not requiring this data beyond the inference at the edge. Gather the data at the edge, make your inference, run your AI models there, and then void the data. Eliminate it forever is a great way to delete the entire possibility of a whole class of privacy and trust issues.

Then letting people control and only them control their own data is the other. There are some companies, very large companies in consumer space that have made that their religion, right? You control your own data. You hold the encryption key. Nobody else can get it. And then there are others who live off selling your data.

They think that there’s just the market speaks. Buyers reward companies that behave well. And I think that’s, what’s gonna drive the right solutions. It’s really that simple.

Maria Palombini
I agree with you, perceptually saying that consumer driven best practices are really important and I think they can really maybe change a market mentality for sure.

So you’ve already shared so much great insight with us. There’s so many ideas, like you said, healthcare is coming home. These are really important insights and topics for people to digest. So I’m gonna ask you, is there any final thoughts that you would like to share with our audience?

Advice for a tech entrepreneur, a young engineer on the verge of the next breakthrough, or a call to action from all the different multidisciplinary professionals listening to this podcast today.

Sumit Nagpal
So I’ll go back to something my dad said when I was probably seven years old and I didn’t quite understand what the heck he was talking about.

In a moment where I clearly frustrated him. He said, think big man. I was probably seven. I’ve tried to do that ever since. Um, so dream big. Don’t let challenges stop you, embrace them instead. Think of your journey as an ever evolving puzzle that you wake up every morning to solve rather than a burden to overcome.

It just changes how you deal with it. Use that to stay fresh inspired. And this has been so important to me find a mentor or two, I’m lucky to have many to stay grounded and inspired.

Maria Palombini
Absolutely. I think that is a very positive note, mind over matter. Well, everyone, if you wanna learn more about Cherish visit cherishhealth.com.

Many of the concepts we talked today with Sumit are addressed in various activities here at the IEEE SA Healthcare Life Science Practice. We have so many global experts, even Sumit, is part of our Transforming the Telehealth Paradigm incubator program. Working together, trying to explore, collaborate, look for all these different types of solutions that are needed to continue to open the doors for innovation. You can find out about all of our practice opportunities programs at ieeesa.org/hls.

If you like this podcast, please share it with your colleagues on social media. You can use the hashtag #IEEEHLS or tag us on Twitter @ieeesa or on LinkedIn @IEEE Standards Association. This is the way we get our word out about our podcast interviews to share the insights of our volunteers, our guests, with the rest of the world.

I wanna thank you Samit for joining us today. You have been very inspirational and insightful.

Sumit Nagpal
Thank you so much for having me again.

Maria Palombini
And I wanna thank you the audience for being with us, and I wanna wish you all to continue to stay safe and well until next time.

Maria Palombini
Hello everyone. Welcome to the IEEE SA Re-think Health Podcast Series. I’m your host, Maria Palombini, Director of the IEEE SA Healthcare and Life Sciences Global Practice. This podcast takes industry stakeholders, technologists, researchers, clinicians, regulators, and more from around the globe to task. We ask: how can we rethink the approach to healthcare with the responsible use of new technologies and applications that can afford more security protection and sustainable, equitable access to quality care for all individuals?

We are currently in season three. You can check out our previous seasons on ieeesa.io/healthpodcast. So with season three, our theme is “AI for Good Medicine,” which brings a suite of multidisciplinary experts from around the globe to provide insights as to how do we envision artificial intelligence, or machine learning, or any other deep learning technology to deliver good medicine for all.

We all want good medicine, but at what price, essentially, in terms of trust and validation in its use. As healthcare industry stakeholders, we’re not looking for the next frontier of medicine if it’s not pragmatic, responsible and can be equitably valuable to all.

So just a short disclaimer, before we begin, IEEE does not endorse or financially support any of the products or services mentioned and/or affiliated with our guest experts in this series.

It is now my pleasure to welcome Dr. Dimitri Kalogeropoulos , who is Senior Independent Consultant in global health innovation, digital development, and governance and policy for organizations, including the World Bank, the European Commission, the World Health Organization, UNICEF, and more. Dimitri, welcome to our conversation!

Dimitrios Kalogeropoulos
Hello, thank you, Maria for the welcome! That’s correct. 20 years in international development and global health innovation and 30 altogether in the field of measurement and information in medicine and AI.

Maria Palombini
In this season, we go directly to our technologists, clinicians, researchers, ethicists regulators, and more about how these deep learning technologies can make real and trusted impact on improving outcomes for patients anywhere from drug development to healthcare.

The question is will AI machine learning or deep learning cut through the health data swamp for better health outcomes?

Dimitrios Kalogeropoulos
Let me start by putting things into perspective, before I answer your first question. Prior to COVID-19, digital health was not, let’s say, a public utility. Instead, it felt as if you were in the luxury watch business, then overnight, everything changed. The world now perceives health tech as a necessity, the path to universal health coverage and has set out to discover how to get there. Am I going to do the things embarking on the famous ethics and governance journey? Which is luckily, beginning to read some critical junctures. We get that with that, the challenge is different now. Going digital is all about addressing both local and global challenges. The latter is now the case more than ever before. For instance, our audience might know the EU has developed a financing instrument for this purpose, called the Global Challenges Program of the Neighborhood Development and International Cooperation Instruments for Global Europe and has established mechanisms to strengthen collaboration with other global challenges, programs, such as the Vaccine Alliance, better known as Gavi.

Connectivity has obviously gone global, so how are we faring then? Before the pandemic, a global challenge was to report mortality and morbidity statistics using WHO’s, by now 11th revision, of ICD. And to compare these figures on the basis of national statistical compendia. This was also, world’s kind of common definition of interoperability and interoperable data, and that’s not long ago.

What happened then is that while being fairly inexperienced, all of the sudden we literally went online and sit there. In the meantime that we had been using technology for more than three decades to reinforce how transactional models of reality, the society at large and the economy. And then all of a sudden we woke up to a new virtual reality of real-time digital interaction and task boards.

And so interoperability stopped being theory and became a headache. As a reflex, almost, we pulled out anything we could get hold of to show the world we’re ready to respond and be responsible about it all, including our decisions concerning COVID-19. And we could no longer make decisions the way we used to. Now, evidence is more important than ever before. Since the 2018 World Health Assembly Resolution on digital health, which called for a demonstration of a tighter integration of health systems strengthening with digital health, including our global crisis responses. Quite simply, this resolution means that embracing digital health becomes more normative and thus more scientific.

And this is where my background kicks in— science and ethics in medical decisions and data in order to build responsible and accountable health systems that deliver and promote equitable, affordable, and a universal access to health for all. This is underwritten by a desire to change healthcare and medical research in order to make access more democratic.

Now, to make it all clear, none of this has anything to do with how we finance, but how we use financing for the equal benefit of patients and society at large. Now as for achievements convincing prior to the pandemic, one of the largest multilateral international development organizations to adopt this approach, not on one, but on two occasions in central east Asia, and to move away from the siloed tech understanding of it all, that, in my opinion, is my greatest achievement.

It sounds underplayed, but what has to be in the game to the standard crafting policy is not part of the deployment of international development funds, not before the pandemic anyway.

Maria Palombini
Wow, Dimitri! That’s such a powerful opening statement. Right away you can tap absolutely your passion in this area and all the great work you’ve done.

We often hear, Dimitri, there’s this intrinsic value in the healthcare system. And although that’s true, it has to be instrumental as well. So we have these technologies such as AI, machine learning to extract that insight, but yet we still seem unable to truly rely on it.

So the question we are going to face and get through with you today is how can we make the tides turn the right way? You and I know AI, there’s this great buzz. We see it everywhere. So many different potential beneficial opportunities throughout the healthcare system. But from your perspective, how pragmatic and realistic are the uses of AI in healthcare? Can it and does it benefit the healthcare system today in its current state?

Dimitrios Kalogeropoulos
With regard to what I’m seeing, a moment ago, I brought up the significance of the World Health Assembly Resolution on digital health toward enabling a future where technology serves good medicine and good health for all.

But the question is four years down the line, and after a deadly pandemic, have we learned any lessons? Is health tech now understood as the means to directly influence better care, or is it still seen as a tool for analysis and statistical reflection? What progress have we made toward enabling trusted data sharing for digital diplomacy for value-based care in economics and pragmatic clinical trials?

All these are major targets, but unfortunately, to date, I’m afraid, I believe we have made very little progress towards these goals. Not so much in terms of results, this will follow, but in terms of changing our mentality, when we think health. Instead of enabling a circular economy in health innovation, we are still tapping into whatever pool of data we can get hold of.

Only now, we use AI to feed other AIS, hopefully with reliable data and then evaluating if our data is in data reliable. Confusing, no? It is. One key question is why not make data reliable by design? Make the data trustworthy. Another key question is why don’t we make trusted data available on tap to make the data accessible for any use, without doctoring, cleaning it and curating it as we do currently to develop artificial intelligence. On top of this one also needs to consider the higher demand for data, means a hard data production factor with industry innovation. Instead of a great restart, we ended up with a great pile up of data.

Now in my opinion, we’re still turning away from the problem of data or the elephant in the room. And this is because it is a complex one to solve. It is almost political and we don’t really want to invest in its solution. To give you an idea, I was chatting with a friend recently who is very active in European health innovation. So this friend says to me, to attract funding, you need to demonstrate a clear purpose in terms of the problem being solved. Right? Well, it makes sense. For example, come up with a treatment for cancer. If only it were that simple because we’re seeing progress and hope in this domain and in MS, but through the use of new vaccination technology. And that important association is not that clear after all. Simply stated investors think of market innovation rather than system change platforms or sustaining innovation. And right there lies the core of the problem in this capital misconception of the birth of disconnected, but seemingly focused innovation will magically get us to some ideal future that we know little about.

To give you a clue, at 2021 Open Data and Action OACD Study conducted on early initiatives during the COVID-19 pandemic, found there has been a missed opportunity to use data to address the multidimensional implications of the pandemic with sophisticated enough products and services. Well, that went by very fast. Other studies have made this abundantly clear too, indicating that the lack of access to proper data led to a lack of governance. Data arriving slowly in a rapidly changing situation with empty data fields and with passing-the-bucket processes being the norm. And this report comes from the US.

So let’s face it. Health data is still an abyss, which is why I think it is too early to worry about the consequences of navigational autonomy when we talk about ethics. What we need is autonomous data.

Now the second part about how pragmatic and realistic the uses of AI in healthcare are well, in a nutshell, there’s a huge potential for significant benefits.

The largest benefit will come from enabling trusted data sharing because AI supported clinical processes must be trusted, cost beneficial, in terms of the alternatives or competitors and ultimately clinically effective and efficient. But since the latter also depends on the patient outcome oriented utility of each innovation, rather than an absolute performance part, we have to be clear about what we are expecting.

Consider for example, COVID 19 vaccines. They performed relatively poorly in terms of stopping infection and transmission, but they’re very good in terms of stopping disease progression, and mortality. And this means that we are allowed room for the latter herd immunity to be developed in due time, but not with the vaccine alone.

So this vaccine works like a stent, very similar with current AI applications. Let me give you one example. I recently read an article in the European Heart Journal on an AI tool for the detection of aortic stenosis from test radiographs.

Now, the study showed that AI could detect stenosis in 83% of the cases. We might consider this 83%, not enough. Well, it all depends. What is the average rate of detection, for example, without artificial intelligence, what is the purpose of the tool and what is the evaluation endpoint?

The artificial intelligence would certainly not be patient-facing in this case, a doctor would use it. So then this 83% perhaps is good enough in actual fact. So comparative analysis can be very illuminating when we judge the performance of artificial intelligence.

There’s another example of an AI, recent evaluation for cancer screening that showed the relative reduction of colorectal cancer of 4.8% and the mortality reduction of 3.6%.

And that sounds very low if the data are accurate, but we have to look at the significance from a wider angle, the significance of these results, because it was estimated that the decrease in costs per screened, individual led to an estimated savings of the order of US 290 million at the use population level.

So now that starts making a lot more sense. The real issue here is that the kind of effort required to develop these tools. The effort required to repurpose the tools and update them when bias is detected and the effort required to integrate the tools into clinical practice. Well, it’s quite high. The efforts to carry out these tasks is rendering the deployment prohibitive in terms of the overall cost-effectiveness of the endeavor.

So we need to invest in this problem too.

Maria Palombini
Okay. Dimitri There’s a major focal point of AI machine learning about how accurate are the results from the algorithm. The impetus has placed on the algorithm, but what about the data? What are we not addressing when it comes to the data that is being utilized to train these algorithms?

Dimitrios Kalogeropoulos
It is estimated that the machine learning project must invest 80 to 85% in curating data sets, make it reliable. And then we have to deal with explainability, interpretability, and a host of other issues attached to their available data sources. Our data sources are simply not up to any acceptable reliability standard. Not when decisions are automated with tools integrated in the clinical environment and therefore have to rely on machines to process things like ground truths and diagnostic gold standards instead of actually just feeding them.

But how can we expect any standard of data to reach our AI and other innovations, our research, our decisions, when we know nothing about the origins in quality of this data? We know we cannot trust data and instead of making it trustworthy before it goes up there, in the vast subspace of global health data, we devise instruments, secure it again, we’re seeing the treatment before prevention pattern.

After all, old habits die hard. Innovators have even produced AI with Scouts, the ecosystem for proper data resorting to the use of synthetic rather than real world data. But what happened to the original aim behind big real world data or big data? Well, take a deep breath and imagine deep fakes in health. Scary. Right?

So with all that, we’re essentially rebranding the data issue as an outlier to skew progress completely in the wrong direction and in order to avoid the least attractive of all innovations, that of sharing data. Data about the pandemic and how we may strengthen our health system to deal with the next one should not require a global operation of the scale and scope conducted by the WHO to get hold of, here I’m referring to the excess mortality study, which required vast resources to produce valuable insights. These kinds of insights should be available on those passports that became so popular because of the pandemic, a new kind, which tells you what to look out for when you have X or Y comorbidities and which medicines to avoid as a result.

The bottom line is, it is time we started using data to its true capacity to save lives and improve access to care. And with the new wave of AI, I see both an opportunity to change that as well as a huge risk that we waste the opportunity in all it’s grief, because we don’t understand the extent or exact nature of the stale data predicament.

Maria Palombini
Interesting. I know you mentioned this before: data is an abyss and there’s been so much focus on data and that data is an asset. However, like anything else when data sits stagnant, it has less value not only to helping the patient, but the overall advancement of healthcare. How can we make data more “active” and valuable? Is it something like more open data sharing? Could it be better integration to clinical care, better integration with technologies? What is your perspective on how we can make data more active and valuable?

Dimitrios Kalogeropoulos
All of the above. To make data more active and valuable, we need to adopt the recommendation made in the World Bank’s 2021 Flagship Report: Data for Better Lives. The model it proposes of value, equity, and trust as the social contract with data. With that, we need to build up policies and roadmaps for these still development in health in order to provide for directionality and still the implementation of this social contract. Last but not least, technology policies have to match our normative governance frameworks and institutions must adopt to embrace new horizon scanning and portfolio-based system chains approaches, which are underwritten bioscans, ethnographic research and much more. Regulatory tools such as GDPR are important, but we need to keep in mind once we start encouraging the flow of data, we need to have the mechanisms in place to safeguard trust in the data too. And this, despite appearances, is far from being on the table as a key issue.

We also need to keep in mind tools, such as Software as a Medical Device, in the U.S., or they use MDR and GDPR albeit very important, are extremely inefficient for changing the tide. We need to call it out. We have been wrong about what interoperability means and entails. A little food for thought, how are we going to implement the all important quaternary prevention operations that public health needs? And we are lacking and relevant AMR, Anti-microbial Resistance, policies without interoperability and this to name, but one major pain area.

Maria Palombini
Wow, that’s a very insightful point; a good question for our audience to start thinking about. You know, I like to do this with my guests. I call it the “think fast” question. So here it is. When I mention “AI for Good Medicine,” what’s the first thing that comes to mind and why?

Dimitrios Kalogeropoulos
Good medicine for AI, because digital health is a mirror.

Maria Palombini
Interesting. There’s something insightful to think about. We talk about ethics in AI for various important reasons and we talk about it in the form of validated and responsible use for healthcare. From your perspective, what are the ethical considerations that are not getting enough attention when it comes to the use of these types of technologies in the healthcare system?

Dimitrios Kalogeropoulos
This article I read quite a while ago about how understanding racial heritage can save lives. I was very alarmed with that article, and I think it’s very relevant because this is about the ethics of data, algorithms, pathophysiology models, and relevant decision-informing devices like AI. Also about the collapse of ethics when digital development in health and vast data is not inclusive leading to racial, gender-based, or other forms of bias.

Now this thought article I mentioned presents a case about how early stage chronic kidney disease is similar across racial and ethnic groups. Black people are almost four times more likely than white people to develop end-stage kidney disease and how racially tilted estimated GFR markers have been causing thousands of black people with kidney problems to wait longer to get on the transplant list. Only to now discover that the race-based calculations used in the U.S. after 1999, misled patients and their doctors to believe their kidneys were working better than they really were. Also affecting decisions about medications, diets, lifestyle that could have worsened kidney damage or created other medical risks. Now consider, this formula and something much larger than this would go in a decision-informing system. The consequences could be dire.

Every year, the Stanford Institute for Human-Centered AI compiles an AI index that sums up the state of play in AI, this year in a whopping 190 pages. So I recently read an IEEE Spectrum summary of 12 charts, making some basic inferences of my own to capture the state of play from the ecosystem ethics perspective and here they are.

Number one, investment in AI is off the hook with a number of financing rounds climbing. So single projects attract more financing than new projects do and this is not necessarily a good thing.

Number two, there is still a disconcerting gap between corporate recognition of AI risks and attempts to mitigate those risks.

Number three, AI vision has reached a plateau, which means we need to look elsewhere for progress, perhaps something wrong with our data.

Number four, reasoning is still a frontier of AI.

Number five, ethics everywhere.

Number six, the legislature is paying attention.

Number seven, the carbon footprint of the current AI pipelines is finally being noticed, which begs the question, hasn’t anyone heard of digital recycling?

Number eight, the data ethics problem is clearly still the elephant in the room.

And finally number nine, AI needs women as men are clearly bad at building AI.

We don’t have enough creativity, obviously in artificial intelligence. There’s a point later on, I want to come back to, with regard to bias in developing systems and actually running them afterward. These are the ethical considerations that we need to pay more attention to.

Maria Palombini
Wow. That’s a very strong, I would call it a top 10 list. Something to definitely think about and really a lot of areas like the digital recycling not being discussed or addressed at least as pervasive and important as it should be right now. So very important insight. My next question is about the vulnerabilities when it comes to patient data. In your opinion, what are some of these threats? I think you’ve just outlined some really hard-hitting ones. Where do you think potentially global technical or data standards may be of important consideration to maybe help resolve some of these issues?

Dimitrios Kalogeropoulos
Vulnerabilities, they haven’t changed. The threats haven’t changed and when I say they haven’t changed I’m referring to the past 25 years. Let me quote part of one of my PhD publications, which was written 25 years ago. I quote “the rapidly disseminated practices of evidence-based medicine and outcomes-based medicine or disease management concepts, which were born and developed within the realm of measurement and information in medicine and associated technologies have led to the proliferation of quite a number of approaches to clinical decision-making support. Some of these include the use of advanced IT while some other have negligently avoided the use of the underlying enabling tools. Evidence-based clinical guidelines and care pathways are, but a taste.” Doesn’t that sound current? In many ways, we’re still doing exactly the same thing that we were doing 25 years ago. A lot of potential, very little application in real life. This is a major threat.

So as proud as I am for having conducted research sets two decades ago, I’m astonished that two decades later, we still have to deal with the same impediments to achieve progress in the transformation of our health systems to patient-centered systems through digital enablement and support.

I’m optimistic, nonetheless, that we are not going to wait another two decades as great achievements are being reported in terms of digital in the service of new grassroots, social governance models and change in other sectors. Together with blockchain and other, by now not so much frontier technologies, new superhighway change path forms are being delivered to morph and influence the future we all envision for our health ecosystems. Sure, there’s hype in there too. So what?

Now, as far as standards go, there are plenty underwriting data interoperability, such as as ICD-11, 80-C, LOINC, SNOWMED Clinical Terms, with their application utility in the context of COVID-19 cancer outcomes, classification, and other new knowledge and data classification domains, constantly expanding.

Then there is FHIR with 807 covering a lot of the ground from basic messaging interoperability to discrete data set modeling within messages. Fast Health Interoperability Resources is what FHIR refers to, but we need much more to reach a full set. We need to cover Structural and Organizational Interoperability or SOI and there we lack significantly. By SOI, I’m referring to phenotyping genotypes, enabling the clinical applications of precision medicine, building ethical AI, but doing away with the need to provide handwritten annotations in order to frame the genotypes or to engineer ground truths. I believe we have all heard the case about AI detecting as a diagnostic pattern that octopus ink signature in annotated images and this is something that we have to stop from happening if we are to trust these devices.

Let me add one more experience. A few years ago, I was consulting with a group from a technology savvy country in an international development project. This group reacted strongly to my proposal to use ISO 3940 Standard in the core set, which is by the way, they only, as well as a very mature, SOI standard and Structure and Organization Interoperability standards for clinical data modeling in support of continuity of care. To my great surprise, I recently heard that the particular group is studying the application of the standard in their home country. So the message here is clear. Keep an open mind, think outside the box for cohesive collaboration themes and make digital development far more efficient than it currently is. Because in terms of implementation capacity, we are currently struggling significantly behind the regulatory front runner or rabbit.

Maria Palombini
Wow. That’s great insight. I think you’ve given us so much today. I think with every single response, there’s been some call to get a reference site, to think about different ways of a situation. For our audience, this has been very helpful. My final question to you is, are there any final thoughts you would like to share with our audience? We have a very broad audience. It could be technologists, clinicians, regulators, researchers. Is there a call to action potentially for a data scientist out there or an AI technologist who’s working with the data, may already be in this domain or is interested in getting into the healthcare domain? What is your final imparting thoughts to them?

Dimitrios Kalogeropoulos
Yes, Maria, there are three things I would like to mention. The first one is thinking at the crossroads of leadership and innovation, data governance, that equity and inclusiveness in design teams and design thinking will breed equitable and inclusive designs. This is what I mentioned earlier when I said that women and men are not equally participant in the AI development process. This is probably the most important message technology can deliver for learning health systems that truly empower the patients. To think outside the box, to think without the box in healthcare, we need to empower and engage patients and the community as the teams that will design tomorrow’s equitable and inclusive health systems. And for this gaining the trust to share data is of paramount importance. Trust that will be used to create health systems that learn how to be equitable and inclusive.

With regard to decision scientists or data scientists, I understand that in 1996, the International Federation of Classification Societies became the first conference, specifically featured data sciences and topic, also the year that I completed my PhD research. Now with data science being recognized as a field of science and application, we need to expand our perimeter to safeguards trusted information engineering. Data science needs to push its boundaries and to close the loop from data to knowledge and back to recycled data, to support longitudinal data and to protect the temporal and semantic value of clinical data for providers and for society at large.

Last but not least, the ultimate secret is if keep eyes on the integrated care crosshairs. Focus on concepts like bundled services and value based outcome oriented clinical decisions to reveal the path to longitudinal data, provider interoperability, and trust the data sharing. Remember that digital health is a mirror. In the process, think big, but always start small.

Allow me to also add that further information can be found in articles that are published on LinkedIn Pulse and with that, thank you for the invitation Maria and for being such an excellent host. I hope we get to chat again in one of your upcoming seasons of Re-think Health. Thank you.

Maria Palombini
Absolutely. Dimitri, you’ve given us so many great insights. Our next season is going into telehealth, but a lot of the points you brought up today definitely refer to that whole new paradigm of patient-centered healthcare. And so, to all of you out there, many of the concepts in our conversation with Dimitri today are addressed in various activities throughout the IEEE SA Healthcare and Life Sciences practice.

The mission of the practice is engaging multidisciplinary stakeholders and have them collaborate, build consensus, and develop potential solutions in an open standardized means to support innovation that will enable privacy, security and equitable, sustainable access to quality care for all.

Some of our activities include WAMIII (Wearables and Medical IoT Interoperability Intelligence), Transforming the Telehealth Paradigm, Responsible Innovation of AI for the Life Sciences, and a host of other areas all across the healthcare life science domain. If you’re interested in getting involved and learning more about the programs I mentioned and the others that are in our activity list, please visit ieeesa.io/hls.

If you enjoyed this podcast, we ask you to share it with your peers, colleagues on your social media networks. This is the only way we can get these important discussions out into the domain, by you helping us to get the word out. Be sure to use #ieeehls or tag us on Twitter @ieeesa or on LinkedIn @IEEE Standards Association when sharing this podcast.

So to you, the audience, a special thank you for listening in. Continue to stay safe and well until next time.

Maria Palombini
Hello, everyone. Welcome to the IEEE SA Re-Think Health Podcast Series. I’m your host, Maria Palombini, Director of the IEEE SA Healthcare and Life Sciences Global Practice. This podcast takes industry stakeholders, technologists, researchers, clinicians, regulators, and more from around the globe to task. How can we rethink the approach to health care with the responsible use of new technologies and applications in such a way that can afford more security, protection, and sustainable, equitable access to quality care for all individuals.

You can check out our previous seasons of the podcast on ieeesa.io/healthpodcast. Here we are with season three: AI for Good Medicine, which brings a suite of multidisciplinary experts from around the globe to provide insights as to how do we envision artificial intelligence, machine learning, or any other deep learning technology, delivering good medicine for all?

We all want good medicine, but at what price, especially in terms of trust and validation in its use. As healthcare industry stakeholders, we’re not looking for the next frontier of medicine. If it’s not pragmatic, responsible and can be equitably valuable to all. In this season, we go directly to the technologists, the clinicians, the researchers, ethicists, regulators, and others about these deep learning technologies and what real and trusted impact can they have on improving outcomes for patients anywhere from drug development to healthcare delivery.

Will AI, machine learning, or deep learning cut through the health data swamp for better health outcomes? So a short disclaimer, before we begin, IEEE does not endorse or financially support any of the products or services mentioned and/or affiliated with our guest experts in this series.

It is now my pleasure To welcome Aaron Mann, Co-founder and Senior Vice President of Data Science of the CRDSA, Clinical Research data-sharing Alliance. Welcome, Aaron.

Aaron Mann
Hi, Maria. It’s great to be here.

Maria Palombini
So today we’re going to get to the basics- data. Why we need to make sure data going in will give us the benefit expected with predictive analytics and clinical research. Just full disclosure to our audience, the CRDSA is an IEEE ISTO Alliance. ISTO is the Industry Standards and Technology Organization. It is a global 501 C6 not-for-profit offering membership infrastructure and legal umbrella under which member alliances, such as CRDSA, and trade groups can stand themselves up as legal operating entities. For the world out there, you might not know IEEE does have this offering.

Let’s get to humanizing the experience for our listeners. So Aaron, tell us a little bit about you. You have a well blended professional background having been a Program Leader at Genentech, a COVID-19 data-sharing Lead at TransCelerate Biopharma, and prior to that, a CEO of a big data analytics solutions company. As Co-founder of CRDSA, what drives your passion in working with data? What are you hoping to achieve with this Alliance perhaps you felt may have not been realized in prior roles?

Aaron Mann
I think the passion I have for data is what it is and what it represents. Fundamentally it’s people, it’s experiences. Data scientists, sometimes we look at things as a series of data points, but for me, it the fact that those data points represent things that happen in the real world to people and especially in a clinical trial context, when you think a tough study say we’re collecting about 2.6 million data points per phase three clinical trial, but each one of those is a unique part of a person’s experience. I get passionate about what it represents. I think that drives a lot of why I get excited.

From a co-founding CRDSA aspect, really born out of frustration more than anything else. As an ecosystem we get really good in secondary use of data RIAs, data-sharing, talking about the challenges, the problems, what doesn’t work and we’re very eloquent in that. When we started talking, colleagues and I, people representing data-sharing platforms, academic research institutions, and sponsors, we shared this frustration of let’s start talking about solutions. Let’s get eloquent on solutions. Let’s come together and form an organization that can solve problems that we can’t solve in isolation as a single stakeholder or a single platform.

Maria Palombini
Absolutely. When I was talking to my colleagues in the world of blockchain we talked about blockchain for healthcare and blockchain for pharma, the real purists were like, we really have to talk about the data. He goes, we’re not really getting to the core of this conversation. So data seems to permeate all our technologies, no matter where we go.

The CRDSA is an alliance, obviously, and we all see these numerous amounts of consortium alliances that are being formed in many different areas of the healthcare domain. So how is CRDSA different? What is the vision of bringing this alliance together and what are the alliance’s objectives?

Aaron Mann
We spent a lot of time talking to a lot of people before we decided to move forward, to make sure that we first understood the problem and how we might approach it, but also made sure that we were not duplicating anything that’s already out there. It’s important to understand that CRDSA is not a data-sharing platform. So we’re not a data repository, a data lake, but actually data-sharing platforms are members of CRDSA. So our role is to represent the entire ecosystem. We have organizations like CPATH, Project Data Sphere, that are data-sharing platforms, data-sharing organizations, that are founding members, big biopharma companies, technology partners, CROs. We serve as the umbrella organization, looking for solutions that are common solutions to the challenges that we share.

If you really take a step back, the vision is how do we use the type of data that we have to dramatically improve the sharing and reuse of clinical research data and accelerate drug discovery. The easy way to say it, from an objective standpoint, is we want to make it easy to share and easy to use this data. Do we have enough volume going through systems and are we retaining high and updated utility and secondary views?

Maria Palombini
Absolutely. I think that’s a well-blended mix of partners and participants you have in your group. So I think that gives it a really equal voice across the board.

Many times we’ve heard “what you put into it is what you get out of it.” This might hold true for predictive analytics. I spent a good portion of my career, observing and researching the biopharmaceutical medical device industry and I never thought I would hear the words “open data-sharing” in clinical research or anywhere across the pharmaceutical value chain. We all have come to know pharma and clinical- heavy IP sensitive, regulatory complex, and the highest level of competition to get to the next blockbuster.

So can you share with us exactly or what is meant by open data-sharing in the world of clinical research and why this transformational shift over the course of the last few years?

Aaron Mann
We’re in the middle of the transformation. I’m not sure we’ve actually shifted quite yet. We’re definitely on that journey.

I think it is a mind shift that we’ve seen on the part of sponsors and research organizations. Data is not the new oil. That is something that you used to hear a lot more 10 or 15 years ago. It’s not something that gets more valuable over time. The older, yes, the less valuable it is and it doesn’t have any inherent value until you do something with it. I think one thing that’s pushing transformation as senior leaders really getting that it’s about how you use these data and that’s where you’re going to compete. That’s your competitive advantage. Not the actual having of these data.

That leads to a second mind shift, particularly in clinical research, that this is patient donated data. It isn’t something that’s actually owned by sponsors, but sponsors are good stewards of that data. It’s the patients that are coming into the clinical trial setting. They’re donating their time and their data to further the science and reusing that it’s an ethical imperative to honor the commitments that patients have made on the effort that they’ve put in to supporting clinical trials. That shift has happened.

I think the third, and in some ways, maybe most transformational, is advanced analytics- AI/ML. Because it requires big data, right? And as companies start building internal data marts, internal data-sharing capability, they quickly realize that, wow, no matter how big you are, you don’t have enough data or the right data on your own. Even the biggest pharma companies, when you start looking at things like targeted populations in precision medicine will just, you need more. And so that recognition that you can’t go it alone, no matter how big you are is something that I think we’re just on the tip of the iceberg in terms of how deep that permeates organizations. But it’s a shift that we’ve definitely seen accelerating.

Maria Palombini
Absolutely. I think you brought up a really valuable point because for so long we hear data is an asset, but for our accounting friendly people out there, data could be a depreciating asset.

Aaron Mann
I did a slide at a conference once in Las Vegas. I threw it up there like: data is not an asset. Data is an action. If I don’t do something with it, it’s just not worth it.

Maria Palombini
Exactly. It just sits there. Absolutely valuable insight from that point of view. I think this is a simple question, but I’m sure the answer is a lot more complex. Why has it taken so long for clinical researchers or sponsors of clinical trials to realize the potential of the reuse of the data from previous clinical studies? Perhaps the right question could be what exactly was prohibiting them from using it?

Aaron Mann
A little history helps context on this because the sharing of data in a clinical research, secondary reuse sharing is really a pretty new phenomenon. It started in 2013, at any scale, with a number of sponsors coming together with clinical study data requests (CSDR), but that was 2013. That was external data-sharing and data-sharing in that context, a little bit of an unfortunate term, right? Because it always looked to senior leaders, legal, your chief financial officer, like, well, this is us being altruistic and sharing out, but what do we get out of it?

In 2016/2017, you see the rise of that internal data-sharing efforts, and that really brought a sharp lens to what is it that we can do with these data? How should we be approaching it? I think that would have been accelerated, but there was a big monkey wrench that got thrown in about 2018 with the GDPR. It had this uncertainty around what data protection meant. And you saw a little bit of a slowdown where sponsors said, well, you know, I could share these data from previous studies, but am I taking risks when I do it? How do I understand that risk? How do I know what’s acceptable risk?

And so that had thrown a little bit of a curve ball, but I think we now have the tools to really mine these data. I think the rise of AI, machine learning, predictive analytics, advanced analytics tribes has changed. Fundamentally has sponsors now thinking of themselves as data consumers, not just contributors.

But back to your question of what prevents sometimes the open sharing it’s a chicken and egg problem. If their data scientists don’t see enough volume to use an update of utility and external data that they can access and use, then it looks like a one-way street when it really isn’t. It means that a company may not dedicate the resources that are needed to prepare to trials per sharing, make the policy decisions that are going to promote volume and utility.

Maria Palombini
Absolutely. We hear predictive analytics used across multiple industry domains. What kind of impact can it have on clinical research? Are we talking more efficacious clinical studies, more targeted patient recruitment, better meeting enrollment guidelines, all of the above or something different? Maybe you could share with us a case study where you have seen predictive analytics have a significant impact.

Aaron Mann
I think at some level it’s all of the above, but the part that gets me the most excited is the creativity. What don’t we know? When we combine different types of data, clinical research data with RWD, what new therapeutic pathways might be open or what new hypotheses do we generate that we can then go and test? So I think it’s really exciting to think about the things that we don’t know.

In terms of case studies that I’ve seen, there’s a lot being done about earlier safety signal, identification, and classification. It’s an important one. It’s a place where early linkages can be subtle and therefore machine learning, for example, is particularly well-suited to making better predictive models based on early signals that may indicate later significant problems.

The other area that we’ve seen a lot of work being done, particularly around precision medicine is subgroups of population identification and the improvement of targeting inclusion, exclusion criteria, really trying to make the trials fit the use cases and being able to understand better how those responses will play out.

I think when you take a step back, most importantly, an outcome that we see is can we enroll fewer, but the right patients in trials? When we make trials more dynamic, terminate them earlier, where we save time and patient burden, when the predictive analytics are telling us that things may not be going the right way, conversely, moving them through regulatory pathway faster when we see there’s good reason to hit that accelerator pedal.

I think all of these are use cases that have been done and are being done out there. You can’t share the use case specifics problem in terms of being able to share broadly, but lot of work being done in the area and I think a lot of support within organizations for how this can play out and support their drug development process.

Maria Palombini
Those are really great outcomes. Everybody wants more inclusive and diverse populations, but targeted in their trials. So I think that could be a great contributor for sure.

We all know there’s a difference between AI and predictive analytics. However, we know that they share a common challenge. It is this: if incorrect or dirty data goes into it than an invalid or erroneous outcome will come out of it. From your perspective, what’s happening now with the data that is currently being used, that needs to be fixed and how can the work of the CDRSA eliminate or minimize these issues with the data before they’re applied into these algorithms?

Aaron Mann
I think one of it comes back to a volume problem and an access problem. When I talk to AI advanced analytics companies, one of the biggest complaints that I hear is that we’ve built a really good tool, but all of us are training our algorithms on the same sets that are publicly available, same datasets.

So I think there’s a need for more diverse data and data sets that are ready for analysis and have high data utility. We use the word “data utility” at CRDSA intentionally, because it is clinical research data. The good thing is it is collected per protocol with defined outcomes, objective assessments, all of that. So it’s quality data to start with, but it’s going to undergo this transformation for secondary use. That transformation might be to protect patient privacy, it might be to protect IP, but it’s going to go through something before it goes into, for example, an AI tool. That’s the point where you can strip out utility. That’s the volume bottleneck because it takes resources to do that.

So we’re really working on both problems: volume and utility. The way we look at it is it’s going to take movement on policy. Policy at data contributors, its sponsors, and from regulators to be able to bridge that gap of volume and utility and standards around what does good look like? I think all that we’re doing is creating a better data model and data set utility, going into the powerful tools that are being created that power next-generation drug discovery.

Maria Palombini
I’m sure that would be very wanted by a lot of these tool-developers. I like to do this with all my guests and I call it the “think fast” question. When I mention “AI for Good Medicine,” what’s the first thing that comes to mind and why?

Aaron Mann
Creativity. What don’t I know? What hypothesis did I not even think of testing, but because the system, the tool was able to interrogate datasets in a way that generated some new thoughts or insights, I’m able to develop a new way to look at a problem. That’s the exciting part of this and the part that I get most excited about first-line.

Maria Palombini
That’s opening pandora’s box. Opening the unknown. What can we find out? For sure. We always hear a lot about ethics and AI. It’s a big conversation globally. I think it’s in every domain, not just healthcare. When we talk about ethics it’s in the form of validated and responsible use in AI and machine learning for healthcare and I know that the CDRSA has some working groups on patient data governance, data protection, and data ethics. Why is this important in the scope of open data-sharing and what kind of baseline or blueprint are you guys trying to set for the industry to follow?

Aaron Mann
I think there’s an essential tension in data-sharing. On the one hand, all these calls for open science. You hear those calls from WHO, NIH, share open line. But the same organization, like the UN can say, we want to open science and then say, privacy is a fundamental human right, which it is.

And so you have this essential tension between privacy, protecting patients, and open science. That creates this governance continuum in the middle. From a governance data protection standpoint, how you interpret as a sponsor, as a data contributor, how you interpret where you should be on that continuum, determines how much you’re going to share, how much data utility it’s going to have.

We have seen sponsors that have stripped out all adverse events and demographics from a contributed trial. Because they were being very conservative on the patient privacy side without balancing with the data utility side. That’s the exception, not the rule, but it happens out there.

I think it also is around access. How easy is it to get to these data? Novartis is very public about their data42 project internal data mark, and they just published a paper and got to a point where their internal stakeholders can access their secondary use data in almost every case, it’s an automated approval. In contrast, a sponsor I was talking to a couple of weeks ago where their researchers have to put in a formal research request backed by a business case to access any part of their internal clinical trial data. So you have really different sides of that continuum.

For us, what we’re trying to do or give people, sponsors, anchor points to say, this is a way that most people do it, it’s not prescriptive saying you have to do it this way, but this is the balance of acceptable risk, acceptable IP protection that does the best job of fulfilling the ethical duty to protect patient privacy and the ethical duty to share openly and contribute to forwarding the science.

So we’re trying to really create that blueprint or that anchor point that allows sponsors to have a comfort approach that they’ve got is one that is generally accepted best practice.

Maria Palombini
It’s amazing that we still have this conversation about the tension between data-sharing and data privacy. When blockchain in pharma and blockchain in healthcare came out, they’re like, this could be a potential viable mechanism for that and we’re still here talking about it, but I think it’s a very important, valuable point. In another podcast, they were doing a precision oncology study and it was the same thing. Trying to protect the privacy of the patients and what came out during the study was they actually had a suite of patients that they found other conditions in their data that they weren’t even aware about. So they basically had to contact the doctor to tell them, listen, there’s these suite of patients we use for the study that they have this condition and they may not be aware of it. Had the data being completely anonymized, we wouldn’t even be able to go back to their governing physician and say that this problem existed. It’s always that balance. Privacy is great and it’s a human right, but I think you have to sort of balance the costs that potentially might come with it as well and I don’t think anybody has that perfect answer.

Aaron Mann
I think you’re right. The biggest frustration that I see technology companies in this space having, especially here in the US is that thinking GDPR and data protection at that level, it’s a really sobering, eye-opener. You can’t just reuse this clinical trial data as easily as you would think they should be able to. And so I think there needs to be understanding on both sides of what is acceptable data protection and sensitivity to that, as well as open science and bridging that gap. Again, it’s a hard balance. There are a number of companies getting this right, or biopharma sponsors that get this really right. But it’s still a big tension point.

Maria Palombini
Absolutely. We know there’s a lot of vulnerabilities when it comes to patient data. We’re talking about lack of security, every day there’s either a ransomware attack or some sort of hack into a health institution. We have privacy issues, patient data governance structure issues. I know your group is currently working on the development of secondary use standards. So what sorts of issues are you guys trying to resolve through the development of those types of standards?

Aaron Mann
Our focus is on that transformation piece that we talked about. What happens during the transformation? What information is available about it? Right now, it’s frustrating for data contributors because there’s a lack of consistency across platforms, and often they are contributing the same trial across multiple platforms. It’s frustrating for end-users/researchers because they don’t have enough information about what transformations did or will take place to these data.

There’s frustration around the sheer amount of data wrangling that needs to happen if you take trials from three, four, or five different sponsors and trying to pull them into one analytical dataset and find out that you have to do weeks of data management, just to harmonize it enough to start the analysis.

There’s a real opportunity to have standards and accepted practices starting with just transparency. What are you going to get when you get the trial? What is the supporting documentation you’re going to get? What information you’re going to get about what has been redacted down to the variable level. It really doesn’t help when a sponsor says, well, we’ve contributed to trial, we had to redact some adverse events, but because of patient privacy, we can’t tell you what they are. We’ve seen that. And that’s just not helpful because now I’m not sure I don’t know what I to know and it’s really dangerous because I’m not sure whether that redacted adverse event matters to my research question could be central to it. And then if I’m using an irregulatory setting without that traceability and ability to know what happened from the original trial dataset to what a regulator is seeing, step-by-step you don’t have visibility into that makes it very difficult to use it in a regulatory setting.

So our mission in secondary use standards is to start bridging that gap first by transparency on the transformations, and then moving through issues and challenges like data harmonization ultimately all the way through increasing the utility by having standards for how data should be transformed.

Maria Palombini
Fascinating. Wow, Aaron. You’ve given us so many great insights. I’m sure the shockwave was, data’s not an asset. Let’s call it an active ingredient for clinical research insights, but just for our audience, maybe you want to share a final thought, could be a call to action for data scientists or data ethicists, AI technologists working with the data who may be in this domain or interested in pursuing this area to support clinical research innovations.

What would be your call to them or parting word of advice?

Aaron Mann

I think if you’re with a biopharma company, if you’re on the data management study side, be good stewards of the data that you have. Share it readily and well, and remember that you’re competing on the analysis, not the data. If you’re on the research side, the data science side, you’re a biostatistician, understand that it’s there, it’s a competitive mandatory. Seek it out. Because from an organizational standpoint, there’s no better reason that your organization, your company will share and participate than if you’re biostatisticians your data, scientists are active users of these data. And I think on the other side, if you’re an AI advanced analytics partner technology company, I think that to know is firstly, the data’s out there, your specific client, a large organization may not know it’s there, but it is. It is a real opportunity to push the competitive advantage of using particularly data external to an organization effectively.

So I think it’s a real opportunity for the technology companies to be an agent of change and drive awareness and a mindset shift within particularly large biopharma organizations.

Maria Palombini
That’s really important. Special thanks to you for joining me today and sharing these great insights.

Aaron Mann
Fantastic. Thank you so much. It’s a great opportunity. Thank you again.

Maria Palombini
Absolutely. I could have talked to you on two other topics and take this podcast for a few more hours, but if you want to learn more about the CRDSA or how to become a member of the alliance, visit crdsalliance.org.

Many of our concepts in our conversation with Aaron are addressed in various activities throughout the Healthcare and Life Science Practice.

The mission of the practice is really engaging multi-disciplinary stakeholders and have them collaborate, build consensus, and develop potential solutions in an open standardized means to support innovation, ultimately helping to enable privacy, security, and equitable, sustainable access to quality care for all.

Activities we are in: wearables and medical IoT, transforming telehealth, decentralized clinical trials, mental therapeutics for healthcare, robotics for the aging. There are many different areas and they’re all touching an element of AI, machine learning, and the work they’re doing. If you want to get involved, visit ieeesa.io/hls.

If you enjoy this podcast, we ask that you share it with your peers, your colleagues, or on your social media networks. This is the only way we can get these important discussions out into the domain by you helping us to get the word out. You can use #ieeehls or you could tag us on Twitter @ieeesa or on LinkedIn @IEEE Standards Association when sharing this podcast.

I want to thank you, the audience for listening in. Continue to stay well until next time.

Maria Palombini
Hello everyone! Welcome to the IEEE SA Re-Think Health Podcast Series. I’m your host Maria Palombini, Director of the IEEE SA Healthcare and Life Sciences Global Practice. This podcast takes industry stakeholders, technologists, researchers, clinicians, regulators, and more from around the globe to task with an important question: how can we rethink the approach to healthcare with the responsible use of new technologies and applications that can afford more security, protection, and sustainable, equitable access to quality care for all individuals? We are currently in Season 3: AI for Good Medicine. If you’d like to check out our previous seasons, please visit ieeesa.io/healthpodcast.

So in Season 3: AI for Good Medicine, we bring a suite of multidisciplinary experts from around the globe to provide insights as to how do we envision artificial intelligence, machine learning, or any other deep learning technology, delivering good medicine for all.

We all want good medicine, but at what price? Essentially, in terms of trust and validation in its use. As healthcare industry stakeholders, we’re not looking for the next frontier of medicine if it’s not pragmatic, responsible and can be equitably valuable to all. And this season, we talk with technologists to clinicians, researchers, ethicists, regulators, and more about how these deep learning technologies can make real and trusted impact on improving outcomes from patients anywhere from drug development to healthcare delivery.

The question is will AI, ML, or deep learning cut through the health data swamp for better health outcomes? So just a short disclaimer before we begin, IEEE does not endorse or financially support any of the products or services mentioned and, or affiliated with our guests experts in this series. It’s my pleasure to welcome Alexandra Ehrlich, Principal Healthcare Innovation Scientist at Oracle.

Welcome, Alexandra!

Alexandra Ehrlich
Thank you for having me, Maria. It’s a pleasure to be here today.

Maria Palombini
Super excited. So for all of you out there, Oracle is a multi-national technology company and one of the top five software technology companies globally. One of its major industries that it operates in is in healthcare.

So today we’re going to talk to Alexandra about going through a realization journey of the challenges with healthcare data, the opportunities to make it better, and where we have many miles to go before we can arrive at that last mile, which we know is the patient. Before we get to the core of the technology and the applications and that kind of thing, we really like to humanize the experience for our listeners. So Alexandra, can you tell us a little bit about you? You have an established background in biostatistics and technology throughout different areas of healthcare and life sciences. What has been the most influential or eye-opening experience in doing this type of work?

Alexandra Ehrlich
It was nice to reflect on that point and to think through some of those eye-opening moments that I’ve had. For me, it was really early on. It was right out of grad school. I was working as a fellow at the CDC, the Centers for Disease Control and Prevention in Atlanta. Coming out of grad school, I had dealt with very clean, very concise datasets, right? So the data that I was interacting with through my learning process was very organized and my first exposure to real life data. We were just analyzing very small components, very small number of attributes. It really hit me then that we have so many answers already locked in the data.

There is a lot of information that is incredibly valuable that for either technological or methodology issues we’re not able to tap into. That really shifted my perspective and my passion from just this insight generation approach into really thinking through the holistic process of data and how to unlock data for a variety of use cases. Even the use cases that weren’t the original use cases that the data was collected for.

So that’s guided my path along the way very early on. Keeping the value of data in mind, not just the primary use but the secondary use of data and really thinking through the systems that enable that.

Maria Palombini
Very important. We’ve had a few guests talk about secondary use of data, and that came up quite a bit actually in this season, particularly. So I see that this seems to be all lining up. Everybody seems to have a very important perspective on that side.

I see that you’re very involved in the Oracle Latinos Alliance. We know we want more diversity in healthcare tech. Can you tell us a little bit about the mission of the Alliance and what are some of the many great benefits that Oracle is doing for the Latino community, both within the organization and potentially outside of it?

Alexandra Ehrlich
Oracle Latinos Alliance have a very succinct goal, which is to empower our members, the Latino community, as well as our allies to really be authentic and to show up authentically in whatever context they’re in, at home, at work with their families and their community.

It’s something that’s really at the core of what we do. And we enable that through different mentorship programs, leadership programs, events, everything from cooking classes that are fun to really deep learning experiences with different guest speakers that we have. But at the core is really maximizing the contribution that every unique individual brings.

And that is not exclusive of their outside life and their history. Many of us are immigrants or parents are immigrants or we’re first generation Americans, first generation college graduates, and really creating a space where we can celebrate what maybe at some points in our lives felt like challenges and see the opportunities in that brings to the table and creating that in a corporate environment is important.

And we have incredible support from Oracle. Oracle has done an amazing job in creating really powerful diversity and inclusion programs across every single group that you can think of. And that collaboration across the groups is also very important. And with that support. It’s not just an employee resource group.

It really translates into initiatives for the different verticals within Oracle, the different diversity councils that really are there to assure that diversity perspective and view is taken into consideration for both business decisions, as well as, decisions for the communities that we serve.

Maria Palombini
Absolutely. I think it’s a great support system for sure. And I think it really speaks to the diversity that’s needed to bring attention, especially in the healthcare life sciences side in health tech. So hopefully you guys continue your success with that. So we’re going to get to the core we know with any new technology and application, there’s always this great deal of buzz on the potential opportunities. And now we’re seeing all this buzz about the use of artificial intelligence, AI, throughout the healthcare system. From your perspective, how pragmatic and realistic are the uses of artificial intelligence or machine learning with healthcare data? Can it benefit the healthcare system today as it stands?

Alexandra Ehrlich
I’ll start with the first part of that question. The comment about it being a buzzword and the important point we’re at right now with AI and machine learning is that we have to survive the buzz, right? Because we’ve seen a lot of trends and fads come and go without really providing, the promised value. We have to de-mystify what AI and machine learning really are. For us at Oracle in our approach and at Oracle Health it’s really been around connecting to the tangible ways that AI and ML is already contributing, is already being heavily used in the healthcare and research and drug discovery areas.

If we think of something like NLP, natural language processing, that is a core functionality of a lot of systems that provides value on a daily basis across different types of providers and people interacting with the healthcare system. So that’s been our approach. It’s that first step is to de-mystify what AI and machine learning are and educating in terms of how it’s currently being used and it’s bringing value in different parts of the industry.

The second part of that, which is can it benefit the health system currently? The answer is absolutely. There’s a lot of areas where we can offload a lot of the workload that is plugging the benefit that humans can bring to the table by leveraging AI and machine learning. This is across the board medical imaging support something like safety for drug candidate compounds, unstructured data, right? Unleashing the value of structured data for different treatment pathways, complex treatment pathways like cancer treatments.

Another place where it’s heavily used now and there’s huge room for it to really expand is the algorithms that are used for symptom detection during emergencies. There’s just so many places where it’s currently providing benefit and focusing on that and showing the tangible ways that we can expand on those use cases has been our approach and it’s really getting traction in the industry and we’re getting such a good reception from providers, caretakers, patients, because it’s something that they can understand. It works in the de-mistifying part of it. They understand how it’s tangible, they understand the benefit and then it simplifies what it means. I think we have ideas of what it is that we can educate and be able to maximize the value.

Maria Palombini
Absolutely. We always think about the algorithm, but there’s so much about the data that’s underneath there that we have to think about as well. You guys are a significant technology partner to the healthcare system. What are some of the greatest challenges you’re hearing from the industry when it comes to data?

Alexandra Ehrlich
Data access. The idea of the right data, right person, right time is something that the healthcare industry has struggled for decades. Once we digitized the healthcare experience, we just had more data we didn’t know what to do with, and we’re still running it. It’s an unsolved problem. We’ve been talking about it for a long time, but every time that we’re speaking to the customers, every time we sit back and reflect on our roadmap as we’re offering solutions, that’s really what we go back to.

It’s kind of the core of all the pain points that we encounter is that data access, that meaningful data access. That actionable data for the right person in the right moment.

Maria Palombini
I think it’s very interesting that you use the term “actionable access” to data because I’ve had two other podcast guests tell me about data not being that valuable if it’s not actionable. So very aligned about some of the conversations that we’re having when it comes to data.

It was interesting. I was actually at a conference the other day and it wasn’t regarding AI, it was actually in another topic, but this seemed to be a major point I keep hearing quite a bit. And it comes up as often from the clinician side and the IT administrators is that the other is trying to make the other’s jobs harder, by always integrating new applications and new technologies and new ideas. And it almost sounds like a communication challenge, however, it just appears the way the data is not designed to flow from one place to another is causing all this extra manual resources and errors and I think you started to touch on this a little bit earlier where machine learning and AI can really save on human resource power, but what can it do to start automating some of this process so that both sides have to work together in implementing these technologies feel or more like each other or feel like they can better work together.

Alexandra Ehrlich
That’s a great question and definitely resonates with our experience as we work with our customers and I’ll address that communication part because I do think it’s crucial. Providers feel like technology is something that’s happening to them and the message that we’ve gotten again and again, is that they don’t feel like they have enough input throughout the process of even assessing the right technology, early on seeing what the options are. So that’s something that is changing, but us as a technology partner, we take that into account and we make sure that we communicate that involvement of the people who are going to be affected by these changes and in the technology that will be implemented. But yes, that is the reality of it and in terms of the way the data is, it really is the nature of the healthcare system.

Different parts of the healthcare system, everything from resource management, revenue cycle management, and then the actual clinical lab systems. They all live in separate places because they serve different purposes, right? So your human capital is going to be consumed in a certain way. The end users are going to be very specific versus your clinical data. That being said, the way that these systems are built, they’re very good at what they do. But when it comes to the more complex questions that would require information across those pillars, that’s where we run into issues. That’s where a lot of the pain points are in the bottleneck to really progressing our analytics. That’s one of the places where AI and machine learning shine. I wouldn’t say it’s a low-hanging fruit because it’s not an easy problem to solve, but it’s that automation. Something like automation of data mapping, discovery of unstructured data to create structure attributes for reporting and analytics, going back to the NLP, being able to mine notes in some of these more complex treatment pathways where the clinical systems are in design to collect that granular information. That’s such a big place of benefit for AI and machine learning that we’re moving towards. We’re trying to stay focused there in terms of the health care industry and us at Oracle Health is how do we really leverage that where it makes sense? That’s really a great place to start for a lot of organizations is to see where they can automate some of that more painful time-consuming processes that humans have been taking for a long time.

Maria Palombini
Yeah, for sure. We touched on this a little bit. We’ve heard data is the new goal, data is an asset, data’s the new oil. We’ve heard so many terms about it. When data sits stagnant, it has less value, right? Not only to the patient, but to the overall advancement of the healthcare system. How can we make data more active and valuable?

Alexandra Ehrlich
We discussed this in the beginning and it’s really around understanding the data and defining what actionable is. Often we define what’s actionable almost in a convenient way with the data that’s available. And then we don’t maximize the value of the technology and the processes. So for us, our approach is really working backwards. What does it mean to have actionable data? What does it mean to really bring value and benefit to the end user? And then we work back from there. The technology’s there. The key is really starting there. What does it mean to be actionable for the people who are impacted by those decisions and then work back from there.

Maria Palombini
Absolutely. I think always keeping the end user, who’s going to be impacted by these outcomes, keep in focus. So I like to do this with all my guests. I call this the think fast question. When I mention, AI for good medicine, what is the first thing that comes to mind and why?

Alexandra Ehrlich
AI in good medicine is giving humans the freedom to do what they’re best at. For me and for us at Oracle it’s really around allowing the humans, the patients, the providers, to be able to connect, to be able to truly be present during that healthcare encounter and AI and machine learning can support that. In many ways across the board. That’s really what I think about when I think about that. If you look at the outcomes, anything that’s related to outcomes across any demographics that provider presence is crucial in positive outcomes and being able to enable that and support that is a huge place for AI and machine learning. A huge opportunity.

Maria Palombini
Awesome. I read one of your recent articles and you mentioned that as organizations reach their digitization goals, they’re facing new challenges. The current healthcare system are generally adequately answering specific questions for end-users, but may be limited in addressing more complex questions. So what types of conflict questions are being restricted and what are some of the opportunities to alleviate those challenges?

Alexandra Ehrlich
In the past few years, and especially in the last couple of years, we are evolving our understanding of what influences health and what influences outcomes. The environment, lifestyle, social-economic status, access, mental health, it’s really beginning to influence how we approach care. And that is creating complexity, from a technology perspective and a data perspective. So as we understand that in order to truly make an impact in someone’s health, we have to take a 360 view of that patient. We reflect on everything that it takes in order to do that. There’s a lot of technological barriers to that. The opportunity to that is the creation of longitudinal views of patients and patients in a healthy state. We usually think of patients only when they’re interacting with a healthcare system, but knowing what this patient’s status is and what their context is when they are healthy, it’s crucial in understanding their prognosis and their options, and their access.

So those are some of the complex questions that are coming our way. And that has to do with everything like wearables, right. And a lot of the IOT and a lot of the engagement platforms, engaging with patients outside of the clinic, everything from the centralized trials and out of the hospital care, all these things are a reality today, escalated and accelerated through the experience we had through COVID. So our systems are catching up to that now.

Maria Palombini
Absolutely. There’s so much more going on today. We often hear about ethics. Ethics in AI in the many different applications. What are the ethical considerations that you see, or you can ascertain that are not getting enough attention when it comes to use of AI machine learning across the healthcare domain?

Alexandra Ehrlich
It’s really understanding the bias in our data. Depending on the bias on your data, it depends who you can generalize to. Who the ending results are applicable for. That’s the starting point and also realizing that this has been a big moment for me in the past year or so. When we look at the training data available to us right now, it’s a snapshot of the present. If we want to create a different future in terms of outcomes, especially around the groups and the populations that are underrepresented, we have to understand that original bias. We’re going to have incredible limitations with the data that exists today in order to create predictive models that will really impact the future in a positive way. Knowing the bias in your data and then understanding that data can only take you so far, because it’s only a reflection of our current state, two components of analyzing the bias and being aware of the bias and the limitations

Maria Palombini
Absolutely. We see this bias discussion keep coming up and it’s something very important that we have to take into consideration as an industry. So for sure.

Alexandra, you’re giving us so many great insights. Any final thoughts you would like to share with our audience, data scientists or artificial intelligence machine learning technologists, working with the data who maybe already operating in the healthcare domain, or is interested in getting into the healthcare domain.

Alexandra Ehrlich
This is something that is a north star for our team and for Oracle Health and something that I communicate as a mentor and as a teacher. You have to understand the problem first. Understanding the problem that you’re trying to solve means that you need to understand what that problem solved looks like for the people who are impacted by that. If that’s your north star and you do your work, your due diligence in understanding that then you work backwards. And a lot of the decisions that you make along the way will be informed by that and should be informed by that. So to me, that’s really what we’re lacking- the deep understanding of the problem and the impact of that problem. And also what a solution truly looks like for those involved.

Maria Palombini
Absolutely. Understand the problem that you’re trying to solve. Some things sometimes you just get so lost in its simplicity.

Alexandra Ehrlich
But in technology is easy to do so because we are creating amazing, powerful technology day in and day out. And for us as technologists and technology partners is something that we have to be very intentional in doing. That’s why I feel very passionate about that.

Maria Palombini
Absolutely. Alexandra, thank you for joining me and sharing all these great insights with our audience and for all of you out there, if you’d like to learn more about Oracle’s work in the health care system, you can visit oracle.com. Many of our concepts in our conversation with Alexandra are addressed in various activities throughout the IEEE SA Healthcare & Life Sciences Practice. The mission of the practice is engaging multidisciplinary stakeholders and have them collaborate, build consensus, and develop potential solutions in an open standardized means to support the innovation that will enable privacy, security and equitable, sustainable access to quality care for all.

Some of our activities include WAMIII, the Wearables and Medical IoT, Interoperability, and Intelligence. That’s a global incubator program and Transforming the Telehealth Paradigm, Decentralized Clinical Trials, and Responsible Innovation for AI for the Life Sciences and a host of other activities.

If you’re interested in learning about these activities and how to get involved, please visit the practice website at, ieeesa.io/hls. If you enjoy this podcast, we ask you to share it with your peers, colleagues on your social media networks. This is the only way we can get these important discussions out into the domain is by you helping us get the word out.

So be sure to use #IEEEHLS or tag us on Twitter @IEEESA or on LinkedIn @IEEE Standards Association when sharing the podcast. Alexandra, thank you for joining us.

Alexandra Ehrlich
Thank you. It’s been a pleasure and an honor, Maria.

Maria Palombini
Thank you so much. And for you, the audience, thank you for joining us and listening in, continue to stay safe and well until next time.

Maria Palombini
Welcome to the IEEE SA Re-think Health Podcast Series. I’m your host Maria Palombini, Director of the IEEE SA Healthcare and Life Sciences global practice. This podcast takes industry stakeholders, technologists, researchers, clinicians, regulators, and more from around the globe to task. We ask them, how can we rethink the approach to healthcare with the responsible use of new technologies and applications that can afford more security, protection, sustainable, equitable access to quality care for all individuals? Yes, this is an ambitious goal, but a very important one.

We have previous seasons of our podcast series. You can find them on ieeesa.io/healthpodcast, or you can use your favorite podcast player- Apple, Podbean, Spotify, and more to find us. So here we are with Season 3, AI for Good Medicine, which brings a suite of multidisciplinary experts from around the globe to provide insights as to how do we envision artificial intelligence, machine learning, or any other deep learning technology, delivering good medicine for all.

We all want good medicine, but at what price? Essentially, in terms of trust and validation in its use. As healthcare industry stakeholders, we’re not looking for the next frontier of medicine, if it’s not pragmatic, responsible, and can be equitably valuable to all. In this season, we go directly to the technologists, the clinicians, and the researchers, the ethicists, and ask them about these deep learning technologies— can there be real, trusted impact on improving outcomes for patients anywhere from drug development to healthcare delivery. So here it is, will AI, ML, and deep learning cut through the health data swamp for better health outcomes?

So just a small disclaimer before we begin. IEEE does not endorse or financially support any of the products or services discussed in our podcast, at any time. We’re here to interview the experts based on their innovations and their experience in the field.

It is my pleasure to welcome Dave DeCaprio, Co-founder and CTO of ClosedLoop.ai, to our conversation. Welcome, Dave!

Dave DeCaprio
Thanks!

Maria Palombini
Great. So we’re getting into a conversation about a better understanding of explainable AI and how to better close the healthcare gap. ClosedLoop.ai lives by a mission to improve health and transform care with data science and AI. They are a winner of many different innovations awards, and most notably in 2021, they won the $1.6 million grant from the Centers for Medicare and Medicaid Services Artificial Intelligence Health Outcomes Challenge— one of the largest healthcare-focused AI challenges in history. They beat out some hefty competition and we’re going to get to it into the core of the interview.

I often hear that successful entrepreneurs are those who are passionate about the topic or the mission of their work. I read this story about your Co-founder, Andrew Eye, about his daughter. She was on the verge of a liver transplant after an autoimmune hepatitis diagnosis of her liver. Ultimately and thankfully, a prescription for prednisone saved her from that fate. But the moral of the story, Andrew later learned that in half of all pediatric liver failure cases, they’d never had a diagnosis and in 15% of those cases, they never ran the autoimmune hepatitis tests. No one had ever used past data to improve that clinical decision. Which is where ClosedLoop.ai is hoping to change that course. This is why I’m so excited to have this podcast with you, Dave. So Dave, tell us a little bit about you. I know you’re a Co-founder of ClosedLoop and knowing the story behind Andrew’s daughter, what drives your passion most in this work? How did you get here?

Dave DeCaprio
Yeah, I think part of the reason that story is so powerful is because it resonates with everybody. Everybody has some connection to the healthcare system and an example of where it hasn’t worked great for them.

I grew up watching my older brother struggle with rheumatoid arthritis before there were any effective treatments. And as a kid, I always knew there wasn’t much difference between him and I, but I was able to run and jump and do all kinds of things that he wasn’t able to. That just never really felt fair to me and I think that underlying unfairness, just because he happened to get a disease that I didn’t, I think has driven a lot of my passion for healthcare.

I’ve been in some form of AI in healthcare and life sciences for about 20 years now. I got started with the opportunity to work on the human genome project, the original sequencing of the human genome at MIT. And then was in drug discovery for a long time. One day I was working in drug discovery and I thought to myself, “I don’t think the problem with healthcare that’s most important is that we don’t have enough pills. There’s gotta be something else.” So I started looking around at what were the problems with healthcare and what were the ones that I, as a computer scientist, would have some ability to help fix and that’s how we ended up in the space of trying to figure out how to use all the available data we have to just make all the right decisions, using all the information today. There’s so much technology and treatment, and there’s so many therapies, but we’re not always giving the right treatment to the right person at the right time, given the data we have.

So that’s been my mission.

Maria Palombini
Absolutely. I think everybody has a healthcare story. I also have a similar situation— family members misdiagnosed with cancer, then it was caught too late and then we all know how it works in oncology when things go too late. Everybody has that similar story and it’s really inspiring that you guys take those challenges and turn them into hopefully a cure in some form or another.

What’s ClosedLoop’s, philosophy on tackling healthcare challenges and changes? What is the vision of bringing this innovative, “off-the-shelf” approach to AI tools, this commitment to transparency that you guys are all about?

Dave DeCaprio
As far as the philosophy on tackling healthcare challenges, I think, one of the most important driving factors for us is really humility. Healthcare has enormous problems. It’s super hard, and there are a ton of smart people working on it. And you can’t go in with an attitude of, “we’re going to have this magic algorithm that fixes healthcare, and then everything’s going to be great and we’re going to revolutionize the industry.” No matter what you do most of the smart people are working somewhere else. And so we’ve really tried to focus on, hey, what are practical things we can do to actually make improvements today with the technology that exists today? And importantly, we try to think about not just how we can build an algorithm that does something, but how do we build a set of tools that make everybody a little bit better at doing this?

There’s no way ClosedLoop is going to be able to solve all the problems, but maybe we can make some tools, that’ll help a much larger group of people be able to really make a bigger dent in the problems we face. If you start with that perspective, then you start to think about “how do we make what we do transparent?”

People can’t use our tools if they don’t understand them. How do we make them as simple and robust as possible? And sometimes that means not using the most advanced technology we can find, but trying to use the thing that’s going to work the most, the most often. And so that’s how we try to approach these problems.

Maria Palombini
I’m glad you mentioned that it’s a tool and it’s not going to solve everybody’s problem. But the idea is that everybody’s working towards contributing to solving the problem.

I briefly mentioned the awesome award that ClosedLoop won, but let me give a little background.

The challenge was focused on explainable artificial intelligence solutions to help frontline clinicians understand and trust AI-driven data feedback. We all know this is a massive concern in the industry. And it was to demonstrate how AI solutions could predict unplanned hospital admissions and adverse events, which is a $200 billion problem that impacts nearly 32% of Medicare beneficiaries. This information coming to us from CMS.

For those of you outside the United States, the CMS is the Center for Medicaid and Medicare Services. It’s a government-run payer for certain citizens of the United States, either driven by age or disability, or some other factor. So, Dave, you guys beat out some competition, some large multinational organizations.

Can you tell us what made ClosedLoop’s patient health forecast stand out among the competition? Where did it excel most to meet or exceed that tough judges panel expectations?

Dave DeCaprio
This is always a fun one to answer. There’s a lot that goes into winning a challenge like this. I think the most important thing is you have to believe you can. When we submitted the application, there were 300 plus teams: IBM, Watson, the Mayo Clinic, the Cleveland Clinic, participating.

It’s a lot of hard work and the first thing is you got to believe that you can actually win so you’re willing to put in all the effort it takes to win. Second, one of the things that I told the team throughout the contest was the overall quality of our submission, it’s going to be dictated by the dumbest mistake we make.

I think one of the things that really distinguished our solution was not having any weak spots. There were three parts of the contest: accuracy, explainability, and fairness. And we pushed really hard in all three of those areas and tried to make it so that every element of the solution reinforced every other element. And we didn’t have any spot where we felt like the solution was weak or we weren’t doing something that somebody else would have thought to do and could’ve seen. On the patient health forecast, in particular, this was a user interface to explain the predictions and help drive further clinical interventions.

As a software company, we approached it as a software user interface. It was a particularly important one, one that shows predictions of people’s future health, but the same qualities of user testing, user research, doing lots of incremental iterations. We did like 17 different iterations of that patient health forecast, every time getting more and more feedback on it. What did people like? What did they understand? What did they not understand? And it changed a ton from the beginning of what we thought would be valuable to what people actually found valuable. And so many things approaching it with just a discipline and a process and being willing to put in the work on all those iterations. I think ultimately made something that stood out against the competition.

Maria Palombini
We’re going to get now into the next part about exactly how this sort of project went on. But I think it’s just amazing, the approach.

So ClosedLoop is based in Austin, Texas. Unfortunately, in major Metro areas, we see there’s always a disproportionate rate of disease. Such as cancer, diabetes, and even COVID-19 amongst people of color. These are often marginalized communities that don’t have access to healthcare. So I know that Dr. Jim Walton, Presidency of Genesis Physician’s Group in Dallas, who reached out to you guys to help them sift through the social clinical data of 30,000 Medicaid patients to identify who would be the most risk of getting ill and would have the most significant outcomes as it relates to COVID-19. You get this request, right? You get this opportunity. What are some of the considerations when you first looked at this project and said, okay, we have all this data, how are we going to validate the findings?

I’m sure that you guys were like, wow, this is a great opportunity, but there’s a lot here to go through.

Dave DeCaprio
This was a fascinating project. I think one of the really interesting things about it is a consideration that happens nearly every project we have which is trying to make sure that you’re building an AI-based predictive model, but that it actually maps to some use in the real world in some actionable decision or intervention that can occur.

I’ll explain why that was particularly important in this case. First, there’s a lot when you approach a project like this that you have to understand about just good hygiene, essentially, in building a predictive model, making sure you’re doing appropriate historical backtests, you got representative populations. You’re checking that the model is performing well across all different groups. It’s not biased towards one or another. Those are a bunch of checks that you need to just understand and do and we consider those kinds of table stakes for operating in this space. The good thing is most of that stuff is well documented and if you just follow data science best practices, you can kind of get there.

Where this project got interesting, was that what was going to happen with these predictions? People who worked for Dr. Walton were social workers. This was not doctors that these predictions were going to. These were social workers who are going to be able to reach out and help people overcome some of the barriers they might have to treatment. Because these predictions were going to social workers, the kinds of interventions they could do were more around the social determinants of health than the clinical aspects of it. So these weren’t people who are going to be prescribing new drugs or ordering tests or giving treatments. But they were somebody who could arrange childcare or transportation or get somebody into a community-based program or enroll them with a community food bank. They were having problems getting meals.

So when we looked at what was available to those people, it turned out that what they really needed to know was who was the most likely to have these problematic outcomes? Where that outcome could be improved by addressing some social factors, something else that a social worker could get to.

And so when we built that model, we actually didn’t include every single piece of clinical information we had available, but we focused a lot on including all of the social determinants information so that when we gave those predictions back, each prediction came with some identification of what were the social determinants that were likely modifiable for this person that could actually improve it.

There’s a big difference between just predicting something and predicting something and saying, hey, here is something that you can actually go do with it. That’s one of the fascinating things in this project is it wasn’t about putting this thing in front of a doctor. It was about putting it from the social worker and seeing what they could do. And that actually affected the model that we built.

Maria Palombini
Wow, that’s a fascinating approach. Usually, you always think about the physical right? The clinical side of health, but there are so many social determinants that are barriers, right? To getting, like you said, they can’t afford, or they have childcare or whatever issues.

Another way of looking at the problem. And obviously, the data with it was probably just an awesome finding.

For our audience out there, the goal of the competition was not just about accuracy. When we think about AI, we’re always thinking about accuracy, of course. But it was about explainability and transparency. We all know with physicians with AI, they’re like, I’m not so sure about this thing and how is this all going to work?

What makes ClosedLoop’s software explainable to physicians who are not technologists but they need to use it for better clinical decision making. What exactly does it even mean to be explainable AI?

Dave DeCaprio
I can tell you what it means for us. I don’t want to get into a debate with anybody about what explainable AI means for everyone and what the official definition is, but I can tell you what it means for us. For us, that’s providing with every prediction that we make, the reasons why.

The system doesn’t just put out a number that says, I think you have a 92% risk of going to the hospital in the next six months. It says I think you have a 92% risk of going to the hospital and the baseline risk for somebody at your age with your overall conditions would be 65%. And that difference is because of the following specific things I’ve seen about you. And by “I’ve seen” I’m anthropomorphizing that the algorithm a little bit. But with each prediction comes with: hey, I’ve noticed you were at the emergency room visits recently. You were in the hospital. You’ve had an increase in utilization. Your drugs have changed recently. You had to change your prescriptions and that’s often associated with complications when somebody gets on a new drug. Or maybe you’ve stopped taking one of your medications, and we’ve seen that in your refill records. There are all these individual items that can come up that affect it. And when you show the prediction along with those reasons why that provides explainability. Now, what you don’t have to do is try to explain all the details of how the entire algorithm works and all the math behind it. Clinicians don’t generally care about that.

What they do care about is seeing here’s what the prediction is. Here’s what the baseline for somebody like that would look like and here’s the reasons why this person is a little bit different or here’s what special about them. If you can demonstrate that and show that those reasons make clinical sense to a clinician, that’s the way they gain trust and other clinicians. They talk to them about the decisions they make and why they made them.

And then those decisions make sense. So then they agree. You also need to have enough statistical rigor and enough scale that you can prove that the individual cases people are looking at are representative of everything. But really it’s about explaining an individual prediction. The math part of this is pretty much available.

We use a technique called SHAP Scores. There’s a couple other techniques available. The underlying math is pretty well laid out, but how you present that to a clinician is really important. How you figure out the right significance cutoff for what is important to show and what isn’t. How do you explain those things in normal English terms so that people can understand them?

That’s a lot of what we build around the underlying predictions to make these things actually comprehensible so that people can understand the individual predictions. The interesting thing about explainability is once you start using it, you realize how incredibly valuable it is for not just the explainability piece, but everything about what you’re doing.

When the models come up with a top factor and a top reason why that doesn’t make any sense, it’s just a great trigger that something has gone wrong in the data. Something is up with the validation of this model. If the model suddenly says that, oh, nobody has been taking their prescriptions for the past two months, well, maybe we’re not getting the right prescription data anymore. And we can see that kind of stuff. And it pops right out in the model.

That’s how we approach explainability. I think there’s other approaches that different people have made. And I think we’re all just trying to figure out what’s the right way to do it.

Maria Palombini
It makes sense. We always hear people say if you don’t understand something you tend not to trust it. I think that the explainability from that point of view, if a doctor can understand the points of reference, how it got there, then it all comes together. So I think that’s definitely an interesting and valuable approach, especially for overcoming that barrier of trust when it comes to physicians from that point.

Interestingly, trust. That comes up again, of course, with AI. We see that AI for healthcare tends to trend towards this proprietary algorithm, to solve whatever issue in the healthcare domain they’re designed for. But this sort of proprietary kind of seems to further fuel the distrust amongst physicians. We’re really concerned that these tools may not account for all the patients equally in their patient pool. So this question of bias and how these things arriving at these decisions.

My question to you is how does ClosedLoop mitigate those concerns for this potential bias by giving tools to health systems, to build their own algorithms? Obviously, with the understanding that they might have the tech team to support that kind of effort.

Dave DeCaprio
This is definitely something we see. We talked to several of the bigger companies and they always want to have this model store where you can come in and just pull algorithms off the shelf and then deploy them in your environment.

I couldn’t disagree more with that approach. Maybe at some point in the future, it might be feasible. But I think if you look at the state of the technology today and the state of the data today in modern healthcare organizations, we’re not at the point where you can make an algorithm or a model in one place and then apply it everywhere.

If you have a proprietary algorithm that works off a very fixed data set like an MRI machine that has a built-in algorithm to predict some aspect of maybe ejection fraction for a heart MRI. That can work very well because the data is constrained. But once you start looking at people’s wider medical records and longitudinal data and integrating many different data sources across healthcare organizations, what you end up with is that so much of the variability of the system is in each company’s individual data layout.

And so the idea that you could somehow take one algorithm and apply it in all those things, and be able to validate that at all, it doesn’t make any sense. You have to validate the actual system that’s running, which includes all of that data. And so our approach is very much to how do we very quickly go into an organization, take the data they have available, build and vet a model on their data. So we can actually get their historical data and do historical backtests and validation on their data with their population. And then explain how those models work so that the people who are involved get a sense that this is not just going to work in the abstract. They know that this is going to work on my population.

It is then possible to get that kind of trust. I don’t ever want to say it’s easy to get trust of clinicians and it shouldn’t be. It should be a high bar to get, but it should be possible if you can show them that it’s going to work in their entire system.

Maria Palombini
Absolutely. Physicians have to earn patients’ trust. So I think when we look at the chain, that’s pretty much the way it will go, for sure.

I like to ask this question of all my guests, think fast type question. So here it is. When I mention “AI for Good Medicine,” what’s the first thing that comes to mind and why?

Dave DeCaprio
I guess I’d say health disparities. The difference in healthcare outcomes, particularly in the US, based on a variety of factors— race, socioeconomic status, gender. There are massive disparities in the outcomes that people have that are not dictated by biology. They’re dictated by societal differences. And these are huge problems. You look at the problem of health disparities, socioeconomic status, nearly every model we build, if you include socioeconomic status as a factor, it comes up as significant. So it is always important. For nearly every outcome that we look at, this is a really big problem. It’s something where it requires an active fix. If you just use AI and machine learning to build systems and don’t think about actively reducing health disparities, what you’re going to do is embed those disparities in the systems that you build.

So it’s not a problem you can even ignore or deal with later because you will make it worse if you build systems today. There is a huge example of this with a model that was trying to select people for chronic care management programs based on their prior healthcare costs. There are racial differences in how much it costs to treat the same illness among different races.

And so that model ended up being racially biased because it was treating people who historically were more expensive, were being treated by the model as being historically sicker. And so it was directing more resources towards them. And so it was an example of a model embedding a past inequity into the future.

For me, it’s a question of AI for good. You have to be on one side or the other of that argument. If you’re not building for bias and fairness into the models you’re building today, that means you’re building models that reinforce inequities.

The final reason that this comes up to me is that overall it’s sort of a “win, win, win” for society when you address these. Medicare in the US takes care of everybody over 65. And so the healthier we can keep people and the healthier we can keep the population, the better off society is as we go forward because in the end, when people hit 65, Medicare ends up bearing a bunch of those costs. And Medicare means the federal government and the federal government means everybody in the United States is paying taxes.

So ultimately trying to reduce these disparities is very important for not just the health of the people who are being affected, but really also the overall competitiveness and healthiness of the country as a whole.

Maria Palombini
Absolutely. We want to focus on aging healthy. As we all know, the aging population is the fastest-growing segment and it’s going to outpace the younger generation and it’s not just about them living longer, it’s them living longer healthy. So I totally agree. It’s really important.

I wish I would have had you on the first episode of this season, we had a debate on whether AI could help address the issues of healthcare inequity, or some have argued that AI actually makes that gap even wider. The guest that I had agreed with what you were saying, that AI has this opportunity to better address it, but we have seen this debate and it keeps going on. Definitely appreciate your insight on that one, for sure.

Dave DeCaprio
Absolutely. It does have the potential to make things better or worse. It’s all in how we use it.

Maria Palombini
Perfect, almost into our segway about ethics. Ethics means many different things to many different people. Here, we’re talking about in the form of validated and responsible use in the use of AI and/or machine learning for healthcare.

Given your work in various healthcare use cases, what would you like the global healthcare community to know about these types of applications that perhaps they may not be aware or misled when it comes to truly and potentially improving the patient’s health outcomes?

Dave DeCaprio
I think one of the first things for people to realize is that fairness is not a math problem. When you build a model, there’s certain checks you can do to make sure that the model isn’t inherently biased towards one protected group or another, and those are important and straightforward things that you should do. But, don’t take that to the extent of believing that there is a simple report you can run on your model and it comes back with a big green “fair” checkmark or a red “not fair ‘X'” on it.

Anybody who’s trying to simplify these issues that much and tells you there’s something you can run to tell you if your model is fair or not, those people are trying to sell you something. It’s a complicated issue. Fairness is, again, you can’t just look at the algorithm, you have to look at the way that model is being used.

And as an example, you could look at something like racial differences in use of the emergency department. You can go see that different racial groups use the emergency department more or less. It’s unfair to use that information to decide how much you’re going to charge people for health insurance. That’s actually illegal and we say you can’t use somebody’s race to do that. However, if you’re trying to decide which people you should outreach to, to help them, you have an education program about proper use of the healthcare system and when you should go to a primary care provider, and when you should go to the emergency department. You really want to target that towards the right group of people. And so then it may make sense to use that same information for a different purpose. And so fairness, that one model that uses this piece of information, maybe fair when used to determine who you should be educating about proper use of the health system and not fair when you’re using to decide health insurance cost. And so you can’t look at fairness independent of the application of the model. I think that’s probably the first thing that I’d like people to know, and that applies to everything, not just healthcare.

The second point I have is really specific to healthcare and it’s that common fairness metrics often point you in the wrong direction in healthcare. There’s a common fairness metric of quality of outcomes and in some contexts, that’s a very common standard for fairness that’s used in a lot of places and it’s very appropriate.

If we look at giving loans based on gender, we’d ideally say that we would like gender to have no outcome on the outcome of a loan. And we’d ultimately expect in a fair world that the same number of men and women would get approved for loans. Now, there can be a lot of disagreements on if that’s not true, is it really unfair or not? But I think we can all agree that ideally in a perfect world, that would be the right outcome. If you’re building a model to decide who should get breast cancer screening, the answer is not that men and women should get it equally. Breast cancer does actually occur in men. It’s not a zero occurrence thing, but it’s obviously far more prevalent in women.

And so if we’re building a model, a fair use of the model that is trying to figure out proactive outreach around breast cancer, it should be biased towards women. The right answer is that the model should choose many more women than it does men. And so you can’t use these simple metrics that work in maybe a loan decision, in a healthcare context and expect them to get the right answer. And in fact, often they will pull you in the wrong direction.

All of that is to say, you have to think specifically about what you’re doing. There are some good frameworks available to think about these issues. Always consider that health care outcomes can be different than other kinds of outcomes and you need to take that into account when evaluating AI or machine learning.

Maria Palombini
Absolutely. One size cannot fit all and I think that applies to every aspect and every element in what we do in the healthcare system. For sure.

We talked about the great opportunities, the exciting learnings, the innovations, what we’re doing— if you had to think of the most challenging aspect or gap, it could be lack of policy, lack of open data, cybersecurity issues, privacy not addressed right now in these AI applications that continues to maybe cause concern, uncertainty, lack of trust in the tools, what would it be? Why? And in your opinion, what may be the best way to resolve it?

Dave DeCaprio
When we talk to customers and various organizations about AI applications, I think one of the biggest areas that people have is trying to think about the ultimate future they want to get to, and the ultimate vision of what they have and not thinking about the practical steps you can take today.

In a sense. I think all of the problems you brought up, security, privacy, lack of open data, all of these things are major obstacles and they all have big issues that prevent us from the sort of “healthcare data nirvana” that we could imagine. But none of those things means we can’t make progress.

Every one of those, there are practical solutions to get things moving today. I think one of the big things that we see that we try to overcome is to get people to think about what you can do today, with what you have and how to get moving and get practical advantages now. Because the only way we get to that bright future is demonstrating the power of the technology today.

When people start to see that even with all of these barriers confronting us, we can still actually improve decisions we are making today. We have people in Dallas. We have people in Chicago, New York, rural areas throughout the country where we’re making better decisions today using the imperfect data that we already have. And if we can get people to accept that we can start using all of this technology and we can gain trust in it even before everything’s perfect, then I think we can start to move forward and that provides the momentum you need to tackle those bigger challenges.

Maria Palombini
Absolutely. Although I’m going to tell you that I like that term “healthcare nirvana.” I might borrow that from my next webinars series, by the way.

Dave, you shared with us so many great insights. I will tell you that my favorite quote is “fairness is not a math problem.” I might put that on my wall at work. But any final thoughts that you would like to share with our audience? We have many technologists here at the IEEE and beyond our walls who may be already participating in this area of tech in the healthcare domain, or thinking about going into it, any calls to action or things to think about that you would like to impart with them?

Dave DeCaprio
I think I’d say for the technologists considering or interested in healthcare, but who maybe hasn’t been in this space, don’t be afraid of it. It is complex and it is challenging, but it is also very rewarding. It is all things you can learn. It is all problems that can be tackled. So there’s a barrier, but don’t be afraid of getting over that. And then, once you’re there, one thing I’ve already mentioned is humility. Understanding that problems are very large and you can have a huge impact without revolutionizing the system. There are many problems that are broken, find something that’s broken and try to fix it.

And importantly, along with that humility is always remembering, especially for the people who are down in the data that every row in that dataset is a human life. It might be your mom. I always tell people, you can do an analysis and get a result and you might be happy with it. But then what if I told you that row 10 in that analysis, was your mom or row number six was your little brother.

Would you still be happy with it? If you’re in healthcare I think you have the responsibility to ask that question to yourself every time. And every time we present a result or we build a model, we try to think, would I be happy if I knew the output of this model is going to be brought on my mom. And if you’re not, you probably shouldn’t be doing this.

The people in that dataset are somebody’s mom. You need to think about that. So there’s an additional responsibility, I think that comes with health care that you don’t have necessarily when you’re analyzing ad impressions on a click stream. But there’s also along with that responsibility comes the impact you can have and the knowledge you’re actually really affecting potentially somebody’s health and some of the most important decisions they make in their life.

Maria Palombini
Very well said. I think that you just really humanized what you guys are doing with tech. It could be my mom, my best friend, my sister, my brother. And sometimes that gets lost, but I think you just brought it back down to earth.

I want to really thank you for joining me today and having this awesome, great conversation. It’s really been a delight. So thank you so much for joining me.

Dave DeCaprio
Thanks, Maria. It’s been wonderful for me.

Maria Palombini
For all of you out there, if you want to learn more about ClosedLoop, visit ClosedLoop.ai and you can see the awesome work that they’re doing in different areas of applications and their next steps moving forward and what they’re embarking on.

Many of the concepts we had in this conversation with Dave are addressed in various activities throughout our Healthcare Life Science practice here. Our mission of the practice is a lot what Dave referenced today. It’s really looking at how we can support innovation, enable privacy, security, and equitable, sustainable access to quality care for all individuals.

We have projects and initiatives such as WAMIII [Wearables and Medical IoT Interoperability Intelligence, Transforming the Telehealth Paradigm], Decentralized Clinical Trials, Ethical Assurance of Data-driven Technologies for Mental Health Care, and Robotics for the Aging Healthy and Assisted Living. These are all activities people from all over the globe, experts working together, developing standards, identifying situations and challenges. So if you’re interested and you want to learn more about these activities, they’re all open and free to participate. And you can visit ieeesa.io/hls for the healthcare life science practice.

If you enjoyed this podcast and you find the things that you heard today really interesting, and you want to share them with your peers and colleagues, please do so. This is the way we get the information out to the domain, letting them know about the great ideas and all the opportunities and challenges with using these technologies in healthcare. Be sure to use #IEEEHLS or tag us on Twitter @ieeesa or on LinkedIn, IEEE Standards Association when sharing the podcast.

I want to do a special thanks to you, the audience, for listening in today and continue to stay well until next time.

Maria Palombini
Hi, everyone. Welcome to the IEEE SA Re-Think Health Podcast Series. I’m your host Maria Palombini, Director of IEEE SA Healthcare and Life Sciences Global Practice. This podcast takes industry stakeholders, technologists, researchers, clinicians, regulators, and more from around the globe to task.

How can we rethink the approach to healthcare with the responsible use of new technologies and applications that can afford more security, protection, and sustainable equitable access to quality care for all individuals? You can check out our previous seasons on ieeesa.io/healthpodcast or use your favorite player- Podbean, Apple Podcasts, Spotify, and more.

Here we are with season three: AI for Good Medicine, which brings a suite of multidisciplinary experts from around the globe to provide insight as to how do we envision artificial intelligence (AI), machine learning, or any other deep learning technology, delivering good medicine for all? We all want good medicine, but at what price? Essentially, in terms of trust and validation in its use.

As healthcare industry stakeholders, we’re not looking for the next frontier of medicine if it’s not pragmatic, responsible, and could be equitably valuable to all. In this season, we go directly to the technologists, clinicians, ethicists, regulators, and researchers about how these deep learning technologies can make real impact on improving outcomes for patients anywhere from drug development to healthcare delivery. Will AI, ML, or deep learning cut through the health data swamp for better health outcomes? Let’s find out. So a short disclaimer before we begin. IEEE does not endorse or financially support any of the products or services affiliated and/or discussed by our guest experts in this series.

It is my distinct pleasure to welcome Dr. Maria Luisa Pineda, Co-founder and CEO of Envisagenics. Welcome, Maria!

Dr. Maria Luisa Pineda
Oh, thanks for having me, Maria.

Maria Palombini
I am super excited with this interview. We’re going to talk about how we can get a better understanding of how artificial intelligence and HPC, high-performance computing, mixed with RNA sequencing is accelerating drug

discovery. So the mission of Envisagenics is to discover therapeutic points of intervention, to cure diseases caused by RNA splicing errors, using AI and HPC. Envisagenics partners with renowned institutions, such as Memorial Sloan Kettering Cancer Center, and has been recipient of grant funding from National Institute of Health and other world-recognized endowments.

I like to humanize the experience for our listeners. I’m going to start with a very important quote, and there’s a reason why I’m going to share this quote with everyone. “Behind every successful woman is a tribe of other successful women who have her back.”

I had the unique pleasure of meeting Dr. Pineda a few years ago at the Health Conference that was taking place in Las Vegas, just before the COVID pandemic broke out in the United States. I actually contacted her out of the blue through LinkedIn and told her I was hosting a session on AI and Women in Health and she immediately responded and agreed to speak in the session. From the first minute I met her, you can sense her enthusiasm and passion. Her dedication to inspire and share her story to mentor women in the field automatically made me think of words I have heard often from women like Robin Roberts, Sheryl Sandberg, and others when they say behind the successful woman, there’s more often a woman mentor behind her. Plus Maria being from New York, automatically I kind of right away just felt alive with her having that background. I felt like I was talking to one of my friends.

What inspired me the most when I was talking with you, Dr. Pineda is when you first opened my eyes, that AI will potentially become the new pipeline for drug discovery. She shared her work at the time with some unique findings on genetics of patients with triple-negative breast cancer. Their work exposed why these patients were not responding to chemo like in traditional therapeutic applications. As the day went on, she also randomly mentioned to me, she was hiring staff for her company and she said her preference was not to see the person’s name on the resume— I never forgot that. She said her interest was to see the qualifications of the person. Gender, race, ethnicity, or any other demographic indicator had no position in her decision for the right candidate. Like I said, I was inspired by the moment I met you in that meeting room. So I am so delighted to have you here today.

Dr. Maria Luisa Pineda
Aw, thanks, Maria. That’s really nice. You have great memory and it’s pretty impressive. So I’m very excited to be here.

Maria Palombini
Thank you so much. Tell us a little bit about you. You studied to be a biologist and had early success by being awarded an endowment of $2 million from the Goizueta Foundation. I’m not sure if I’m saying that, right?

Dr. Maria Luisa Pineda
Goizueta, yes.

Maria Palombini
And you were an NIH fellow and more. What drives your passion to not only help patients but also at the same time, your passion simultaneously to mentor women in the field?

Dr. Maria Luisa Pineda
Well, I was raised by a really strong woman— my mom— entrepreneur, businesswoman, raised three children by herself. So I think it starts by that— being raised by a strong woman and businesswoman. I learned and saw that. Now that I’m a mom, it’s even more important because I see how difficult it is, but how important it is and I could really see how women can do everything in their power and that they put their mind into.

What really makes me passionate always since I was very little, has been science. I’ve been doing science since I can remember and when I moved to this country, I ended up getting my mentor at Barry University and she was a German Scientist, a woman. Not only was she a great mentor, but an ally. She was always helping me on the science and I was a high school student back then and she helped me put a science project together and then I ended up winning and placing in the Intel International Science and Engineering Fair. With the funds I got from winning, I bought my first car, but that also allowed me to get a full fellowship from the Goizueta Foundation, which was run by the widow from the CEO Founder of Coca-Cola, who was Cuban-American. She was looking for a Latin X student that they could fund and after I won the science fair, she saw me in the newspaper and was able to give me that endowment; which what I was able to go to private school with. On top of that, then I was able to get NIH grants and when I pursued my Ph.D., I was able to also get Beckman, and Hearst Foundation Fellowship, and allowed me to realize this country provides so many opportunities for people that are interested in are proactive and are passionate in what they’re doing.

And for me, it was science, but while I was finishing my Ph.D., I realized I was not only able to do very good science but also all throughout my career, I was able to get my own funding for school, for research, and started a couple of groups of what can you do with a Ph.D.? Not only for females but for all Ph.D. students in the tri-state area, New York, New Jersey, Connecticut. Because I realized I could get my own funding and I was very good at this business thing, but I wasn’t sure what it was or what it meant, but I was mentored then by venture capital angel group founded by women to fund only women in C-level positions in companies, it’s called Golden Seeds.

And it was really impressive because women that start companies are in C-level positions actually have higher returns for their investment. So my passion is not only science, but also making a difference and having references and getting mentored by women and really good men allies, but being for other women in the United States, being that person for them and having a reference for them, because it is possible. You just have to make it happen.

Maria Palombini
Absolutely. I think it’s an inspiring story. This is why I started with the quote with the tribal women behind the woman is because this always ends up that way. I mentioned a little bit about Envisagenics, what the vision is, but how did a biologist by training, marry the science to this cutting-edge platform, using AI and high-performance computing, to accelerate these valuable insights that you guys are now generating and finding?

Dr. Maria Luisa Pineda
When we were at the lab, my co-founder, Martin. We were lucky to be part of Adrian Krainer’s development of Spinraza. We were seeing everything that was being done at the lab. And we partnered with Ionis Pharmaceutical and Biogen for children with Spinal Muscular Atrophy, which is a genetic disorder where children’s muscles stop working.

My professor, Adrian, and his team were developing in partnership with these other pharma, this small RNA therapeutic that could fix this RNA error in children with SMA, Spinal Muscular Atrophy. It took them almost 12 years, but the children, that couldn’t move a single muscle are now walking, are sending Adrian like little trinkets and pictures of him. That means their muscles are working again. They’re smiling again. So I was like, wow, that’s amazing. I wanted to do what they did with Spinraza, but instead, do it for many other indications. So what we were doing because Harvard did the human genome

sequencing. We had availability of sequencing and back then, one whole human genome could be a terabyte or so. So the data was starting to get bigger and it was very expensive in the beginning to do them, but the sequencing was getting cheaper and there was all this new technology that we could use instead of doing it on-premise, right on the computer.

We had this thing called the cloud that’s starting to be developed at the same time as sequencing. So the premise was using cloud computing, hyper-performance computing, so we could automate and accelerate what we were doing on-premise, right on your computer, in the lab faster.

It used to take us four to six weeks to analyze one dataset. Now we can do a thousand patients in under two hours. The premise of data and the amount of technology was exponential. So how do we use tech and high-performance computing or any sequencing machine learning so we could actually extract all that information and use it for therapeutic development?

While we’re building the company, we wanted to make sure that after we extracted truly meaningful data, we also had a biologist team that could then validate everything that came out of the AI/ML platform. It was very hyped in big pharma, so we wanted to make sure that we had a proof of concept that we actually were able to validate the findings that the platform was showing. Because, as my co-founder says, “everything is in the pudding.” Meaning, you really have to showcase tangible things because data information, it’s very abstract for us to generate therapeutic for patients so they could get treated and have better outcomes in their life.

We really had to take all those findings and validate them. So we did that with a case study that you said in triple-negative breast cancer, which has a very high unmet need for women in the United States and Europe. We have around now 50,000 women and there’s nothing available. What we wanted to do is use our platform at least to identify the right targets, which is exactly what my platform does, is identify that target for the right patient population. So then you can stratify them then design an RNA therapeutic or other types of therapeutic modality so we can target it the right way, finding the right drug for the right patients, basically. And then repeating the process over and over again. Machine learning and AI allow us to say no in a faster way, or keep putting more resources because what we do is extremely expensive.

In order for us, to accelerate and change the way that we do discovery instead of testing random drugs and see which one works, we actually identify the target and then develop the chemistry for that target, which then we can stratify the patients for that specific target, which becomes a component diagnostic as well as a therapeutic. We can do that now in less than eight months.

Maria Palombini
That’s really great. I think this is when we really think about the real potential of these kinds of platforms. But for some of our audience, who are not really scientists, they’re more on the technology side. So let’s just say we have to give a little bit more about this RNA thing.

We’ve heard about the mRNA vaccine from Moderna and Pfizer. Can you share with our audience what it means exactly by RNA splicing and the types of diseases that are most likely to be caused by this type of “error.”

Dr. Maria Luisa Pineda
First off, we’re heavily a health company based on RNA, so we’re very grateful that mRNA vaccines were brought to attention, but generally speaking, in order to create and make your body work properly, you have to create proteins. Protein is what makes all our tissues/our body function properly, but then, we all have the same genes. So, how do we all look different? That’s called RNA splicing. RNA splicing is how you cut and paste all those genes to make different proteins. That’s what makes all of us diverse. You look different than I do and even my siblings look different, but we all have the same genetic information. RNA splicing creates the diversity of the human genome and the proteins are being made. Then there’s many errors or some that are cis-acting or trans-acting. The cis-acting are like genetic disorders, just like spinal muscular atrophy, which is, making an error on one gene. Where in trans-acting, it’s more of when this splicing factory, which is the largest factory of yourself, has around 300 proteins. It tells you how the proteins are being built and when it gets messed up because it has 300 proteins, many things can go wrong. That’s where machine learning and platforms like mine could use machine learning and AI to basically look at opportunities and understanding how these errors are being made.

Most of the diseases that happens to are things like cancer- a number of solid or hematopoietic cancers, meaning, breast cancer, lung cancer, leukemia. Those don’t have a lot of DNA errors, but they have tons of RNA errors. When

you’re trying to develop a therapeutic, you should understand how that disease is being toxic to your body.

We use our platform to basically understand sequencing, and all these machine learning modules or algorithms to understand and extract all that insight of how the disease has been affected- which proteins are present in the disease patient and not in normal tissue. So when we were deciding the therapeutic, we’re hitting the right protein. Then if it’s too toxic, then we take it away, we put a bandaid (which is an RNA therapeutic), or we change it, or maybe use your immune system, which is fighting to make you feel better. We use the immune system to kill it, to go and eat it. There are different ways that RNA splicing errors could help.

I think the other ones are neuromuscular disorders or neurogenetic disorders. Those have 10 proteins that are messed up in most of those disorders. 8 out of 10 are RNA splicing factors. You really want to make sure that you can group patients by their RNA errors and understand what’s happening and the biology behind it. So then when you’re deciding drugs and therapeutics for them, you are doing it, understanding the mechanism of action and understanding what’s happening within the disease.

Maria Palombini
That’s just fascinating. I mean, just the insights alone. You’ve really hit on what the platform SpliceCore can do. What makes this platform so unique?

Dr. Maria Luisa Pineda
SpliceCore Platform utilizes RNA sequencing datasets for discovery purposes. For those that don’t know, once you have a tumor, that tumor normally goes to pathology so they can see what’s going on in the tumor. So you can get what type of cancer you have, what stage it is, but you also get a lot of sequencing, RNA specifically. We upload it to the cloud and then we use that against our transcript of reference like a map. We have approximately 7 million splicing targets. Instead of looking at genes, we actually don’t care about genes, we care about exons- three exons together, because they could be targeted by therapeutics.

By reenvisioning the human genome, and instead of calling these genes, we call these 3 exons and RNA splicing events, we now have 7 million of those. If you’re looking for something to drug and the database is only 33,000 then if you go through all your 33,000 and you do not find anything, nothing of your

chemistry set, then you give up. But when you have a 7 million target list, then you have more possibilities. Out of the 7 million, again, not all of them are good drugs and that’s where we use machine learning and AI.

We use different features because of having coincidences between data sets. Let’s say we find some samples- datasets from patients in John Hopkins Medical School, and then we go to the Broad Institute and then we go to MGH at Harvard and get three different datasets from breast cancer patients. And we find this target that is present in all three different cohorts of patients and not present in normal tissue.

Then we say, okay, this isn’t coincidence. Something might be going there. So we use these features, or I call them filters, and we diversify our approach instead of taking a funnel approach per target selection. Because in a single funnel, if we use the same filter for everything, once one goes bad, all of them will, because you use the same filter, right, or same approach? Instead, we use a diversified approach where we use different filters. By doing that, then we can identify targets for different modalities. Modalities is the type of chemistry that you use for drugs. So you can have targets for RNA therapeutic or antibodies or for small molecules. Depending on the chemistry that I use, the targets will look different, so the proteins will look different. We really use the platform like that.

Maria Palombini
That’s just awesome. These levels of data that your guys are getting to is just unbelievable. How have you managed to keep it secure, private, compliant? I’m sure you guys have all of these challenges having to do that.

Dr. Maria Luisa Pineda
Data is a core piece of our company, Envisagenics. I think we’re very fortunate because we have Microsoft as one of our partners. I think Microsoft and other cloud service providers have done really well for us to have built our platforms with them, or while they were starting, they basically were really worked on

security and privacy and compliance. We frequently interact with the engineers and knowledgeable experts so we can assist with the growth.

But in reality, we focus on the science and building our platform and evaluating things in our lab while companies like Microsoft, AWS, and Google- all three of them have really focused on securing things on the cloud and having everything very compliant.

But, all the data that we analyze is de-identified. We have absolutely no data that could be tracked back. And even because of that, the platform is almost double de-identified because once it goes through our platform, we have different types of files that come out of that. Once it comes out of the specific SpliceCore outputs, those outputs cannot be back engineered and can only be analyzed or read by SpliceCore. That could be also put into different cloud service providers or partners. We can add it to people’s tech hub, or cloud, and if we need to analyze their data, we’re not moving it. When you have patient data, you don’t want to move it, store it or do anything with it for privacy. So what we do is that we bring our platform to that dataset. Our specific file outputs I was telling you about. Those data outputs is what we use for drug discovery and development. They don’t have to touch, move, or, do anything with anybody’s data.

We took that approach on the technical. It was a big bottleneck in the beginning, but working very closely with Microsoft and other cloud service providers, helped us to build our platform in the cloud with HPC, from the get-go. That has allowed us to focus on the science and leave all that data management for them.

Maria Palombini
That’s awesome. I hear this a lot now, too, with swarm AI and decentralized research, and it’s all about sharing of the insights, not so much the data.

Dr. Maria Luisa Pineda
There’s so much data out there, it’s what you do with the data that makes a difference.

Maria Palombini
Absolutely. So you’ve already shared some interesting outcomes from your work. What do you think are some of the greatest contributions you guys have had either towards the development of a targeted therapy or, the total amount of reduction of time in finding out particular insights that were not there before, or all of the above. What do you think has been some of your greatest contributions so far?

Dr. Maria Luisa Pineda
I’ve mentioned the triple-negative breast cancer using our SpliceCore platform and the downstream validations that come with it. But basically, we went from

data analysis of RNA sequencing all the way to a novel preclinic called Target and its compound in a matter of eight months.

So our platform can predict this optimal binding for RNA therapeutics. Our machine learning algorithm predicted five and two of them worked. To this date, scientists for RNA therapeutics, do something called microwalk where they go in one base at a time. So they manually test over 200 nucleotides upstream and downstream and two to three work. So imagine we’ve predicted five and synthesized five and two of those worked because we understand all the biology behind it. Each of those compounds is worth $3,000 to $5,000 to just synthesize it and a timeline to get it done in a matter of months or years and we just cut the cost so you can test a small fraction without having to waste all those resources on time.

That’s one of the things that deep learning and AI platforms like ours could definitely, you could see it right away, right? Just by the numbers.

Maria Palombini
That’s cool. That is really fascinating. Definitely helps expedite nearing that race, anything helps.

I hear this debate. There’s no such thing as precision medicine, or we have to move towards precision medicine, but I noticed something specifically when you talk about targeted drug discovery, you use these words very selectively. So I kind of want to get your input as like, what do you think is the difference and why is it better to more accurately look at therapeutics through that lens?

Dr. Maria Luisa Pineda
I think precision medicine is not very specific per se, where was targeted drug discovery. We at Envisagenics believe that if you find the right target for the specific indication or specific disease, then you understand you can stratify patients so it’s finding the right therapy for the right patients. That’s why we call it targeted because we find the target, we understand the mechanism of action, the biology behind it, and try to understand the disease itself and how the target is involved in the disease. Then we designed the chemistry against that target. So once we’re going into the clinic, then we can stratify the patients. We can understand what error we’re fixing on that patient population. And I think it’s more accurate; it’s a better term. It is the future of medicine.

We all have to be treated in a targeted way because cancer just means when the cell was bad. We all have the same genetic material, but there’s so many things that are involved in diseases, pathogenesis, right? If there’s so many things could go wrong, you really have to understand what’s going on wrong for each person. But if we could group those patients, then we can target them in groups instead of one by one. Precision medicine is one person and that takes a long time. But if you can group them, then we could target them by groups and stratify them and save more patients’ lives faster.

Maria Palombini
Absolutely. Very good point. I like to do this to all my guests. I call it the think fast question. So when I mention “AI for Good Medicine,” what is the first thing that comes to mind and why?

Dr. Maria Luisa Pineda
AI in biopharma has come so far. Eight years ago, let me just put it that way, we were starting to be invited to panels and there was the same five companies. Maybe 50 people in the room were talking and now, some of the AI panels that I’ve been, we have 2 to 5,000 people that are interested.

So the AI sector in biopharma industry has grown so much, and it’s such an essential part of this organization because we really have to use innovation to change. I mean, look at COVID the way that it happened, right? We use innovation, we use Biointech, they did such an amazing job, and everybody came together in a year to have a compound being tested in clinical trials, developing it, and all the pharma. AI was such an important part of this and it’s very promising. It will bring forward new therapeutics that we’re hoping to reach patients that are in big need and their families. So we can accelerate change and in a group effort really bring forward what has not been previously possible without traditional methods of just failing one by one.

Maria Palombini
Absolutely. One of my first podcasts for this season, we had a debate on whether the ethics of AI. It was all about, does it cause more healthcare disparity or actually close the gap? But in this case, with you, it’s more in the question of validating responsible use in AI for health applications. So you have the work in the science and now the tech side, what would you like the global healthcare community to know about these types of tools that perhaps they may not be aware or misled when it comes to potentially improving the patient’s health outcome?

Dr. Maria Luisa Pineda
I think AI, you really have to work together in order for you to use it the right way for the right means. For us, at least, is for drug discovery. So understanding from the patients what’s going on in developing therapeutics for them.

We created a global advocacy organization that is dedicated for the discovery and development and delivery of better solutions so we can improve patients’ lives. That is a coalition between technology developers, pharma companies,

research organizations like mine, universities and the US and European governments, and Canada. We put in together so we can realize the potential of AI and machine learning in healthcare.

How can we improve the quality of care? But addressing the industry challenges like publishing responsible, ethical, reasonable standards, how we’re developing policies, working with government, NGOs, key opinion leaders, and other international stakeholders. So we can have the premise or the promise of AI and how it works and how it can improve patient’s lives, but at the same time, making it efficient, sustainable, and creating an accessible healthcare system that is diverse. For instance, we all use data. We want to make sure that the data is coming from a diverse set of populations. We’re going through COVID, that happened, right? So, you know, minorities and underrepresented groups and women tend to not being part of those clinical trials so then we didn’t have a lot of data going in. So we always say, ” garbage in and garbage out.” So as data scientists and innovators in healthcare, we have to make sure that we have a wide variety of participants across the healthcare spectrum, as well as the diversity of data in patient population because diseases are global. They’re not one race. They’re affecting us anywhere in the world. That’s why you have to think about these issues globally, but make sure that they include us in the conversation. So when we’re standardizing, we were part of that as well as the government, pharma companies, and some of the academic institutions because they don’t have enough knowledge so combining everybody into one organization, like the Alliance for Artificial Intelligence in Healthcare, has allowed us to come together and set something up. So I want to make sure that everybody knows, I guess we’re working towards a healthier future, but all of us as a group. And I think that’s extremely important for our children and medicine in the future.

Maria Palombini
Absolutely. Really important to note that diseases don’t have a bias. You talked about so many great opportunities and insights. Talking to some of my guests, they always say that there was some single most challenging aspect when they

started or as they go through the process when they were using the applications of AI. It could have been lack of open data or there’s not enough standards developed, more policy, or it could be not enough computing power. And all of these things just seem to somehow fuel some concern or uncertainty or credibility and trust of these tools. So for you, what was it, or what could it be and why? And in your opinion, what would be the best way to resolve it?

Dr. Maria Luisa Pineda
So I’m the type of person that if it’s not there, you can create it. One of the co-founders of the AIH, or the Alliance of Artificial Intelligence in Healthcare, said if there’s no policies, then let’s get together. There’s no standards, let’s get together and figure them out, put them together with the government, with the regulatory institutions so we can get things done.

I was the vice chair for a year and a half and now I’m the secretary of the AIH. We really work together with my other AI in drug discovery or in healthcare companies and the pharma partners to really work on all of these challenges that we all face. It’s not only Envisagenics, all of us face the same thing. So grouping it and working together will help us apply it and resolve it. And then when it comes to, all the technology or a cloud or bottlenecks. Once you have a bottleneck, then you go and work with people that could help you solve it either government or providers.

But again, you need to have that proactiveness and that vision and be willing to work. Just because there’s challenges doesn’t mean that you shouldn’t do it actually it’s the opposite. If there’s challenges, they need to be resolved. If you don’t try to resolve them then who will. So I’m always trying to put a foot forward and be part of the change and try to resolve things as best as we can and bring the opinion leaders and the leaders on each of those fields so we can resolve it together.

Maria Palombini
Absolutely. I think it’s a very important approach. You all sharing the same challenges that are maybe blocking innovation or really not letting you open the doors the way you want to. So the best thing is to get together and figure it out.

I am familiar with the organization and I’m all for the great work that you guys are doing over there.

Dr. Maria Luisa Pineda
I appreciate it. It’s been two years and a half that we’ve been building it from scratch, but it’s definitely necessary not only to work together but also help each other and partner with each other.

Maria Palombini
Maria, you’ve given so many insights and so many thoughts today. Any final thoughts you would like to share with our audience? A call to action for any technologist considering getting into this space or is already in that area of health tech, but not really sure where they’re going with it.

Dr. Maria Luisa Pineda
I really want to say that if it was easy, everybody will do it. Just because it’s hard doesn’t mean that you shouldn’t. And so I’m always saying, just go for it. Ask for help, get mentored, get allies, get partners.

And by doing that and having the right team in place, you really can accomplish anything you want in life while having a balance and balance means very different things for people. I’m a mom, a wife, I’m a CEO and I couldn’t do anything if I didn’t have all the support from my mentors, from my team, from my husband, from my son.

Having that balance, whatever that means to you, will take you places that you will never imagine that you could.

Maria Palombini
Absolutely, it takes a tribe. I think that’s really important. So for all of you out there and make sure you have the right support system. I think it’s really important to achieve your goals.

Maria, thank you so much. I want to thank you for your time, but especially for the great work and making yourself available to talk with me today, I greatly appreciate it.

Dr. Maria Luisa Pineda
Well, thanks so much for the invite. I always love talking about all the work that we’re doing, the amazing science that my team is building. And again, it’s all for

the patients and their families, so we can get drugs and therapies available for them as soon as we can.

Maria Palombini
Absolutely. So for all of you out there, if you want to learn more about Envisagenics visit Envisagenics dot com.

Many of the concepts we talked about today with Maria are addressed in various activities here at the IEEE SA Healthcare and Life Science Practice. The mission of our practice is engaging multidisciplinary stakeholders and have them openly collaborate, build consensus, and develop solutions in an open standardized means to support innovation. And that’ll enable privacy security and equitable, sustainable access to quality care for all.

We have activities such as WAMIII, Wearables and Medical IoT Interoperability Intelligence, Transforming the Telehealth Paradigm, Decentralized Clinical Trials, Responsible Innovation of AI for the Life Sciences and a whole bunch more. If you’d like to learn more about these activities, they’re all open. Meaning you can just join. You don’t have to be a member or pay anything. And you want to contribute your expertise in solving a major challenge to open the doors to innovation, please visit ieeesa.io/hls.

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I want to do a special thanks to all of you, our audience for listening, continue to stay safe and well until next time.

Maria Palombini
Hello everyone! I am Maria Palombini, and I am Director and Lead of the Healthcare and Life Sciences practice here at the IEEE SA. And I’m also your host for the Re-think Health Podcast, Season 3: AI for Good Medicine.

The Healthcare Life Science practice is a platform for bringing multidisciplinary stakeholders from around the globe to collaborate, explore, and develop solutions that will drive responsible adoption of new technologies and applications leading to more security protection, and sustainable equitable access to quality of care for all individuals. Yes, this is an ambitious goal, but a much necessary one. The Re-think Health Podcast series seeks to bring awareness of these new technologies and applications with a balanced understanding in how to use them, how to be applied, and where potentially they may be need for policy standards or whatever it takes to drive more trusted and validated adoption to enable better health for all.

We have previous seasons available on Podbean, iTunes, or your favorite podcast provider. AI for Good Medicine Season 3 will bring a suite of multidisciplinary experts, technologists, clinicians, regulators, researchers, all with the goal to provide insights as how do we envision artificial intelligence or machine learning or any other deep learning technology, delivering good medicine for all? Naturally, we all want good medicine, but at what price? Especially, in terms of trust and validation and its use. So as healthcare industry stakeholders, we are not looking for the next frontier of medicine if it’s not pragmatic, responsible, and can be equitably valuable. So in this season, we go directly to all these experts and we try to get to the bottom of it and make real and trusted impact improving outcomes for patients anywhere from drug development to healthcare delivery.

So the question is: will AI, ML, deep learning cut-through the health data swamp for better health outcomes? With that, I would like to welcome Anthoula Lazaris, Scientist at the Research Institute of McGill University Health Center, and Nate Hayes, Founder and CEO of Modal Technology Corp. In this discussion, they’re going to talk to us about the third wave of AI for better patient outcomes and potentially realizing precision oncology. This is a fascinating case study. From the minute I heard about it, I was very excited about it, and I think it really shows how we can start to move the needle forward.

We are now on segment 1. We like to humanize the experience for our audience and we want to humanize the people behind the microphones. So a little bit about Anthoula. She has more than 26 years combined experience in academia, McGill University, biotechnology industry and management in senior-level positions with a demonstrated history of working in the hospital in the healthcare industry. She has been at the Research Institute of McGill University Health Center for a little over 11 years, focusing on bringing precision oncology to patients through clinical research projects.

Some of her career highlights include being part of the team making Nexia’s IPO, the largest public offering in life sciences in Canada, up to 2002. She was the first to demonstrate that a translation initiation factor can act as a proto-oncogene. The work was published in Nature.

And, Nate. He’s an entrepreneur, mathematician, and software developer who has been instrumental to the development of Modal Interval Arithmetic and served six years as a committee member of the IEEE 1788 Standard for Interval Arithmetic.

In addition to his executive leadership at Modal, he is Co-founder and board member of RISC AI, Inc.

So, Anthoula, Nate- welcome to Re-think Health.

Anthoula Lazaris
Thank you, Maria, for having us as well and giving us the ability to present our collaborative project.

Maria Palombini
Oh, this is very exciting. I’m so interested to get to the nuts and bolts of this interview.

Okay, so I’m going to start with you, Nate. Maybe you could share a little bit with us what is a ALIX, A-L-I-X and what is the fundamental difference between a third wave versus a second wave AI tool? I mean, we’re just getting onto AI and you’re talking third wave, so obviously you’re already light years in front of us.

Nathan Hayes
No, that’s a great question and maybe to provide a little context here, I’ll even rewind and go back to the beginning and give an overview of where things started in the first wave back in the 1970s to 1990s, kind of roughly is the time period of what we would call the first wave of AI. These early AI systems were very good at reasoning. You know, playing chess or checkers, for example, but they didn’t really have an ability to learn because the way that they were developed is typically humans would program these systems with a set of rules, like what are the rules for chess, for example. And then the computer could use those rules to reason about the chessboard and act as an artificial opponent, for example, in the game. Things evolved roughly in the timeframe of about the turn of the century here, 2000 to present, I think, most people would characterize or agree that we’re still primarily in the second wave of AI and the main distinction here between the first wave is that in the second wave, the machines have actually become good at learning. So they not only can reason, but they can actually learn how to do something.

Machine learning, for example, is looking at a pile of photographs and saying, is it a cat or is it a dog. The machine by analyzing a large test or a training dataset of images, it can actually learn how to interpret the images and then after the training is complete, you can put in new images that the computer wasn’t aware of or that it didn’t get the seed during the training time, and it will then predict. It’ll say, oh, I think this is a cat or I think this is a dog.

So fundamental to this concept is you’ve got a training process for the second wave machine learning or artificial intelligence and in that training process, you’re analyzing very large sets of data so that the machine can find patterns in the data and it can learn. And then after the training process is finished, then you have deployment out into the field and the machine will then, what we call inference, or make predictions based on the results of the training process.

And from a mathematical perspective, what’s really going on here is this learning process is a very complicated non-linear global optimization problem. So that is the main characteristic of how these machines learn under the hood in a mathematical perspective. And the other characteristic that I think really defines the second wave that we’re currently in is that when the current algorithms and the current computers and methods that are used to solve this optimization problem are primarily statistical in nature.

The reason this is important to understand is that since everything is statistical, and confidence can only be measured for example, in terms of probabilities, you’re never really completely sure exactly where you stand in terms of how well of a job you’ve done with the machine. And in that sense, a lot of people have talked about using these second wave tools that it’s like working with a black box.

So as we talk about entering the third wave, the primary difference here from the second wave AI is that in the third wave, the machines become excellent at learning. And in addition to that, the machines begin to provide explanations. We’re overcoming that black box capability and we’re providing a more clear and concise and intuitive answers to the humans that are trying to work with the AI in terms of understanding how the machine goes about making certain decisions or predictions.

So this is what is very broadly called explainable AI since it’s kind of a new concept, there’s really a lot of different definitions and a lot of different groups that are starting to work in the third wave may have different definitions of what explainable means, but explainable AI from our perspective means that because of this new approach that we are using with the ALIX training method, which is built on this Modal Interval Arithmetic and it’s a completely different algorithm or method, if you will, than anything else that’s currently out there. The thing that is different is it’s not a statistical approach to training or solving that optimization problem. And so in that regard, we’re getting rid of all of these probabilities. We’re providing guarantees and repeatable results and answers through this process and through this unique capability, we’re also opening up that black box and providing a guaranteed view or answer to how did the machine, for example, arrive at this particular conclusion in terms of making a prediction that a picture contains a cat versus a dog or if in terms of healthcare, what we’re talking about today, is a patient healthy or they have a particular diseases.

Maria Palombini
Great, Nate. Thank you. Anthoula. Obviously Nate set the foundation for us on the technology. You know, we talk to a lot of clinicians and researchers and sometimes they’re like, oh, I don’t know about this AI thing when we’re talking about research. Can you give us a little insight about the case study, what you were going for in your research, and then at the end of the day, why you chose to move forward with a cutting edge AI tool, such as ALIX for this precision oncology research.

Anthoula Lazaris
When we talk about precision oncology, we’re talking about not treating just the disease, but treating the patient who has the disease. So really identifying unique features within that patient’s cancer. As we identify these unique features in the cancer, new technologies have evolved. For example, liquid biopsies, we hear about liquid biopsies.

This is what we’re doing here is we no longer need a sample of the tissue from the patient, which is very invasive. Instead we’re using a liquid form in terms of it could be blood, urine, saliva are just three examples. So with respect to the project that we have with Nate and where we started it. So with a basis, looking at precision oncology, really trying to focus on individual patient care and applying liquid biology, which is really in our case, looking at components within the blood that are either shed by or changed by the cancer.

The work that we do in our lab is focusing on colorectal cancer liver metastasis. We looked at the tissue and we identified markers that could predict a patient’s response to treatment, but we literally need tissue for this, which is not always practical when it comes to getting biopsies from patients. So the starting point of this project is we already had some predefined specific features within the tissue that we now said, well, let’s go into a liquid biopsy and see if we can identify these features in the blood and in essence, identify which patients will respond to treatment and which patients will not respond to treatment. And for this in the blood specifically, you hear a lot about circulating tumor DNA, where they’re looking at genetics. We took a different approach. We’re looking at these vesicles that are secreted by multiple different cell types and we looked at the proteins within these vesicles. So the starting point, the large amount of data we collected was vast amount of proteins from mass spectrometry data on the blood of two different populations of patients, those that do respond to current treatment and those that did not respond.

When we first met Nate, which actually was brought to our team from our business development office. So, as you can see, there’s a lot of multidisciplinary going on here. He presented ALIX to our team and we were really surprised that this type of analysis program, you call it third wave, actually existed. And at the time, Nate just referred to the basic bioinformatics tools, which really rely on statistical significance.

That’s a key feature here, I believe, because when we talk about statistical significance, so we pulled out based on our tissue and even looking at the blood proteins, we use bioinformatic tools on all the proteins we’ve pulled out of the blood. And we found over 50 proteins that looked like they were different between the two patient populations. But we had no idea which ones were important, which ones were not important. We couldn’t rank them to identify. So we’re screening now looking at 50 different proteins, which is very time consuming. So we were intrigued that ALIX could actually develop a signature for us. And also rank the signature and the biomarker found in the blood according to importance in answering our question, what will lead to a patient not responding to treatment versus a patient responding to treatment.

Maria Palombini
That’s fascinating. So much going on in the world of oncology research and to start to get at that level is critical, but really just amazing.

Anthoula Lazaris
First of all, we were surprised from the start in terms of what Nate and his team had developed in terms of, I wouldn’t even call it a software, I’d call it ALIX. So ALIX is our friend. The main outcome is we generated a signature that was able to tell us which patients would respond to disease, which patients will not respond to disease. And importantly, like I said, it was able to rank them as relevant and irrelevant.

The other thing that came to our attention was the way ALIX worked. So I’m a molecular cell biologist. I am not a mathematician or an AI person. What I had to understand from the beginning is that ALIX is driven by a multiplex analysis. We’re not looking here at identifying individual biomarkers. So it had to be clear from the beginning when we were first discussing with Nate and his team that we’re not looking at an individual biomarker, we’re not looking for a target for new drug here. That was not the goal of the project and we had to keep our focus like that.

Once we saw the signature, we said, okay, let’s apply our biological knowledge and look at different pathways and see what pathways are up or down regulated. It wasn’t that simple. Applying the biology to ALIX’s signature was novel.

It’s one thing to find a solution, i.e. the signature. It’s another thing to actually understand the solution. So we only had half the battle won at this point. So what we eventually through repetitive meetings and discussions with Nate, and I think that’s, what’s really important in this type of collaboration is Nate comes at it with his mathematical background and AI background. We were able to communicate, we’re able to understand each other’s languages. Whereas I was coming more from a biological sciences background, but through discussions, we were able to realize that ALIX’s solution was really telling us a whole body’s response to the disease. So it’s not just the tumor itself, tumor cells in the blood that people often find, et cetera. We’re not looking at that. What ALIX has identified for us is the body’s physiological response to the cancer. This is new. We had to figure out ways of trying to understand. So how do we now look at the whole body as a whole to understand what the signature means?

In essence, we had two major findings. One is we’ve developed a signature, which we will now move on to try to bring it into clinical practice. But again, that’s longterm still. And second is understanding what the solution ALIX is providing and how we could use that to better understand the physiology of the human body.

Maria Palombini
Wow, it’s unbelievable. I think that’s just amazing. I guess that’s when they say when you’re putting data to good work. One of the benefits of having both the technologist and the researcher on these kinds of interviews is that you can get both perspectives at the same time. So first I’ll start with you, Nate.

ALIX is scalable in performance and infrastructure like you mentioned, and is proven in software in this particular use case. But how can it successfully classify health versus disease patient and identify those biomarkers and those nuances that, Anthoula just came out and shared with us?

Nathan Hayes
Yeah, it’s a really good question and it goes back to what I was mentioning earlier in regards to, the training process versus the inferencing process. The McGill use case that we did with Anthoula, we analyze the data, using a method called K folds, which is basically where you take all of the data you have available and you basically partition it into K different folds where K could equal 5 or 10 or whatever number.

And the idea is that you set aside some of those folds or testing data and the rest of the data is used to train the system. And then after you’ve performed that training, then you set aside a different set of the folds for testing, and then you train again. And so this is a way of training the system, measuring capabilities in the field.

What we realized in this particular use case is that every time every single fold that we did, the training was always a hundred percent. And that was really important because therein lies the evidence of the hypothesis that, Anthoula and the researchers have that there really is a pattern in the data here that ALIX, because of the guarantees that it provides mathematically, based on the unique way that it finds solutions. It’s a proof performed inside the computer of the training solution. And so that is important to let the researchers know that they’re on the right path here, that there’s validation to their thought process. But in addition to that, the one other thing Anthoula mentioned is the ranking of the biomarkers and because of the Modal Interval Arithmetic method that we use with ALIX to solve the training as a by-product or as an outcome of those trainings with the ALIX software or method, we had a ranking of all the different proteins and, we analyzed thousands of proteins and out of all of those proteins, ALIX was able to rank them from the most important to the least important so that we could create a pie chart or a graph that we could provide with the researchers and actually identify by name what were the relative importance of all of these different proteins. And this again is all happening in a non-statistical manner. Basically, it’s a computational proof done inside the computer based on set theory that based on the data and the model that we created, this is the result.

Even though we still have work to do in terms of broaden the database of samples to improve the overall test accuracy of ALIX out in the field and we believe that’s going to improve with time. One of the things that we demonstrated with the K folds testing is that the ranking of the biomarkers did not change hardly at all, between all of the different folds. And so in that sense, you have a high degree of confidence that this list of biomarkers or that signature that Anthoula was talking about is not going to change even as the size of the training database grows over time.

Maria Palombini
It’s just amazing what this technology can do.

Anthoula Lazaris
You can just add to that. So the ranking in science is I can’t stress how important that is, but, ALIX also identified irrelevant protein markers. So you figured, okay. That’s the garbage, it’s not because when we talk about validation, like in a trial and you’re going across multiple different sites, different countries- how do you normalize your data? And that is a major issue in any type of clinical tool you’re going to develop, is normalization. So we haven’t yet finalized this, but we’re exploring with Nate, these irrelevant proteins that do not change between our patient samples. Could we use those to normalize data across sites?

So there’s a plethora of information that we’re still trying to understand in ALIX’s solution.

Maria Palombini
That’s amazing. I think, next time, if ALIX can talk, we should invite him to come to the conversation as well.

All right. I tend to do this to my guests. I’d like them to think quick and have a short, quick answer. So we’ll do this one at a time. So Anthoula, I’ll start with you. When I use the term, or I say the words, “AI for Good Medicine,” what’s the first thing that comes to mind and why?

Anthoula Lazaris
For me, good medicine, just first of all, is meaning improve patient care. So AI for improved patient care to mean means tools or technologies that support patient care.

Maria Palombini
That’s how I envision it as well. Nate, how about you?

Nathan Hayes
For me, I come at it from a little bit different of a perspective and that’s due mainly to my background as the technologist and the mathematician. But to me, the one word is ethics and using the AI in a responsible manner.

Maria Palombini
Absolutely. That’s leading into my next question for Anthoula. You touched on a little bit on this term validation but we often hear about ethics in AI and machine learning for healthcare, and it’s being used in multiple different ways and things, but given your experience now with this particular use case and having to use the application and seeing some of the outcomes and opportunities with it, what would you like to share with the global healthcare community about using these kinds of tools like AI or machine learning that perhaps they may not be aware or even misled when it comes to potentially having real impact in improving patient outcomes?

Anthoula Lazaris
When we look at the ethics component, there’s two things.

There’s data from the patient protecting the patient’s data. And there’s also ethical bias in terms of different patient populations. If we look at data protection in order for us to do the work that we just talked about today with Nate is on our side, on the hospital side. And on the resource side, we had to have ethics protocol to collect the data, but our ethics board and our protocols are very clear.

Any information I provide Nate or I put into any bioinformatics or AI software or technology, they cannot contain any identifiers. These are very well-defined in the ethics community- a date of birth, a day of surgery, names, of course, by far are completely out of this. And all of our data is actually double-coated.

You may ask why don’t you just anonymize? If you want to follow up on these patients to see if you find something interesting. If they’re anonymized, that means you can never go back to follow up on these patients. If they’re double-coated though, and this comes down to another ethics issue is if they’re double-coated and you identify for example, a disease that was maybe a susceptibility to Parkinson’s, et cetera, there are in your ethics protocol and in the consent of this patient there’s procedures put in place that you can actually go back to the patient’s doctor and let the doctor make that decision. That’s just a small example of one of the components that’s embedded in ethics. Our ethics in Canada, I can speak for, and specifically in Quebec, Quebec is actually more restrictive than the rest of Canada. It really protects the patient’s information and I think the patients need to be aware of that, but we can’t overprotect and not be able to go back to the patient to provide their doctors valuable information either. So we have to be aware that we still need to have that openness to go back to the patient when we need to.

With respect to bias, we work in colorectal cancer liver mats, by far it used to always be more male dominating in the older age groups. Unfortunately now with an increase in obesity, we’re seeing a shift in the younger population, but when we do select our patients like you do for a clinical trial, you are biasing your study based on who you know will benefit.

But I think what’s important is like you do in a clinical trial, you need to very, well-define your patient cohorts, the data you’re putting into it. So you already know that it’s going to be biased in what the bias implies. From my perspective, that’s the main two ethical issues.

Maria Palombini
Yes, very important. In blockchain, the quality of what you put in is the quality of what you’re going to get out. It’s almost the same concept and I think it’s really important.

We talk to technologists, they all have a whole array of things that comes to mind when it comes to a challenging aspect or gap that they’re finding in really driving the trust, the adoption, the mainstream acceptance, whatever you want to call it, you know, for the use of the technology in these applications. I guess my question to you is if you had to think of the single most challenging one that’s currently maybe not addressed in current discussions around AI or maybe just keeps getting pushed to the side, creating that little bit of uncertainty on credibility or trust in the tools, what would it be? And in your opinion, what may be one of the best ways to try to resolve it?

Nathan Hayes
Very good question. From a technology perspective, I think the main issue there is about leaving this paradigm of statistical probability behind into the third wave with ALIX and the guaranteed outcomes. But I think more broadly, even in a non-technical manner, I think the most important issue, there is something that Anthoula already touched on a little bit earlier, and that is the interdisciplinary nature that’s required for these programs and I think successful outcomes.

In my own personal view, this is one of the reasons our collaboration with McGill has been so successful is because of the way that our teams have worked together. Bringing our respective areas of domain expertise to the table through dialogue and discussion, being able to overcome the language barriers, so that we can really understand where each other’s coming from.

So we can really understand the medical hypothesis so that we can translate that into a machine learning hypothesis. So that we can take the machine learning results and translate that back into the domain of the medicine and the healthcare. It seems obvious, but the reason I point this out and answer it is because we do actually run into a lot of other scenarios, use cases, people just throw the data over the wall, kind of mentality.

And I think some of that’s just because these domains of technology and medicine are so far apart, it can be a daunting task to overcome that gap. But I think that there’s a lot of that going on. I get worried and concerned about that sometimes in terms of how is that really affecting the work and the quality of the results that are being arrived at using these techniques or methods?

Maria Palombini
Definitely something to think about. You both have shared such tremendous insight today. Any final thoughts that you would like to share with our audience, a call to action or something to get involved or take the extra step, whatever it might be in this pursuit of using these types of technologies to really start making an important impact in the area of precision oncology and research and that kind of thing?

Anthoula Lazaris
First and foremost communication, communication, communication. Like Nate just mentioned being able to understand each other’s language when you don’t know something, say you don’t know it and bring in others to help support you. I think that’s one key thing. And like Nate said, I think that’s why we’ve succeeded in what we’re doing so far.

And a quote. I can’t remember who said it, but basically it’s not enough to just do our best, but we need to know what to work on. With this specific example, we had one question, one hypothesis, and we got a solution. I find in science sometimes people are over-ambitious. They say, wow, ALIX is amazing.

They’ll try to feed it a whole bunch of data, but you need to stay focused and you need to have a simple question. Like Maria, you said at the beginning, we want pragmatic to be pragmatic. We want to be able to allow our patients to receive these solutions. In order to be pragmatic, we need to ask simple questions.

Maria Palombini
Very good point. And Nate, how about you?

Nathan Hayes
I would really like to just follow on that and add my second to it. It’s just so important to emphasize. I really do believe it is the most important thing to end on here that as exciting as all of these technologies are particularly ALIX and the new capabilities that it brings to the table, the machine learning and the AI, it is still just a tool. Everything in terms of the quality of the outcomes, the ethical nature really depends on the humans that are using the technology and how they work together.

Maria Palombini
That’s fascinating and very good parting points for our audience.

Many of the concepts that we’ve talked about today with Anthoula and Nate are currently being addressed in various activities here, IEEE SA Healthcare and Life Science practice. We cover a lot of areas of blockchain, AI, quantum, forward-thinking in mobile healthcare, telemedicine, whatever it takes to improve the patient outcomes across the healthcare value chain.

So we will include the links to Modal Technology Corp and the Research Institute at McGill University on the blog posts that’ll be accompanying this podcast. You can learn more about these respective organizations and the great work they’re doing.

Please check out the Healthcare and Life Science practice website at ieeesa.io/hls. We’ll have all the information about the different incubator programs we’re doing. They’re open for everyone to participate and to help us contribute towards global solutions to try to drive responsible and validated adoption of these technologies. I ask all of you to please, if you liked this podcast, please share it on your networks and actually use hashtag #IEEEHLS, or you could tag me Maria Palombini or the IEEE Standards Association. So we can give everyone access to this great information and this awesome case study. We want to get it out there and make everybody aware of what’s going on. I want to say a special thank you to Nate and Anthoula for joining us today. Nate and Anthoula, thank you. This was so great.

Nathan Hayes
Thank you.

Anthoula Lazaris
You also for having us.

Maria Palombini
Pleasure. And to all of you in the audience. Thank you for joining us. I want to continue to wish you to stay safe and well, and please keep tuning in as we bring the bright minds, such as the ones we’ve had today to keep sharing these great insights with me and with all of you. Until then take care.

Maria Palombini
Hello everyone! I am Maria Palombini, and I’m with the IEEE Healthcare & Life Sciences Practice. Today, we’re kicking off Season 3 of the Re-Think Health Podcast Series. Season 3, will focus on AI for Good Medicine. So a little bit about the Re-Think Health Podcast Series. We talk to multidisciplinary experts around the world, focused on various themes and topics, and we want to bring awareness and balance understanding in all these new technologies, tools, and applications, where we may need some policies or standards, all in the name of driving responsible, trusted adoption to give better health for all. We have previous seasons on Podbean, iTunes, and you can learn more.

So AI for Good Medicine, which is the focus of our theme on this Season 3, will bring again more multidisciplinary experts from around the globe to really answer or provide insight into questions is how do we invision Artificial Intelligence, Machine Learning or other deep learning technologies to deliver good medicine for all, right?

We all want good medicine, but at what price? Price, meaning in terms of trust and validation in its use. We are not looking for the next frontier of medicine if it’s not pragmatic, if it’s not responsible and can be equitably valuable to all. So in this season, we go directly to the technologists, clinicians, researchers, ethicists, regulators, and others, and talk about how these deep learning technologies can make real and trusted impact on improving outcomes for patients anywhere from drug development to healthcare delivery.

Here’s the question. Will the AI, the Machine Learning, the deep learning cut through the health data swamp for better health outcomes? So with that, I would like to welcome Sampath Veeraraghavan to our discussion on the true potential of AI in healthcare and helping marginalized populations. This has become a critical topic for debate, and he’s going to be helping this with us.

Welcome Sampath.

Sampath Veeraraghavan
Hey Maria, wonderful to join you all here on this podcast.

Maria Palombini
Thank you so much. So before we get to the details of the technology, the applications, the debate at hand, I like to humanize the experience. So a little bit about Sampath. He’s the Global Chair at the IEEE Humanitarian Activities Committee, or sometimes here we call it the HAC. He’s President Elect for IEEE Eta Kappa Nu and the 2020 recipient of the IEEE Ted Hissey Outstanding Young Professionals Award. He has more than 17 years of research and industrial experience in spearheading business critical strategic R&D programs and has successfully delivered cutting-edge technologies in areas of conversational Artificial Intelligence, natural language understanding, cloud computing, assistive and sustainable technologies. He’s globally best known for his technological innovations in addressing global humanitarian and sustainable development challenges. And this is why he is the first person and the most important person to talk to about this critical debate. First of all, Sampath, tell us about your work and objectives at the IEEE HAC and now with this new thing coming up with Eta Kappa Nu.

Sampath Veeraraghavan
Thank you Maria. First, as the Global Chair of IEEE Humanitarian Activities Committee, also called as, HAC, I lead the overall strategy and the portfolio of global programs, primarily focused on inspiring, connecting, and engaging close to half a million IEEE members. So they can take and apply the technical skills for social good.

We primarily focus on four major strategic areas as part of our work. The first one is raising awareness for technologists on how you can put the technical skills for addressing the grand challenges in the sustainable development space. Second, we provide the educational materials and training so that IEEE members could advance their skills for social good engagement. Third, we also provide project funding program so that we could actually empower our members transform their ideas into actionable projects, which could address the local challenges.

And lastly, we want to foster a global ecosystem to bring together technologists, local community, and partners so that we could address pressing global challenges. And our efforts strongly aligns with IEEE’s core mission and are critical to achieving IEEE’s strategic goals. And in fact, in 2021, I know I was very delighted to spearhead the HAC to a record breaking group.

Since its inception where we achieved a record of more than 25,000 site members and we received close to 385 projects globally and supported close to a hundred projects and we established 30 plus global partnerships and launched key programs- IEEE HAC Global Summit, positioning IEEE as leader in the sustainable development space.

Speaking about IEEE Eta Kappa Nu, it’s one of the world’s oldest, top-most honors society in science and engineering. And about 10 years back, it was merged with IEEE and it has about close to 200,000 life members throughout the world. And it has more than 200 chapters around the world. Many pioneers in the technology industry are part of Eta Kappa Nu.

So really excited to lead this true, true global impact program that has a true impact at our members at grassroots.

Maria Palombini
Absolutely. I know you’ve been doing great work at the HAC and, I’ve talked to other volunteers who work with you. They’re super excited and obviously great overall for our organization globally.

You know, Sampath, you have such a diverse background, so much research technology. What inspired you? What ignited your passion to really look into where technology can be used for good?

Sampath Veeraraghavan
Thank you, Maria. That’s a very important question. In fact, to answer this question, I have to do a time travel. I have to go back almost 18 years, back in my journey/career. So my journey actually started as a student in India, where I leveraged computing technologies to design an automated screening system to detect development delays in children. Basically this effort, that opened up critical opportunities to initiate early intervention programs, to treat children with special needs like autism, benefiting families below the poverty line in Southern India.

This, I think, was a very major stepping stone in terms of my inspiration because this program helped me to directly connect with the marginalized population, see how I could, as a technologist, come back with an appropriate, relevant and low-cost solution to address their needs. So the success of this effort made me realize how it is very important for technologists, especially like engineers and IEEE members, to apply your technical skills and leadership skills for social good.

This further ignited my passion and inspired me to start the humanitarian engineering program called as Brahmam, meaning knowledge. Which aims to deliver next generation social innovations to serve the needs of marginalized communities. This has been a very amazing journey in the last 17 to 18 years, where I have launched several global initiatives that are brought to the academic institution, industry leaders, our professional organizations, and governmental agencies to address pressing global challenges faced by children with disabilities, impoverished women, and students from marginalized communities in developing nations.

Maria Palombini
Wow. That’s such great work and such important work. And I could see how it’s carried you all the way to what you’re doing now. Now we’re going to get a little more deeper into the technology and to the discussion around this concept of AI for Good Medicine and for the audience out there. When I say AI, I’m not exclusively talking about artificial intelligence, but the whole realm of machine learning, deep learning technologies in AI.

So, Sampath, maybe you can just explain a little bit to our audience, the kind of research exposure or hands-on tech development that you’ve had around these types of technologies in health applications that you may have experienced firsthand.

Sampath Veeraraghavan
Thank you, Maria. That’s a great question. So throughout my career, I have spearheaded large-scale transformational AI programs in healthcare. Before I touch upon some examples, it’s important to understand some of the AI core capabilities like machine learning, computer vision, natural language understanding, and speech recognition. All of these capabilities offers new approaches to solve the toughest challenges in healthcare. For instance, machine learning techniques like deep learning, it offers the powerful capability to create sophisticated models that can be leveraged for a wide variety of healthcare use cases, prediction, forecasting, classification, so forth. Similarly, computer vision techniques, it processes the visual information in detail, in images and videos to generate valuable influences.

If you leverage the AI model along with these advanced techniques, it helps us to create solutions and tools that can assist medical practitioners to examine clinical images, identify hidden patterns of tumors and which in turn supports the expidited decision-making and delivering an effective plan for patients. Specifically as part of my career journey, there are two major programs I would like to call out.

I lead a major initiative called as Information Systems on Human and Health Services. Essentially, this is a first of its kind system, which was focused on tracking the statewide visibility in Southern India.

What we did was we collected all the statewide permissions. We leveraged machine learning techniques to process the massive amount of data and interconnected the underlying patterns, and very meaningful insights to support decision-making. And this in turn empowered the healthcare providers, policymakers, governmental agencies, and disabled individuals to understand the disability prevalence pattern and initiate prevention measures. And also it helps them to better understand the needs of disabled citizens and facilitated the creation of equal opportunities for them, both in terms of education and employment.

The second major project I would like to call out here is on the Conversational AI Spectrum. Recently I was involved in delivering one of the industry’s first programs in conversational AI technologies to advance voice innovations for the healthcare industry. So the idea here is we wanted to expand the conversational AI capabilities so that we could support healthcare use cases like prescription ordering and urgent care appointments. Again, all this AI core capability, what we touched upon, it all offers a very unique and universal approach in opening up critical opportunities to further drive AI innovation in the enterprise healthcare segment, actually.

Maria Palombini
That’s fascinating, Sampath. I think that’s so much great work you continue to demonstrate. It’s unbelievable and great for all of humanity. I like to do this with my interviewees. I say to them think quick. So when I say to you, or you hear the term “AI for Good Medicine,” what comes to mind and why?

Sampath Veeraraghavan
Thank you, Maria. AI can be used to handle some of the greatest challenges in the healthcare segment. When we talk about AI for Good Medicine, few things come to my mind. One is how do you creatively use machine learning models to leverage and handle voluminous amount of medical data and uncover insights to help improve health outcomes and patient experiences. Specifically, there are a couple of areas that come to my mind where I feel creatively, we could play an important role to solve some key challenges.

First, how do we accelerate medical researchers to advance the prevention, diagnosis, and treatment of diseases, right? And increasingly AI models becomes important in this segment where we are empowering healthcare providers with right tools. Today, the doctors don’t have to scan through thousands of CT majors. They rather could use an automated AI system to help them to identify the most important ones so that they could expedite their decision-making. Similarly, the second important area that comes to my mind is reducing the health inequity and improving access to care for underserved population. This is important because, as you see, 50% are not connected to the internet. So the goal is how do we devise solutions, which can work both real time and offline? At the same time, provides a robust approach to simplify the access to health care and also to provide a critical opportunity to bring these people to the mainstream healthcare services.

Thirdly, AI today is vital. You rightly said we need to think about innovations in patient-centered innovations. We are no longer in the age of mass production. We are living in the age of mass personalization. So I think when we talk about AI for Good Medicine, this is also key because today the AI is empowering the healthcare providers to see if there’s a rare condition. It helps them to closely understand what are the other similar patterns they have seen in other patients and helps them to customize based on the genetic condition how they could help the current patient.

And lastly, it’s also important that we have ethical and responsible use of AI to save all patient’s privacy. So these are some broader, a couple of things that comes to my mind, but I think the most important thing is, as I said, the ability to handle voluminous amount of data that transforms the opportunity to provide low-cost solutions. I think that’s going to be key in terms of achieving and supporting the overall good, wellbeing of the larger community.

Maria Palombini
Absolutely. I think that AI has a lot of promising opportunities, but we’re going to get a little bit into maybe its challenges in just a little bit.

This is the core of our discussion with them about technology for good and equitable access. So, I’ve heard the argument that perhaps AI machine learning can support fairness, personalization, and inclusiveness in healthcare helping to address the healthcare inequity question. In your opinion, in all the work you’re doing, do you find that AI can actually help address the racial, gender, and socioeconomic disparities in healthcare systems? Or, like some have argued, that it further creates more inequity in the healthcare system.

Sampath Veeraraghavan
Thank you, Maria. It’s a challenging question. I think the potential of AI and the challenges of AI are equally big in my view. So the answer is yes/yes to both, actually. Let’s first look at some of the potential. What are the possibilities, right?

Now, if you look at the super power of these AI systems, they can look through large amounts of data and it can help us to surface the right information or the right prediction at the right level to the right stakeholder. This is going to be very important because now with the advancements in cloud computing, and capabilities like a deep learning models, it’s going to help us to drive the next frontiers of innovation that will empower healthcare stakeholders with tools to compare patient cases to every other patient who ever had the same kind of disease or pattern. It results in a data-driven approach to identify the most effective treatment. And that’s one best-suited for the specific genetic subtype of the disease in someone with a certain genetic background.

That’s truly personalized medicine. That’s truly a personalized approach in digital healthcare and the prognosis should also be good, actually. And now, if you think from the same angle, this can also empower people living in poor settings. We can leverage automated chatbots that potentially could help us to screen for some symptoms, so that it can reduce the burden of the medical teams in those setups, actually. So there’s a ton of super power and possibilities here, how AI could actually help to address the racial, gender, and socioeconomic disparity in healthcare systems.

With that said it also comes with its own potential risk. For instance, a poorly designed a system can be misdiagnosed, right? And that’s going to be a trust-breaker and the impact is going to be even more larger. And similarly, remember these systems are heavily dependent on data upon which they are trained on. So that means if there is a cultural bias within this dataset that, unfortunately, will be incorporated into the system and those blind spots will be integrated into the environment where they’re deployed. One of the challenges I also see here as certain problems, you also require high quality data where you could actually can get a very robust AI model. If that data, which you used is, again, biased or otherwise flawed, it’s going to be reflected in the performance of your system.

And lastly, we spoke only about the data, but also remember the AI system also has something called as algorithms. So if the developer is unaware of the unintentional bias and introduces that bias in this programmatic logic, that’s also going to maximize discrimination.

So that’s why it’s important that technologists looking at developing AI-based solutions, you have to make sure that you proactively have measures in place where you have to maximize your impact and minimize the risk in terms of disparity creation. So I think the answer is, AI has tremendous potential, but also it comes with this risk. So it’s very important that we put controls in place to limit the negative impact of technology.

Maria Palombini
Absolutely. And you just basically answered by next question. You just jumped in front of it. I think that everything goes hand in hand. We can’t just think about benefits and opportunities of anything without thinking of the challenges that comes with it.

When you think of this whole thing, right? All these, this technology groundbreaking, that kind of thing- what’s the single most challenging aspect or gap? By gap, it could be security, lack of open data, lack of standards, not the right policy written, whatever that might be is currently not in AI applications or deep learning or machine learning, what have you, that continues to cause concern or uncertainty in credibility and trust of tools in this healthcare application? In your opinion, what is it? What could it be? Or I’m sure there’s more than one , maybe. And where do you think is the best path in resolving it?

Sampath Veeraraghavan
Thank you, Maria. It’s an important question, but again, there are several pieces that’s integrated here. You have rightly called out several dimensions here, right? Security, privacy, open data, lack of standards. So if you have to answer this question, I think I’m going to take one step back and give you a holistic dimension.

First of all, it’s very important to understand that AI is not a “one size fits all” approach. So I think it’s important for the global community to know that AI solutions are here to supplement. To reduce the pain point experienced with stakeholders in healthcare. It’s also critical to understand that these systems adapt over time because you are not deploying an algorithm in vacuum. You are actually deploying a technology, which is going to be part of an environment, but people will track with it and the system will adapt to it. For instance, if it designed some kind of scoring system today to rank a medical device or a solution it’s going to change, actually. So in my view, I think the key important challenge right now is we need to actually create a global ecosystem where we bring together policymakers, technologists, the local communities, and healthcare professionals, to holistically work together, to define standards along the lines of security, privacy, open data access, and so forth. We need to develop cost-effective AI models and products that can empower physicians and practices and hospitals to incorporate AI into daily clinical use. I think we should make sure there’s awareness and there’s also from technology standpoint, we are working from patient-centered innovations so that AI is seen as a complimentary technology to empower them rather than being seen as human machines.

There are also a few important things we need to do as part of this ecosystem. For example, the responsible use of AI. This can be achieved by enforcing standards and best practices to implement fairness, inclusiveness, security, and privacy controls. A few examples here is you could always check as a technologist, whether your models and datasets for bias and negative experiences. And there are several techniques in the industry like data visualization and clustering, which can evaluate the datasets distribution for fair representation of various stakeholders dimensions.

Secondly, you can also do routine updates to your training and testing datasets, which are essential to fairly account for diversity in users’ growing needs and usage pattern. And of course, they’ve got the sensitive user information for their patients which need privacy controls, like encrypting data at rest or in transmit.

So by doing all those things and also having a retention policy in place, you’re kind of making sure that you’re not only doing the right thing and you’re also working backwards, by focusing more on what the patients want and what the doctor needs and devise solutions, which are truly specific, relevant, actionable, and impactful.

So in a nutshell, we need a global ecosystem. At the same time, this ecosystem should provide standards and framework, which will enable us to develop universal solutions which can be easily developed and deployed whether it’s a developing nation or in an underdeveloped nation set up. I think we really need to have good quality data, high quality standards, and an interoperable framework where technologists can develop plug and play solutions, which can help us to support large scale and easily deployable solutions.

Maria Palombini
Wow. That’s very important. I think the idea of the plug and play and interoperability and all this- there’s so many questions and challenges around all these technologies. Something to have our audience take away with. You’ve already shared so much insight, so many great ideas and opportunities and things to think about.

Any final thoughts that you’d like to share with our audience- a call to action, something that they should look into, an opportunity that may be of interest to them of getting involved?

Sampath Veeraraghavan
I think the one important out here is first of all, huge kudos to IEEE Standards and to you for starting this podcast, because the timing of this podcast series and the thematic areas is very important given that we are still trying to come out of the pandemic situation.

Now, in terms of the final thought, I think AI tools has played a very tremendous role, especially in the pandemic situation, like COVID. Many places throughout the world help us to deliver solutions to track the pandemic, forecast the demand and supply, helping the local governmental agencies and healthcare.

There are two aspects to it, right? One, I think as a technologist, how you can advance these innovations in AI and second, most important thing is what does your local community need? I think it’s very important when the need and the technology meets that actually decides the bigger innovation.

And that’s where IEEE comes into play, they provide a tremendous amount of opportunity. For example, IEEE Humanitarian Activities Committee, as I told you earlier, we provide a portfolio of programs for you to participate, particularly with technical skills for social good. So definitely participate in these programs.

And again, IEEE Standards is an important program. Most recently we have launched Patient-centered Healthcare System Virtual Pitch Competition, which is also very important. You are able to mentor and guide these teams, I think that’s also a way for you to give back to the society.

I think I’m going to quote here, Leonardo da Vinci, the famous quote: “I have been impressed with the urgency of doing. Knowing is not enough; we must apply. Being willing is not enough; we must do.”

So I think we need to build inclusive and prosperous futures for everyone. I think it’s important, as a technologist, we all should look for an avenue to apply our technical and leadership skills for the larger good, so that we can collectively advance technology for the benefit of humanity.

Maria Palombini
If you want to learn more about the IEEE Humanitarian Activities Committee, you can visit hac.ieee.org. If you didn’t get that, you can visit the blog posts. We have links to activities Sampath is affiliated with plus other activities. In addition, just to let you all know that Sampath served as Advisory Committee Member and a Judge on the recent IEEE Re-think the Machine: Transforming RPM into a Patient-centered Healthcare System Virtual Pitch Competition, which aired on February 8th, 2022.

The HAC is actually going to mentor the first place winner student category for, hopefully, a potential pilot of their solution in the remote patient monitoring space. All of this information is available on the blog post affiliated with this podcast. So as you can see, a lot of the conversation we had today, the concepts that Sampath shared with us are addressed in various activities within our Healthcare and Life Science practice.

You know, the whole season is really going to get into these important themes- the benefits, the opportunities, but as well as the challenges that we can’t just neglect. And so when we come to these unsolved questions, this is what we bring a global community to collaborate, identify, explore, and build solutions in the form of tech and data standards, to really address some of these questions that are inhibiting the industry from moving forward and fully embracing the technologies.

So with that, I invite all of you if you’re interested to get involved in any of the work, as well as the HAC, or any of the work here at the Healthcare & Life Science practice, you can visit the practice website at ieeesa.io/hls. And hopefully, you can come along and join us for this great global experience.

I want to say a special thank you to Sampath for joining us today.

Sampath Veeraraghavan
Thank you, Maria.

Maria Palombini
And to our audience for tuning in. I wish all of you to continue to stay safe and well, and hopefully join us next time. Until then, take care.

Maria Palombini
Hello everyone. And welcome to season two of the IEEE SA Rethink Health Podcast Series. I’m your host, Maria Palombini, and I lead the IEEE SA Healthcare and Life Sciences Practice. The practice is a platform for multidisciplinary stakeholders from around the globe who are seeking to develop solutions for driving responsible adoption of new technologies and applications that will lead to more security protection and universal access to quality of care for all individuals. We all know cyber security is hot right now. There’s a lot of discussion about the challenges we’re seeing from breaches to organizational individual risk. And it’s constantly evolving from policy getting involved to technologists and engineers, trying to develop these solutions. As quick as the challenges come at us, this season features conversations with experts on this growing challenge on cyber warfare, the breaches, the use of the technologies that are out there helping us to improve our healthcare, but making our data vulnerable at the same time.

So with that, I would like to introduce you to Dr. Becky Inkster, who is our guest today. A little bit about Becky, she’s a neuroscientist. She’s passionate about everything from cell phones to genes, to jewelry, hip hop, you name it. Becky likes things to like it all. And she integrates it somehow into all of her work, very seamlessly. She researches artificial intelligence, machine learning and mental healthcare, computational creativity, ethics, and governance, digital clinical music based interventions. So you’re going to find that this conversation is going to be very, very enthusiastic, but also very different than what we’ve traditionally had in our other episodes. So before we get to the core of the work you’re doing, maybe you want to tell us a little bit about your work around cybersecurity, especially your passion for doing things around mental health, including both children and adults.

Becky Inkster
Absolutely. Just to build on the context that you’ve kindly set for me, I am really passionate about digital mental health, and I work very closely with a lot of different digital mental health and wellbeing providers. There’s a lot of support being offered across a wide range of age groups. So working with VR and pediatrics, tangible interfaces and toys to support emotional development and kids youth peer, peer mental health support networks, one-to-one, tele-psychiatry psychotherapy virtual companionship for the elderly to reduce loneliness. And it just goes on and on. Those are a couple examples just across the different age ranges, but with this diversity in tech innovation, this explosion in mental health accelerated by COVID, there’s a lot of diverse challenges from a cybersecurity perspective. So even hacking into a VR headset is very different from a cyber criminal, trying to attack patient records that are fire compliance.

We have to think of all these different surfaces that are very vulnerable, especially when we work with some of the most vulnerable people. And so given the sort of the surge in the supply and demand of digital mental health and wellbeing, I argue that cybersecurity needs to go straight to the top, it has to be one of the highest priorities, privacy by design, and a lot of other issues actually. The World Economic Forum recently released a white paper and the word cybersecurity was only mentioned once in 71 pages, which is around 26,000 words. I think that kind of sums up where digital mental health is in terms of thinking about cybersecurity. I really do want to make this a trend in our industry really, and the trends that I’ve noticed as you’ve mentioned, Maria, the sort of difficult times for healthcare where breaches are at an all-time high.

I read one report that was showing almost 900 million data records were compromised worldwide in January, 2021 alone. And that’s more than the entire year 2017. I recognize that mental health data falls within the category of health. We absolutely want a parody of esteem, which means that we want to value mental health equally with physical health. I argue that from a cybersecurity perspective, mental health data needs extra attention and extra scrutiny as it’s extremely sensitive in ways that perhaps people haven’t really fully thought about. Even just a crude example here in no country is cancer illegal. But attempting suicide is a crime, a criminal act or prison offense in certain countries and even disclosures of sexual orientation or gender identity could put people at risk or in danger. And the reason I mentioned mental health and sexual orientation and suicide just as one example, there was a groundbreaking report by the Trevor project involving over 30,000 young people between 13 to 24 years old.

They found that 40% of those who identify as LGBTQ plus have seriously considered a suicide in the past year when they were surveyed in 2018. So a lot of these issues are very personal and they spread beyond what you might normally think of as being a mental health concern. And another trend that I’ve noticed. Many people have noticed that cyber crime has evolved beyond just encrypting data to essentially blackmail or extortion of especially vulnerable people. A lot of people know the example of Vestavia, but for those who don’t, this was Finland’s largest psychotherapy provider that went bankrupt. They treated tens of thousands of patients across multiple centers in Finland. And they experienced data breaches where confidential client therapy session notes were stolen.This includes other personal information too. And when the cyber criminals went for the provider and they refused to pay the criminal started to blackmail victims and this included children.

So we’re seeing this shift or a potential trend really going directly at the vulnerable people and disclosures of this type of sensitive information could really endanger victims and others. For example, there’s often an emergency contact or details of another person or someone named during the therapy session. They might have abused the individual or somehow been connected and information disclosed about them too. And things such as previous suicide, thoughts and attempts, or if someone who’s approached when they’re vulnerable to pay a ransom, this could trigger issues if they already had experienced financial hardships or debt, and it really goes on and on. So, it could be naming sex abuse, victims, abusers, et cetera. So generally speaking mental health globally, there’s still a huge amount of stigma. And extorting vulnerable people could have a really harmful impact that could be life or death, or really trigger very serious instant consequences.

And then just to kind of tie up two other trends that I’ve noticed here that don’t necessarily directly relate to mental health yet, but I want to bring awareness to this is a possible trend relating to cybersecurity insurance. So, AXA, they’re no longer covering ransomware payment reimbursements. They’ve changed their policies in France. In digital mental health, we have to be very aware of such trends. Often in our fields, we are small and medium sized businesses, which could be deemed as soft targets. Many of the providers are vendors to large enterprises that are just starting on their journey. I also wonder whether trends will move from being solely motivated for financial gain but hacktivism and other types of targeted efforts. For example, hospitals being forced to release a patient or cyber criminals targeting human rights organizations, or what I’m trying to say is really I wonder whether the motivations for cyber attacks might become more complex rather than just financially motivated.

But that’s just my own personal concern coming from mental health. And you mentioned new approaches, what new approaches am I looking at and areas of research? So for me, I found a very successful approach was to bring providers together to have that conversation and that conversation could be anything from cybersecurity to collecting data. So not too long ago, I brought together over 50 providers in the digital mental health and wellbeing space. And together they gather data insights from millions of people around the world to show the impact of COVID on mental health and wellbeing. And that really got me thinking that I should launch a cyber security project because safety is a non-competitive issue. We’ve created this project. We’re at the beginning of this journey, but we want it to be a huge opportunity for providers to be proactive and to examine the current state of cybersecurity in the digital mental health space, and that it can help towards creating coordinated standards and responses to cybersecurity threats and attacks within our industry.

I’ve started working with ethical hacker Alyssa Knight to examine API vulnerabilities in digital mental health. And then I’m also working with XRSI, which is X reality safety initiative and just supporting the development of standards for safety and security in XR environments. And one last thing just to mention new areas of research that I’m really keen to map out is to look at not just how to fix the systems, how to address these threats and attacks, but how breaches map to clinical and psychological outcomes. So what is the impact on individuals of interruptions to mental health service provision on these outcomes for victims, or even just service users of the platform who may not have been affected as well. So just really trying to explore these clinical outcomes. And we’ve seen in previous research in cases of a heart attack, the clinical outcomes were worsened after the data breach. So I just think it’s really important to see what happens to risks of self-harm suicide, substance abuse, and how can we mitigate these risks, by having victim support centers, ready to address any issues of continuity of care after a breach,

Maria Palombini
That was a very powerful and insightful opening. And I think now you all know why I enjoy talking to Becky so much because she just gives you a lot of great information. I can sense it. I’m sure our listeners can sense it, but you have a very deep enthusiasm and passion and motivation for your work. Maybe just to share with our audience a little bit about what inspires you, motivates you to look at these new things and pursue all the research and try to take it to the next level?

Becky Inkster
I really like trying to make connections that are either extremely far apart and then link them all together. But for me, it starts with identifying a huge blind spot. So also being able to take a step back and not rushing into developing technology, and just seeing the horizon of the risks, what could potentially be ahead for the longer term future. I find that very inspiring. Also it occurred to me that I’m really motivated by working with digital mental health and wellbeing providers and combining this with cybersecurity experts, because both of these groups are really focused on safety, safety of data, safety of care. When you combine these two groups together, as I’ve just started to experience, it’s unbelievable how you can really start to get exponential output from combining those.

Maria Palombini
As many of you have noticed, Becky touched on this when it comes to mental health, we’re starting to see now more and more focused attention. Like we saw with telemedicine on the issue of mental health, you know, as a result of the consequences of the COVID-19 pandemic, you know, people in isolation or just the post-traumatic stress disorder of something of this kind, you know, still going on, we’re not over it yet, but at this point, and we’re seeing that these issues of mental health are coming more to the forefront. And this is from children through adults, 30 to 40 years old, all the way up to the older generation. So with that, you know, we actually even saw the US FDA put out some digital health enforcement guidelines around treating the psychiatric disorders during the coronavirus year, 2019 using these remote health devices. So what are some of the concerns as it relates to the security or the vulnerabilities and the patient’s privacy when it comes to use of these technologies, when we’re talking about, as you mentioned a very vulnerable population right now?

Becky Inkster
I think what you’ve just identified, which I can elaborate on, is a serious imbalance.We’ve seen the positive side about this surge in demand and supply with digital mental health providers, which is excellent, but with the FDA regulatory change in April of 2020, we see that many providers, it’s spurred them to move a lot faster than they had planned. And a lot of providers wanted to take advantage of this wide open door, which had never been opened, or it was even tricky to get your foot in the door. I think this created a really big imbalance and the world economic forum to quote them said it really nicely that this imbalance was between time to market and time to security. It really does create this enormous attack surface filled with just endless vulnerabilities for cyber criminals to explore even then, especially API vulnerabilities.

I personally have witnessed this firsthand where providers would get very excited about accelerating their technology and their products and their services, but not thinking further into the future about things like what would be their appropriate breach responses. Have they mapped out their responsible disclosures, have they considered budgets and thought about victim support safety, have they considered GDPR and having to report breaches and all these types of things. Quite a few, to my knowledge, really haven’t considered this at all, or let alone have a budget for cybersecurity to begin with when it comes to security and patient privacy, we’re really at the beginning of that conversation and digital mental health. That’s why it’s so important to bring in cybersecurity experts to help us with this. But again, we also have to feed back and explain just how sensitive this information is, a separate point on not cybersecurity per se, but related to data, grabbing on a historical scale and the loss of patient privacy.

When you mentioned security, the NHS recently announced that it was going to create a database with 55 million patients’ medical histories to be shared with third parties to improve research and planning. Now obviously that’s not an attack. I would never say that, but there are some elements that fit feel similar. Patients, including myself in the UK have a very short window to try and control the privacy of our data. And we have to opt out, by printing a piece of paper and sending it to our GP and many people still aren’t even aware of this issue, that it’s involuntary sharing of their data and in the past not perspective, but other past data. It’s a big issue here, and it’s not cybersecurity, but it’s still unclear who will use this data and for what purpose. So it kind of resonates in this, in this strange way, and it certainly feels like an invasion of privacy taking data without consent or transparency or public debate, especially when it includes private sensitive data like criminal records, mental health episodes, smoking, drinking habits. It really is everything diagnosis of disease, dated instances of domestic violence, abortion, sexual orientation. So I think while it’s a very different scenario, there are a lot of similarities to these issues.

Maria Palombini
Absolutely. So for all of you out there, I guess many of you are thinking, well, we’re talking about cybersecurity for people who have access, right? But really at this point I want to get to here with Becky, and I think it’s really important. It is assumed that technologies and these remote tools and models are for hard to reach patients in need of mental health treatment. While also watching these patients often emphasize that through the use of these technologies, the healthcare industry is supposed to be doing more by promoting the concept of self care and democratizing patient health data. So Becky, in your research, you find this to be true, or do you see that this only relates to certain areas of populations like established versus emerging economies or the connected versus unconnected? Are you seeing any sort of sparks or lack of sparks in this kind of area?

Becky Inkster
I’m seeing a lot. I’m seeing almost every type of combination and variant here. So I work with the extremes with people who are severely unwell with mental health illness right across the wellbeing spectrum. And similarly people who don’t have access maybe through financial hardships or other reasons they’ve left prison to reenter the community. There’s a lot of different groups that I work with. I’ve seen tech fail for very sick people. I’ve seen unconnected people be excluded from things that could probably really help them. People becoming more occupied or, or overburdened by self care responsibilities. So I think you just, you see every possible angle, but I really do believe that there’s nowhere near enough support for the hard to reach communities, from a technology perspective.

And when we do, it’s quite linked with depression, anxiety and some of the more common mental health conditions, and we need to go deeper and reach people who are unable to access technology, unable to use technology. And we just need to understand how we help people who are experiencing homelessness. For example, it’s not going to be the same solution, and it’s not as simple as just handing someone a phone someone who has drug dependencies. It really isn’t that simple, I should say on the flip side though, because I don’t want to just always see things from, from one lens for eating disorder group therapy, there was some research showing that digital was actually, it was just as good if not slightly better. Sometimes if you are able to access it by just having the comfort of your own space and not having to go to a physical place, maybe you don’t want your body on display or to be judged in a physical space. Or perhaps if you’d been crying after a session, you don’t want to have to leave a physical space. So there’s a lot of benefits to it just to kind of balance that out.

Maria Palombini
Interesting. So it’s not a sort of one size fits all approach. We have to definitely look at where some things are working and maybe there’s some learning cases, right? Like what seems to be working for this group can be sort of amplified and maybe potentially help another group. I mean, that’s the beauty of the research.

Becky Inkster
Yep.

Maria Palombini
Our focus obviously is on privacy and protection of all individuals from children to older adults in using these digital health toolkits and technologies remotely of that nature. But when it comes to pediatrics or the role of guardianship or the role of a caregiver with these new technologies, there always feels like there’s a little throw, a little kink into the chain. There always seems to be some sort of challenge that we have to sort of figure out. I think one of the big things is around children, a parent or clinician. We know the end to end encryption of anonymization in the data chain. So a parent or clinician might want to wish to access the content from a young adult’s digital mood diary per se, right. Just to, you know, for safeguarding, you know, does the duty of care override privacy rights does that, and then does that negatively impact the treatment’s effectiveness? So I’d love to hear your perspective on this.

Becky Inkster
I could go on for a long time about this and it’s a huge area of focus that I care deeply about. So it’s an excellent set of questions. And I think the simple answer should be duty of care, should override privacy. If someone has harmed themselves or threatens to harm themselves or others, this needs to be reported and confidentiality needs to be broken, but in digital spaces, it’s just not always that clear cut. And it’s not as easy to protect someone, especially in anonymous settings. So obviously parents can do things like making sure they’re aware of passwords and these types of things. And I should say parental monitoring is a very good protective factor for mental health outcomes in a young people’s development of mental health problems in later life.

So it’s extremely important for parents to be involved, but increased privacy doesn’t always equal increased protection. And there’s this strange juxtaposition that we need to start teasing apart. And I’ll give an example here in the UK. One of Britain’s most prolific pedophiles would not have been brought to justice without using social media data according to the national crime agency here. So now Facebook is planning to potentially implement end to end encryption in its messaging services. And this has caused a lot of concern for police and their ability to identify predators who would be abusing children and making it easier and safer for predators and making children even more isolated. The role of parents, the role of clinicians to make sure they’re very aware of these issues, it’s extremely important. Especially when predators are pretending to be someone else, especially in a position of trust and especially on a digital mental health and well-being platform or space, where there’s already such a very real risk about the young people talking about their vulnerable state, potentially risk disclosing information that the predator could offsite them or take advantage of.

So I think that this juxtaposition between cybersecurity encryption, keeping everyone safe, there’s a huge issue that we need to tackle because if we keep young children, young people vulnerable to predators, these adverse childhood events, which we call ACEs in mental health and psychiatry, there are huge predictor of poor mental health outcomes later in life. We have to be so careful about how providers, how end to end encryption is rolled out in digital mental health settings. If it’s ruled out, this juxtaposition between preventing cyber attacks and keeping data secure, we have to balance that with the potential harm of not monitoring signs of abuse and it’s unrelated to mental health, but in the news right now, one of the headlines is that WhatsApp announced that they’re taking the Indian government to court over a controversial new law that will increase the government’s ability to monitor online activity. So, the law would require Facebook to remove encryption so that messages could be pulled into a database and monitored for illegal activity. So you could see mental health fitting into that, but that’s an ongoing issue where Facebook said that they won’t store user data in this way. They’ve launched a legal challenge on that basis. So it’s a really big issue. But in mental health, in particular, we’ve got to figure out how to balance that.

Maria Palombini
You know, I often hear about responsible data use when we’re talking about any kind of medical technology. So I think from, based on your research, and I know with mental health care, we have to be extra sensitive on how we define responsible use of the data coming out of these devices and the use of these devices. So I guess based on your research, is there some sort of industry defined standard as to what would constitute, responsible data use, you know, security, privacy, in developing or testing new technologies for mental health care.

Becky Inkster
This is just my lone voice, and this is why I want to work with so many different providers. But as I mentioned, I’m trying to gather these providers together to get their views on this as well, but I’m also a co-founder of a mental health and wellbeing venture. Through that startup journey or the inside perspective, I personally don’t feel that there’s a strong sense of support in terms of how we follow industry defined standards, or quite often, we make very strong, ethical judgments on our own because we want to be ethical, not just following legal or industry defined standards, but it becomes very difficult. And I think that’s part of the reason why I wanted to gather all of these providers together to almost create our own set of standards or discoveries that could then be embedded into something bigger significance.

There’s this tricky trade-off where it’s data minimization. You don’t want to collect anything that you don’t need, and you don’t want to keep it, just make sure you’re churning through your data if you’re not using it, just get rid of it versus collecting enough to be able to tell a full, valid truth about someone’s experiences or mental health status. It really is this tricky balance of trying to support someone on their journey, but not run into issues with false positives or making predictions, inaccurately and things. I worry a lot about responsible data use again, when looking out at the provider space not too long ago, I was approached by a whistleblower making extremely serious allegations involving a data coverup. So this was within a digital mental health wellbeing space. Being responsible with data and, and looking to, to these standards or these industry defined standards, I think standards get you so far, but the way people decide to act within their provision, that’s a very separate issue that I think we need to cover more. So I really do actually worry a lot about responsible data use and I know standards can get us to a certain level, but I think that’s why it’s so important for providers to come together and to share their issues, to link the standards to something that is real worlds practicing the front line of digital mental health.

Maria Palombini
Absolutely. We are approaching a time when doctors prescribed mobile apps games for adolescents or virtual reality kits to treat social anxiety or mental health rather than medication or talk sessions. Yes or no?

Becky Inkster
No, and now I’ll explain. Yeah, we have to tread very carefully with this type of discussion. That question just reminds me of when I was interviewed by a media outlet and they were talking about this hip hop therapy paper that we published and the media wanted to use the headline to stop taking your medication and just listen to hip hop. And we were horrified. We obviously didn’t let them go ahead with that headline. We didn’t acknowledge that, that we said that we just completely parted ways, but abruptly stopping medication can have such serious consequences. So we’d have to steer away from people thinking that this one thing can really do it for us and nothing else really matters. Obviously there’s a lot of increasing numbers of treatment options that’s becoming available. But we have to remember that with mental health.

You can see this from a biological perspective, psychological perspective, or sociological perspective. All these different factors, each person’s needs are different and their treatment plan or how they’re supported, will differ as a result. While all these different treatments are emerging, they’re very exciting gamification and all sorts of really interesting tech innovation. We just have to acknowledge that each option has its own important way of contributing, but we have to fit the right pieces for each person differently. I think my first point that I’d want to make is, medication is still a very important option for patients. They can benefit from this, those who choose to go down this route. Medication adherence has always been an issue in mental health. But we’re starting to see some tech innovation like Digi meds, trying to help improve outcomes and adhere to medication to help them feel better.

And within medicine, again, there are other emerging alternative drug industry trends. We’re still seeing the psychedelic drugs being used to treat phase three trials to treat mental illness and combining talk therapy with medication and leading to positive outcomes as well. I think that there’s still a lot of great work being done in that sort of space. Where I’m excited about is the evolving concept of talk therapy. So making it more informal through talk sessions or chatting about your mental health while gaming with others, it can be very therapeutic and less prescriptive. It can open conversations with peers and really open dialogues about mental health or how chatbots can just be there to listen while someone tapes or speaks a very intense expression about how they feel so talk or chat therapy. I think it’s really evolving, but it shows a lot of promise there.

And an extension of that, an area that I’m interested in is music therapy. I think that this is really gonna start to do great things when you combine it with technology, allowing people to express themselves in non-prescriptive ways. And yeah, a lot of interesting things asking people how they feel, but more on their terms, it might make things a little bit more accessible, especially for hard to reach groups. We can’t always use prescriptive approaches or clinical approaches because I think things like even the dark web people will want to be as far away from clinical spaces as possible so that they can seek support if they were wanting to find a suicidal partner. For example, I just really think that people go where they want to go when they’re seeking support and that we just have to make sure that all of these options are available and we try to keep people as safe as possible because we’ve seen this kind of a surge in the supply and demand of the more well-being side of things or the mild to moderate mental health. It’s made me sort of curious about whether in coming years, we might see a stronger push away from medical treatments or attempts to blend and then taper medication or reduce side effects and reduce medication treatments from treatment plans, and then try to add other options into, kind of the talk therapy, the physiological measurement. But yeah, that’s just one thing that I’m curious to see how that space gets bigger and bigger, what happens.

Maria Palombini
So Becky touched on this in your introduction remarks, how much time from a point of development and design is being put towards cybersecurity and privacy risks. Do you find that developers have this at the top of their agenda, or is it more about ease of use for the patient or extending the battery life or making it more accessible or that kind of thing? We see a lot more, you know, function on human factors or on usability, but sometimes we feel like the attention is not so much on the cybersecurity and protection of data side. Do you find that this is more the same in digital health and you’re in health technologies or are you seeing it that you’re finding more of the developers are more focused on the privacy and protection side? Is that top of agenda? Point of view?

Becky Inkster
Yeah, I really wish I could say we were. But no, I think it’s, it’s exactly those issues that you said in healthcare more broadly. If anything, I’m a little bit worried that we are lagging behind a lot more in considering cybersecurity and privacy risks. Even when I work with mental health providers who have 10 plus years experience and a lot of data that needs protecting there are still serious issues and concerns because the threats and the attack surface is constantly evolving. But at the same time, I think the journey of that 10 plus year provider can be very beneficial for providers who are just starting that journey. I think it’s important to work with both extremes, especially those who are just starting the journey, because that’s exactly when we can start to build in a cybersecurity culture and really get them thinking about all the different issues in that space. And this whole privacy by design, or just really thinking about that from the beginning, gives us an opportunity to go from way behind to right at the forefront.

Maria Palombini
Absolutely. So I asked this of all my guests, because there’s always so much diversity in this answer. Many have argued that the regulators, the policymakers should do more to require the developers, the technologists for software and these connected health technologies to do more in building these security features from an either privacy by design perspective or just an engineering perspective. So my question to you is do you think that this is more like policy needs to stand up or require it? Do you think it’s more like a combination of everything? Like we need more standards, we need policy to set it up and we also need the industry to step up and come together and help address the problem, like where’s your perspective on this kind of thing?

Becky Inkster
My disappointing answer is that it’s everyone’s problem. But I will say again, as you’ve noticed, I’m really coming at this from a provider perspective and I think providers are at the heart of it all. And they’re the ones that are on the front line, they’re facing the real issues, they’re making decisions. And yet in my field, a lot of these decisions or discoveries are not being captured and either fed up to the powers that be, or, you know, embedded in various decision-making processes. So my answer to this is just that we have to start listening to providers more because they’ve really got a lot to say that could help us with these issues. And then one group that wasn’t mentioned in the examples that you gave is especially for mental health, the importance of lived experience, it’s extremely important and in cybersecurity and there’s research showing that there’s increased mental health challenges and burnout. It might be very interesting to look at the dual expertise like experiential mental health and wellbeing knowledge, as well as the professional knowledge, this crossover between cybersecurity experts and especially those who face mental health problems. I think that is also another really important source where we can learn a great deal about what’s working. What’s not, how do we roll this out? So those are two of my angles that I always like to think of, but of course it’s everyone’s problem.

Maria Palombini
What would you find or say is the most important call to action? Either for the healthcare professional, the hospitals facilities, the clinicians, or the engineers, or the policy makers or patients themselves, what’s the most important action you can impart to them to start mitigating this risk in the use of these technologies?

Becky Inkster
I don’t have an answer yet, but this is exactly the question that I want to ask at my summer conference. We’re going to be discussing that exact issue and trying to figure out how we rank the vulnerabilities and how do we come up with decisive actions? So we’re very fortunate to have experts like Alyssa Knight who can really help us, but the conference that I run is digital innovation in mental health. And normally it’s in the precincts of Westminster Abbey, but we’re obviously virtual at the moment. This is the main thing that I want to cover at the conference, how to make impact, especially from a cybersecurity perspective, but equally looking at the online child protection issues and balancing those together. So while I don’t have anything to say just yet, that is really what we’re trying to tackle in the coming months and at the summer conference. I’m hoping that people now are really appreciating the importance and the extra sensitive nature of mental health. We should have the highest standards and we should have the most support. So we’ve got to come from the back of the queue and get to the front somehow.

Maria Palombini
Excellent. So for everyone listening, just click on to read the blog post and the link to this upcoming conference in August, IEEE SA is gonna also be participating in it because this is an important initiative for our work here in the healthcare life science practice. But for all of you who may want to attend there, just get involved. Please take a look at that blog post for the link to the conference. Becky has shared with us many great concepts, and a lot of the different points are covered in different activities. We have here in the IEEE SA healthcare life science practice activities. We do virtual workshops because we’re all virtual. We have incubator programs, we have standards, development projects. We’re doing as many of you may have heard from our previous episodes. We have a global connected healthcare cybersecurity virtual workshop in which Becky did participate in our last one as a facilitator in one of our virtual breakout sessions we’ve, those are the ones that are on demand from February and April and June.

The live ones are going to be in September and November as a five-part series. So hopefully you can find out and join us in listening to those. Plus we have plenty of incubator programs around wearables and medical IoT, interoperability, and intelligence, decentralized clinical trials, and obviously tele health security, privacy, and accessibility for all. So we’re covering many different areas that Becky touched on at some point in our conversation. And if you want to learn about all of these activities, you can visit IEEESA.IO/CYBER2021, but we hope you come and check out. And if you have an idea or want to get involved in any of these activities, the best way to do it is to express your interests and tell us so that we can make sure you can bring your expertise and time to finding a solution for everyone. So with that, I want to thank Becky for joining this conversation today and your time. And with that, I want to wish everyone to continue to stay safe and well until next time.

Maria Palombini
Hello everyone, and welcome to season two of the IEEE SA rethink health podcast series. I’m your host, Maria Palombini and I lead the IEEE SA Healthcare and Life Sciences Practice. The HLS practice, as we like to call it, is a platform for multi disciplinary stakeholders from around the globe, who are seeking to develop solutions for driving responsible adoption of new technologies and applications into the domain. Hopefully, the end outcome will be more security, protection, and universal access to quality of care for all individuals. We know that cybersecurity is evolving constantly from increasing policy to a changing threat landscape. This season brings all these conversations from these experts on the growing epidemic of cyber warfare breaches as we see on health data and health technologies, and how they’re looking at it both at the regional level and the trends we’re seeing across the globe. Together, we’re hoping that with solving these problems and the benefits of these devices, we will reengineer the strategy to better patient privacy and overall security. So with that, I would like to welcome Roque Juárez from Mexico to our discussion.

Roque Juárez
Hello everybody. Thank you, Maria, for your introduction. And I’m going to share with your audience about this fascinating domain.

Maria Palombini
We can’t wait and I know you have a really diverse background in security intelligence. I know that you’re currently at IBM Mexico. So with that, why don’t you give us a little bit about yourself, some of your specialty, especially in your work in IT security, some of the things you’ve seen throughout the years, how they change or maybe gotten better, new developments, especially being in Mexico, you come with a different perspective, as all our experts from around the globe.

Roque Juárez
Of course, my pleasure, Maria. I have to say that I’ve been involved with information security, IP security, and now cybersecurity. Since I was at university, I perceived that this area was so fascinating since the first time I met some news regarding the historic hackers such as Captain Crunch and Kevin Mitnick. I thought, and I was sure that this area was going to be in the focus of so many industries, because all of them were getting support by it more and more. So I got engaged, and I couldn’t leave it. I think it will be the best part of my life for the rest of my life. It has been evolving so quickly. We can say that maybe if 15 or 20 years ago, cybersecurity or information security as the main and the holistic concept. It was not in the focus of many organizations or in the focus of many regulators. And we have to say that it is a natural evolution process. Especially in Latin America it is a challenging domain. Because sometimes, historically talking, cybersecurity has been perceived as a business blocker. For every control you decide to deploy, you’re going to blow up the business vision, mission, and main purposes.

But in current times, and due to this pandemic, we can see that all the organization’s no matter which is the sector of the industry they are in, they have to transform the core business. Most of this transformation is supported, at least enabled, by technology. Healthcare industry is one of these industry sectors that is being impacted with this accelerated evolution. Now, we can say that in Latin America and globally, industries have been engaged with IT and in cybersecurity issues sometimes before the healthcare industry.

For example, traditional industries such as financial services, insurance services, ecommerce, these industries have to be focused on cybersecurity and IP security, they developed a business with engaging customers and these business environments. Because the nature of the core processes are supported by IT. Some other industries as manufacturing or healthcare for example, IT is a standardized technology, so in this case now, healthcare is taking advantage of this standardized technology provided by the traditional IT to develop the new patterns in the core business. Now, we can see that healthcare industry, the core devices, the core apparatus, the industry uses to make the main objective of the industry, like laboratories, hospitals, and these kinds of organizations. Institutions are taking advantage of these IT standards and technology and devices. But now, these new industries that are taking this advantage are facing new challenges that they were not aware to handle. And it is not a critique. And now, the hacker has to develop to embrace different kinds of services and processes to make this transformation a tangible thing. I’m talking about business or core processes, but they have, for example, the patient support processes as registration as the following up about the patient status and things like that, and administrative and management processes. In this big picture, healthcare has to handle a lot of challenges due to this standardization of the technology that they are using for the core business.

Maria Palombini
I think you’re giving such a nice macro introduction. You know, I could sense from your passion right away that you’re into this. You’re already jumping into our next segment, the core. You already started to preface this that you know, healthcare underwent a major digital transformation. We all know this, like anything else in the digital era. Obviously there wasn’t always or there is not so much a focus on cybersecurity or the cyber breaches and the vulnerabilities compared to other sectors that were more traditionally attacked, like banking, insurance, finance, e-commerce, that were first on the hit list. You mentioned there’s some real critical challenges that have emerged. Can you share exactly what you envision or your perspective on those challenges and how they’re impacting overall the healthcare industry?

Roque Juárez
Yes, of course. The first important thing to keep in mind is that, based on some cybersecurity industry reports that have been published at the beginning of the year, we can see in the IBM x-Force Threat Intelligence Report, this industry moved from place 10 in 2019, to place seven in 2020. The most common attack factors that we can see that the attackers used were around ransomware, data theft, and server access attacks, but we can see that these attacks are related to common IT standards or common IT technology used to support some other processes or services that were not the core processes. Based on what we mentioned about this digital transformation and this adoption, I can see three main challenges. The first one is that the healthcare industry is adopting its core technology. I mean, some years ago, IT was just a group of support services for administrative tasks and things like that. Although the new medical devices are running on common IT loggers, I mean, operating systems, networking applications, software engineering, things like that. So they are exposed to the vulnerabilities discovered reported on these IP assets. That’s the first main challenge. The second one, the numbers are not related to the priority. I think these three challengers have the same level of priority. Let’s see why.

The second one is privacy on personal info. And most of us can think that the privacy is just for the patients. We have to think about the privacy of the information collected from the collaborators or employees, it is at the same level of importance as the patients want. So the essence of this industry, the healthcare industry, requires that the data from people have to be collected and exchanged because of its process nature. This data is considered in most of the laws and regulations all around the world, as personnel and sensitive, the most important sensitive information. All the organizations that collect or change this information, that’s to protect it at the same level of risk as the most valuable information. If you are like most people, and you identify or classify your processes and business information as relevant and confidential, the personal and sensitive information that you have, it doesn’t matter if it is from your collaborators, employees or patients, it has to be ranked or classified at the same level. So the level of protection that you have to deploy on this info is crucial. And it can represent investment and efforts to protect. That’s the second main challenge.

And the third one, since all the research and all the investigations and collaborations around the vaccines, especially because of the COVID-19 pandemic, specifically talking, there’s a new confirmed challenge related to hacking the infrastructure with these researchers, or investigations are done. This could affect the integrity, availability and confidentiality of the results of the research and investigation. But what is more that we have to think about, is that some attackers make phishing campaigns against common and end users or common people as you and me where they distribute emails or some advice around the internet, which turn people or to access information or some advantage around vaccines. They are trying to steal the information or personal bank accounts and things like that. We cannot lose the idea that the protection of the information around research and investigation plus two components. I think all the organizations in the healthcare industry have to pay attention to that, because the integrity and the reputation of the brand the organization can jeopardize.

Maria Palombini
That’s fascinating. We’ve had many of our expert guests pinpoint the fact that they need to embrace just in general, the situation with these vulnerabilities as organizational risk, not just a product risk. So I see that you as well share that same point of view. We’ve had different research and I’ve had some of my guests say that the Latin American region is a little bit behind In creating strategies for response or anticipating these kind of breaches in connected health applications as they continue to gain speed within the region, and given your work there and being from the inside, is there anything that you’re seeing in trends that seem to be that there’s more attentiveness to the challenge? Are you seeing some new ideas, either from government or from just industry, the area, trying to address some of that growing challenge that’s happening not only in Latin America, but this is a global challenge, but perhaps bird’s eye view from where you are, see what’s going on?

Roque Juárez
That’s an interesting point, because healthcare organizations in Latin America are making big efforts to close the gap. Maybe the starting point of these challenges for these organizations is not easy. It’s not easy for anyone. But in this part of the journey, they have not been trying to address the problem, but just investing in technology.

Right now, and I think it is a global symptom, all the organizations are swimming in a pool of tools and technological platforms, trying to reduce or mitigate the risk associated with this changing threat landscape. They are trying to address the challenge with a wider view, which is positive in my perspective, because they are trying to share the concerns with the C level, they are wanting to drive this challenge as a corporate a challenge, not just IT or technological approach, they are trying to move the needle around holistic effort: people, technology and processes. This is a group of premises that they are trying to work and develop. What is more, currently, they are not trying to acquire more technology, or replace all the hardware and software that they invested in previously, what they are trying to do is to develop capabilities around these three premises I mentioned. It’s not easy, because right now there’s a lack of resources due to the pandemic and the economic situations, it is not easy to get all the resources the organizations need to address and to show the challenge. But they are trying to make a clear association between business needs, and not just the regulator requirements. They are trying to add customers and business environment requirements to these benefits and risks associated with the technology, and IT technology-supported core processes in the healthcare industry. Latin America is making progress. I think it is not as fast as required. But we are not doing nothing.

Maria Palombini
One of the things that I’ve been reading more in the headlines, and it’s unfortunate because we’re in the middle of a public health pandemic, and we’re worried about obviously saving lives, opening data to help research. But yet we’ve seen this increase of attacks on general healthcare institutions and COVID-19 specific research institutions. Can you share your perspective on what’s driving this increased appetite for these hackers? Like what’s their motivation? Or are they getting access to something that they weren’t gaining access to, before that? What’s really fueling this rage?

Roque Juárez
It is a question without an easy answer. Because I think that mostly people have associated all the cybersecurity issues as a teenager driven event in the past. And nowadays, I got to say that when we read the newspaper, or we read on the internet, or somewhere else, that an attack was successful, maybe we are associating an image with a teenager in underwear in the parents’ house, playing games with computers. This is not any more like that. These cyber crimes are at the same level as organized crime. We have to stop thinking that this is a teenager’s matter, these are relevant and cooperated industry matters. Based on that, we can see that the fuel for these hackers could be to sell in black markets, all the information they can get from these investigations or research. It can be associated or classified as an act of vandalism. The other component of this equation could be, as I said before, to get personal and sensitive information that can be sold again, in digital black markets. If we can check in different reports around the amount of money that black markets related to cyber crimes is generating, we can get the answer to these questions.

Maria Palombini
Absolutely, just another level of complexity to deal with in the midst of this challenging time. So I asked this of all my guests: from a point of view, we hear debate that this is a we need more policy to address the issue of cyber vulnerabilities in the connected healthcare system. We hear others who say that it should be market driven, engineers, and technologists need to step up for the benefit of the service they provide to customers. So we’re hearing all these different things. From your perspective, what do you think? Or what’s your perspective on where we need to start pushing more of these opportunities, whether it’s policy, whether it’s development of technical standards, whether it’s incentivizing industry to sort of step up and start addressing these kinds of issues at the foundational layer?

Roque Juárez
You work up an important and relevant actor in this play. I’d have to say that the work that regulators are doing is essential, but it is our starting point, it is not the destination. When you are working just for the regulator to be compliant with the regulator, you are not doing things right. I mean, to be compliant with the regulator has to be a natural symptom that your IT and cybersecurity operation is aligned with the business requirements and the regulatory requirements. But most of the time, what happens is that an audit by the regulator is going to be executed next week, so I’m going to be prepared. You are not doing anything to change your current threat landscape, your current vulnerability landscape, not in the benefit of your business, just to be compliant. So that’s what I said that it is a starting point, you are going to have some indications to be compliant with but the challenge for the administrators, the cybersecurity responsibility in the organization is to understand these regulations, and to translate the business environment to the business context. So you are going to be aligned and you are going to be compliant. It is a starting point, in my perspective. Another important thing you mentioned, when you work in an industry, you can make such progress as developing standards as sharing concerns or lessons learned. It is not an issue that is not a problem we are going to fix alone, to collaborate, to embrace we need to enhance all these efforts that regulators and organizations or standards organizations are doing too. How? Most of the times when a law or some regulations are going to be published or standards are going to be published. There’s a period where you can contribute, share your concerns, or share your experience and this can be used to develop a link. So this is a way. I mean there’s not a silver bullet. There is no procedure to follow. But I think it is a good starting point, right?

Maria Palombini
Yes. You covered so many great things and you know, some of the points that I’ve just picked up really quickly are common themes that we’ve talked with other guests from around the globe that you hit on just the same. First of all, cybercrime is an organized crime that is no longer a teenager thing or something just as happens because someone has nothing better to do. And at the same time, that cybercrime is an organizational risk, and we’ve heard this recurring theme as well. I think an important point that you also brought up just as a note to everybody, we do have a common theme where we say policy needs to step up a policy is definitely not the end game. I think you reinforce that point as well. The third part is, we hear a lot of investment going into technologies and how you know, we can deal with the issue of cybercrime and cyber breaches. But the question is that, it’s not just about investing in the technology, like you said, it’s trying to fix the problem. We have to try to get to the problem. The sad part is that usually when we move up higher on the level on a scale, we think it is usually a good thing. But the fact that healthcare is moving up as an appetizing place to be breached, is not such a good thing. So this is something for our audience to keep in mind. You brought up so many great insights, common threads, what do you think is the most important call to action in the healthcare domain? You know, we’re talking a wide risk of hospitals, facilities, pharmaceutical companies, technologists, regulators, patient advocates, patients themselves, there’s a lot of people and entities in the mix. What do you think is a really important call to action?

Roque Juárez
Again, it is a complex situation, as you were describing. But what I would say is that the first big step is to bring these new risks to the table with the sea level in the health care organizations. I think this could be a big step for the industry. In the meanwhile, we can reinforce some more tactical and operational actions to make this change. It is not an easy problem, but how do you eat an elephant? A piece at a time right? So, to make progress based on legal changes or legal efforts, but not to stop the airport, I could say that let me share a general call to action. Secondly, to integrate the filter technology cybersecurity risk in the organizational risk. When you are managing your organization or corporate risk, healthcare cybersecurity risk has to be there. Third one, to manage all the vulnerabilities and monitoring of the healthcare technology stack, as part of the corporate program will their abilities management program, put to work with manufacturers and service providers to define security and operations requirements as part of the design. This is an important thing. We mentioned that sometimes this cybersecurity is not considered in the beginning. This is why, because when you are designing, you are not taking cybersecurity in mind. So if we push these actions with the manufacturers and service providers, the landscape is going to change. And finally, last but not least, to train people in cybersecurity as part of the daily activities. It is not just your employees, your customers, your administrators, your operators. As I said before, one of the premises is based on people. It doesn’t matter how much you invest in cybersecurity, if you have people who is not trained in cybersecurity, or people who is not changing his or her passwords, just to put an example, because you’re not going to tell him or her to change the password, they are going to change the way they perceive and interact with cybersecurity. So I can say that could be the main group of actions to execute and to have in mind.

Maria Palombini
That says a very important call to action. And I think that something for our audience to think about, that this cyber challenge is like a large elephant in our way, and we can attack it all at once we have to do a little bit at a time. Roque brought up many great concepts today that we are currently addressing in various activities in the healthcare and life science practice. I want to share with you all that we are hosting a five-part virtual workshop series in 2021, called Global Connected Healthcare Cybersecurity. And we’re presenting it in collaboration with the Northeast Big Data Innovation Hub, out of the campus of Columbia University in New York. This workshop series is designed to really produce pragmatic outcomes, and build the framework for these much needed solutions to response to prevention, to preparing strategy and everything in between. And if you’re interested in attending and being part of the open collaboration to develop these solutions, you can see them on demand, just register free and you can see them anytime at IEEESA.IO/CYBER2021. And just let you know, we have many different incubator programs where we incubate ideas for standards or best practices in telehealth we have them in decentralized clinical trials, a mobile health app certifications, obviously, and WAMIII, which is Wearables and Medical IoT Interoperability Intelligence. So if you would like to engage in conversation about what you heard today about overall what’s going on in the industry, please be sure to check out our IEEE WAMIII channel. And you can learn more about all of our activities at IEEESA.IO/RETHINK. Thank you audience for joining us today and tuning in. And we wish you to continue to stay safe and well until next time.

Maria Palombini
Hello everyone, and welcome to Season Two of the IEEE SA Rethink Health Podcast Series. I’m your host, Maria Palombini and I lead the IEEE Standards Association Health and Life Sciences Practice. The practice is a platform for multidisciplinary stakeholders from around the globe who are seeking to develop solutions for driving responsible adoption of new technologies and applications that will lead to more security protection and universal access to quality of care for all individuals.

We know cybersecurity, which is our ultimate goal – how do we protect the connected healthcare system? It is evolving constantly from increasing policy to a changing threat landscape where there’re still considered many risks and attempts to proactively combat this challenge as it’s happening in real time, anywhere throughout the globe. This season, we’ll bring you experts to share with you what they’re seeing globally, and as well at the regional level.

And with that, I would like to introduce Andrés Velázquez from MaTTica to our podcast today. Andrés it’s going to share some really great information with us. He has a very deep experience, more than 20 years in cybersecurity, cyber crime, computer forensics, and digital investigations. These are all the things that we need to know in a connected healthcare world. But before we get to his expertise, I’m going to ask Andrés to share a little bit about what he does at Manteca and what actually inspires his passion to go into this space.

Andrés Velázquez
Thank you very much Maria. MaTTica has been evolving for the last 15 years. I actually created MaTTica back in the days, because I saw that there was no computer forensic company in Latin America. The need for digital evidence or to find digital evidence to present it to court and to different processes was at that time something that made me make a decision. I was trained by the US Secret Service at some point. One of the things that I have been doing is helping a lot of organizations internationally against child abuse. So these are some of the things that we’re doing. We actually are the crisis management team for the IT on some of the biggest hackings and narrations into some companies here in Latin America. So I think that will help to understand what we have been doing, and how I got into this field? I always loved computers. At some point, I decided that cybersecurity will be the thing that will lead my way in this life.

Maria Palombini
It’s fascinating. Every time I talk to you I always learn something new about you. I didn’t know about the secret service thing. There was an interesting thing on your LinkedIn profile. You had mentioned that you are an incident response enthusiast. It’s the first time I’ve seen it. Maybe it might be out there somewhere else, but maybe you could just share a little bit of light exactly what came to mind when you said that this is something that you want to say about yourself?

Andrés Velázquez
It’s kind of interesting how everything has changed in the last 20 years when I started doing cybersecurity. Everything was about firewalls, anti-malware; that time was about antivirus. Then I started into policies and all the documents that you have to have, and everything started to move into forensics. As I mentioned, the part of computer forensics led me to digital investigations and digital investigation led me to get into something that I really like. It is how you can do incident response and crisis management in clients. Most of the clients that we have are in the financial sector. So it’s kind of weird how I’m going to say this, but I love the adrenaline that I get when I was called to solve an issue of a client or a company that could get very messy.

Maria Palombini
No, I wouldn’t call it weird. We call it passion. And we have many volunteers like you in our different programs who share a similar passion. The idea to find a solution, to do something, to make something that was bad better, or find a good outcome for it. That was one of the things that I found most exciting about our initial conversation. When we were talking, I noticed that you were very tactful in not using the term cybersecurity. And you even mentioned to me that cybersecurity is a technology engineering term, but what we need to focus on is risk mitigation and response. So we’re seeing more companies such as yourself, like MaTTica, who are getting into this sort of area and really proposing this concept of risk mitigation, risk quantification, proactive response, forensics, and that kind of thing. So maybe you can explain some of these concepts on this approach and why you believe in the world of connected healthcare is because that’s where we’re more and more moving towards. It’s really important to incorporate this sort of approach into your strategy system.

Andrés Velázquez
Everything started because I have been training a lot of board of directors from different kinds of companies in Latin America. When we talk about cybersecurity with them, they think it’s something very technical that you have to know how to program, or you have to know what distributed service is. And the best way I have learned to talk to them is to talk about risk. It’s very interesting because this can be applied to pretty much everybody else, even on the personal side, if you listen to these past podcasts and you start listening to some terms like buffer overflow, or the WAF, and all those terms. We’re very used to talking like that with acronyms, because I’m a very technical guy. Well, you won’t understand. So getting into the risk approach is better.

We are used to reacting to risks. Businesses are used to understanding that they have to do something about risk that could be implemented, control, transfer the risk, or accept the risk. When we can link the risk to something that could affect the company in their reputation, loss of the operation, or an incident that they could lose money by a lawsuit and find the cost of getting back to operations. Then they will understand the value of considering cybersecurity on their plans. This is something that is interesting also because we, on the personal side, are dealing with risk all the time. The only thing is we understand what the risk is. Let’s talk about the pandemic situation that we’re facing right now. I was in San Francisco when everything started, the news was very critical and the way that they were explaining what was happening, but at the end, or at that time, they weren’t really clear on what were the risks.

I remember all the things that I did on my flight back to Mexico. I don’t think they were wrong, they were in the right things to do at that point. So cybersecurity is not about installing anti-malware and a firewall, as I mentioned, it’s about creating a strategy. Now, how can I link this to the healthcare perspective? Well, first of all, we need to understand that technology and cybersecurity are cousins, but they’re not brothers. There’s a gap in between them. Innovations, in most of the cases, have a lack of cybersecurity leaving a lot of risk on the table. The research and development teams are trying to create the most amazing devices, but in the end, those devices could have their own vulnerabilities. They can run in networks that have not been secured. And the users of the technology are not aware of the risk when they have them. It’s very interesting the way you presented these questions, because no, the companies in general are not embracing this concept. They’re still hiring people that will do cybersecurity as something that will go on the operation side, not really on the strategic side of it.

Maria Palombini
Interesting that risk is one element. And I think one of the things that sort of gets lost is the concept of privacy. We think about secure breaches, but what really we’re even not focusing on is patient privacy. And you mentioned something very interesting to me that I found so profoundly insightful when you said that there’s a fight between being comfortable versus being secure. And you said it in the scope of, there’s a balance with the medical devices we use in hospitals versus consumer devices utilized in the home and in the concept of overall risk. Do you want to explain a little bit more what you mean by this fight? Like what you have observed or what you’re seeing as trends from that point of view?

Andrés Velázquez
It’s something that at least in this field we discuss a lot. We always want to have the most secure infrastructure from the internet of things and points servers and networks. Let’s say that the information is stored in our colleagues’ computers and is very confidential and we want to control as much in how the user moves information. So the person responsible for protecting the information will block everything. It’s more secure, but the user cannot do their job. So we can not lose all the controls because that will risk the confidentiality of the information. We need to find a way that it’s secure, but it’s usable. It’s pretty much on how we can balance those two concepts.

Maria Palombini
It’s very interesting because it’s always sort of the question – comfort or quality versus uncomfortable but more secure. This is just a question in life we all see. This is the balance that we have in everything that we do. One of the reasons why I invited you on this is because you bring the Latin America perspective. And when we were talking in Europe, they have GDPR where there is a consensus of governments who are following GDPR policy around privacy, but then when it comes to Latin America, you said there are some countries who may be a little more robust and others that are not. Are you getting a sense that those who are not are starting to embrace this concept of looking at regulation or protocols to sort of give more security? We know connected healthcare will be moving more and more into the Latin American region. Just try to get your perspective and maybe some insight on what you see going around.

Andrés Velázquez
We have some data privacy laws in Latin America. Some of them are actually very similar to what was created in Spain a few years ago. Those laws protect sensitive data, like the ones used in the healthcare industry. Pretty much the difference in the way that I can see in Latin America is the way they enforce it. And in some cases the law has just been approved. So we’re in the process of implementing the challenge in most of the cases, I think it’s in the public sector. That is the biggest sector or the biggest area that has healthcare systems. Actually, I was a co-author in a book published by the Mexican data privacy authorities on the law where I explained the biggest risk about data privacy in the public sector. Pretty much what I stated is that the local entities will not have the same budget, the skills or time to implement the same systems and protection as the federal government.

This applies to all the public hospitals and the way they are storing the patient information. Some of them only have the information on paper. They do not transfer that information to other hospitals or other entities. Some of them have their own systems, but they could be connected or not to others. Some of them pretty much outsource the processing and the managing of the medical records. And we have had a huge issue here in Mexico a couple of years ago. A person in Ukraine was spending his nights, looking for databases that will be published without a password. And he was able to find a database with 1.3 million medical records from Mexico. He contacted me and I helped him to figure out where it was from. That information was from one specific state in Mexico. Doing some investigation, I was able to find that they were trying to find a database administrator for probably six or seven months, but at the same time, they actually got a contract with the government where they have to store and process and manage the medical records of these patients in Mexico. All their information was available on the internet without a password. So yes, they probably decided to transfer the risk to another entity. But at the end, that entity was not able to secure that information. We actually brought down the information. We were sure that nobody saw it. We tried to contact that company. They said that they didn’t have anything to do with that, but the company a week later disappeared. We actually gave all the information we had to the local data privacy authority. And they actually tried to find them. They were not able to find it anymore, so it pretty much disappeared. So we have a law that will protect the sensitive data like these medical records, but now that their information of all these patients was affected. Now we can not do anything to bring it back as it was before. Yes. It’s going to be a penalty to this company, but in the end, the data remained on the internet for some time.

Maria Palombini
That’s 1.3 million patients that we’re talking about being exposed. So that’s very insightful. You have a technology background, and obviously you have to intersect with policy and regulators and with industry demand and boards of directors. And I asked this to all my guests – there’s always this debate that regulators and policy makers need to do more to require the engineers and developers of hardware and software, these connected medical devices and building more security features. Do you share a similar perspective that you feel policy and regulators need to step up more, or do you think maybe there needs to be more technologists to come together and collaborate and develop technology standards to address the problem? I’d like to hear your perspective since you intersected all these different domains as you go through this process.

Andrés Velázquez
It’s very interesting. Because I have been doing the forensic side of my company for a while. And one of the biggest challenges that I have been facing and working with with a lot of entities out there, like the Council of Europe or the United Nations, is that technology brings a different way of understanding how things work. If I have a case where someone actually accesses these medical records from another country around the world, at the end on the technical side it’s just a click. I don’t know if they are in another country that doesn’t have the law around cyber crime or not. So if I bring these to answer your question, there’s a huge thing that we have to consider and it is called jurisdiction.

I had to spend probably two years trying to understand jurisdiction in the way the lawyers understand it based on what I just mentioned. So when we’re talking about creating law around technology, you’re talking about controlling something in a jurisdiction. In the States, we have the HIPAA to address cybersecurity in the health system, but we don’t have that in Latin America. We just have these data privacy laws. So how we can interact in a world that is now connected, the information that data from these medical records was in a server, or at least some servers in the United States, not really in Mexico or in Latin America. Now we’re talking about globalization, it could be in any country in the world. If we’re gonna talk about law, we’re gonna be blind folded because that will only apply to some countries. Therefore, I prefer to talk about standards or best practices in some cases if we’re not able to carry standards, and then try to be able to adopt those standards globally, that we don’t care if there’s a law or not, we will be able to solve most of the issues that we’re facing.

Maria Palombini
That’s really interesting. And I’m so delighted that you brought up this point because often when we talk about healthcare without borders, being able to say “I can take my data and go into this other country, they’ll have my whole history and be able to take care of me.” And we’re also worried about the technologies in doing so, or the data taxonomies or the languages. But you brought up an important point, which is there is no harmonization of policy around healthcare data. So although we may have technology means we still have the challenge of policy. And as well, as you mentioned, just in general, the technology standards and data standards around all those things. So I’m delighted that you brought that point up because I tend to hear these debates on this whole arena quite a bit.

I thought this was very interesting coming from the US when you said to me we need the CIA for cyber vulnerabilities and anything from connected health in anything we do. Naturally I was thinking of the Central Intelligence Agency in the United States, but you are referring to those three letters or something else. So I would just want you to share with our audience what you were talking about when you said CIA and exactly what in reference to how this can be applied to this growing challenge.

Andrés Velázquez
The CIA is not really my vision. It’s something that we have to learn when we are starting cybersecurity. I need this called the CIA triad. That is a concept that focuses on the balance between financial reality, integrity and availability under the protection of an information security program. So when I tried to link it into the health sector, the settlements are very important. Confidentiality – that only the persons or the devices or systems that the law allows are the ones that are looking at the information integrity, or talking about that the information or the data is not changed without any record control or that it has to be changed. And I will really say pretty much that you can have information or data when you need it. Normally I mention two examples. The first one is about our bank accounts. I don’t want my bank account to be public. So that’s why it needs confidentiality. I don’t want my bank account to show a wrong number of how much I have on it. Well, if it’s over what I used to have, I will be happy. But if I access my bank account and I see less than what I had, well, I don’t want that to happen. And the third thing is, if I need to use what it’s on my bank account, I know I need to be available to me. If I move it into the health sector, what happens with this medical record? What happens with this device that is attached to me that needs the information that has to be exact, and it cannot be manipulated.

So those three concepts, we normally talk about with the decision makers. We need to make them understand that this reconstitution is the vase of cybersecurity, and they need to be linked to the strategy of the company that processes that we want to secure. So I don’t want my medical record to be public, to be changed in their content that could have an allergy that I don’t have, or the other way, and I need that record to be available when I get to a position that I need it.

Maria Palombini
Very important. Based on what we talked about today and all your experience, perhaps you can share a final thought with our audience on one of the most important call to action for an individual or a patient to take, for the overall healthcare domain, or for any other stakeholder, like wearable developers and connected medical device developers to sort of take that action or take something into consideration to move the needle on this growing challenge?

Andrés Velázquez
We’ll get back to how we started, talking about risk. So yes, for a hospital or a facility, the information that you’re receiving from your patients, all the technologies, like they are researching and developing new devices, please consider cybersecurity because that will help to solve issues right now, instead of finding out that later. There’s going to be an issue with either data or information on how the device actually works about policy makers. We have to understand that we have to find ways to make this something that everybody could apply, meaning that there are maturity models and we have to cover security. Now, not everybody is going to be in the highest range or the lower range.

We have to figure out how we can implement cybersecurity in a very strategic way that could be improving, depending on how everybody is working. And at the end to the patients, that is pretty much you, me and everybody that is listening right now. There are some risks, and try to understand how the entity, the hospital, the wearable, the medical devices that you’re using could have a vulnerability and something that could affect you. I’m not trying to be fatalist. I’m trying to be kind of real. With what happened with the COVID, we had to understand the risk to decide which controls we have to apply. And I have been trying to understand how much we can get from the COVID reaction to cybersecurity. And yes, on cybersecurity, we’re going to be as secure as the less secure person is involved in what we’re doing. It is a chain. So I will like to end with a phrase that I loved from a cryptographer in the United States. His name is, uh, Bruce Mayer. He says that cybersecurity is not a problem about technology, it is a problem about how we use technology. So don’t blame the technology, how we’re using the technology and who are creating new technology.

Maria Palombini
That is a very profound final thought. You’ve shared really great insight and concepts with us, and a lot of the things you’re talking about, we are covering in the IEEE SA Healthcare Life Science Practice. Most notably to our audience, we want to share with you. We are hosting a five-part virtual workshop series on global connected healthcare. And we’re doing this in collaboration with the Northeast Big Data Innovation Hub based in the campus of Columbia University in New York. And the series is designed to bring anyone who is involved in technology, either in healthcare practice, clinical research, regulatory research, or in general engineers to openly listen to some of the great concepts and new technologies that are out there, and most importantly, work together to identify and develop a framework to moving towards solutions, whether it be in the design of the products themselves into practice, or in where we need policy to step up and help support the overall goal.

This series takes place live in February, April, June, September, November. All of them are recorded on demand. If you’re not able to get to one or all of them, you can register for free at ieeesa.io/cyber2021. We also cover this in many other incubator programs from our telehealth paradigm, security, privacy, accessibility, and continuity for all. We have the decentralized clinical trials program, and of course WAMIII, which is wearables, medical, interoperability, intelligence. All of our incubator groups are open and inclusive. We welcome anyone who wants to contribute towards moving the needle on the challenge. You can learn more about all of these activities at ieeesa.io/rethink. I want to thank Andrés for joining us and sharing all this great insight and you, the audience, for being with us and continuing to follow us. We look forward to you joining our next episode, but until then continue to stay safe and well.

Maria Palombini
Hello everyone, and welcome to the Rethink Health Podcast. I’m your host, Maria Palombini and I lead the IEEE Standards Association Healthcare and Life Sciences Practice. The practice is a platform for multi-disciplinary stakeholders from around the globe, who are seeking to develop solutions for driving responsible adoption of new technologies and applications that will lead to more security, protection, and universal access to quality of care for all individuals. And with that, I would like to welcome TR Kane from PricewaterhouseCoopers to the podcast today. He’s been working in the area of patient privacy to address the risks of the cyber world across a technical discipline. Currently, his role is Cybersecurity and Forensics Partner, Global Third Party Risk Leader, US Strategy and Transformation Leader at PricewaterhouseCoopers. So TR, can you share with our audience a little bit about the great work you’ve been doing at PwC? And some of the things that you’re seeing like trends and global challenges from where you’re sitting right now?

T.R. Kane
Yeah, you bet Maria. So I’m seeing a number of trends facing healthcare, with first being really the increased use of third parties. If you think of healthcare organizations, whether you’re talking pharma, providers, or even the payers, you have this ecosystem of data and trust, that continues to expand from organizations directly controlling it, to really placing more reliance on contractors, the cloud, suppliers, business partners, and vendors that have effectively become the key components of those healthcare organizations processing, storing, manipulating, transferring, regulated patient and even employee data. I think the second thing that I’m really seeing and where I spend a bulk of my time, is really the need for tying business and cyber risk. It’s greater than ever, from medical devices to technical platforms, expanding platforms within healthcare to patient care platforms as examples, that all must be managed, they need to be monitored, and they need to be reported upon effectively. So I’m getting a lot of demands and asks for calls and even at the board levels around how we get cyber risk aligned to patient safety and business outcomes.

Maria Palombini
So what we’ve seen in the world of cybersecurity has been this focus on prevention, like how do we stop the problem before it happens. That’s what we think is the best solution. However, we’re seeing more of a trend, and you mentioned this earlier, towards risk mitigation, this concept of forensics in the whole episode when these breaches in this quote unquote warfare starts to happen. So maybe you can explain some of these concepts to our audience and why they’re just as important or more important, rather than just working on the prevention, the vaccine for the problem and how we’re actually looking at preventing the risk in that situation. And maybe what you see companies doing better or not so great in embracing this concept, in better managing risk overall in a connected healthcare system.

T.R Kane
First and foremost, connected healthcare platforms are really increasingly touching patients and expanding across the healthcare industry. So one of the things not just from a risk perspective, but from a trust perspective, it’s becoming the core of the focus coupled with the mechanisms to manage risk that lends itself to establishing that very trust. As platforms are rolled out, even risk management oversight, technical forensic investigative capabilities, and other detective technologies, the industry really is starting to look at more independent organizations to help edify the trust gap. So things like tie trust, getting those independent outputs, but also having a strong cyber and privacy set of embedded controls around their patient and clinical healthcare platforms. And what I mean by that is, we can’t just simply rely on an independent third party to check the box. It’s really how we embed new products, medical devices, the rollout of technology, even acquiring. There’s a lot of M&A activity within healthcare right now. How do we ensure that we have the right governance and the right processes to really embed the controls to protect the very data that we need to protect, i.e. privacy and the mechanisms being security. And it’s really striking that right balance between the patient and doctor experience, compliance, risk reduction, while also managing costs in concert.

Additionally, more and more healthcare companies are starting to use endpoint detection and response. So different EDR solutions to help gather data from endpoints. But I think this is the key, while it is still reactive in nature, it does help begin to mitigate risk once an attack has been identified. However, it’s not a proxy for overarching cyber risk management, and the alignment to organizational risk and business outcomes. It’s reframing cyber risk as a business risk and not taking that legacy view that cyber is just a technology risk. I think the last thing that’s also very important as we’re seeing organizations, as I think about risk, mitigation and detective capabilities, is aligning specific playbooks around incident response and resiliency. So playbooks around what we do with medical devices for each? How do we handle phishing? How do we handle ransomware? That to me this is very important because you’re cross threading all the different organizational constituents that need to be part of those business risks, not just treating it solely as that cyber responsibility to respond, handle, and mitigate, because it’s not.

Maria Palombini
We see an emergency and companies start throwing money, quote unquote, at the problem investment. There’re figures ranging from 100 million US dollars plus to be invested in the next five years to 15% increase in cybersecurity measures. It’s not just about throwing money at the problem, right? What is it that would be the most effective way to invest this money so that these organizations can get the best return on investment for the money that they’re putting into the problem?

T.R. Kane
I’ll tell you this is probably the number one set of discussions around this topic that I’m having with executives. And what we’re really seeing is the need for cyber risk quantification. It’s the trend we’re seeing grow exponentially. So directly aligning risk and controls to prescriptive calculations of associated dollars for those risk controls or quantifying the risk of not doing something. I.e., what’s the cost of a record for a breach times the number of records a provider maintains, equals a specific dollar value, plus compliance penalties? CIOs and CISOs alike are really starting to learn that their boards and specifically CFOs really want a better articulation of why am I spending this percentage of my organizational dollar on specific initiatives. They want alignment of the cost, the risk, and the business outcome versus hearing. We have X amount of tools, we scan X amount of endpoint devices every month, and we have anomalies detected in our environment. That is unquantifiable. And it’s not actionable for a board or even an audit committee. So CISOs and CIOs alike are really pivoting their agendas, to be risk based and risk quantified to directly align to their business stakeholder expected outcomes.

Maria Palombini
One of the concerns we keep hearing about similarly is, hopefully this money is going to be used in a way that’s going to deliver. So let’s see how that goes. We have this constant debate that regulators should do more or should require developers and software engineers to do more. I guess the question is sitting from your perspective, do you have a similar perspective where regulators need to step up and start making these mandates in, or do you think this is more a market driven approach incentivizing these technologists to embrace this concept to start delivering on this idea of more security and more protection of privacy?

T.R. Kane
Specifically around medical devices, net new products that are emerging into the healthcare industry. They’re just simply not enough regulatory protocols, controls, and oversight, like you may see from the OCC and the FFIEC and financial services. So I think there’s a greater need for regulatory monitoring and enforcement. And those are both important. Because monitoring doesn’t necessarily mean tickets are being written, I think you need to have real enforcement and look at the clear difference between financial services and the enforcement of their regulations. There is a clear difference in response and reaction when systems or products have been exposed due to a breach in financial services versus healthcare. So I think if you’re gonna move the needle, you need to have healthcare regulatory bodies set standards, but I think it needs to be in cohort with medical doctors and the broader medical community, but also with the manufacturers to align on those standards. It shouldn’t just be at the policy level, I think it needs to go a level down at a technical security level, and not just be a guideline, not be a recommendation, but be a federal mandate with defined penalties for non compliance that are tracked, reported and enforced on an ongoing basis.

Maria Palombini
What do you see as the greatest cyber threat and consequence in the healthcare system that maybe others are not fully migrated to, or maybe it’s just not gotten the whole exposure like we think it has been?

T.R. Kane
The attack surface has grown exponentially across healthcare organizations. And when I say exponentially, it is moving at a velocity faster than healthcare organizations budget to keep up with them. So if you think of healthcare interconnected ecosystems around biomedical devices, mobile phones and devices, laptops, mobile workstations within hospitals, all the way third parties are being leveraged for outsourcing data and data handling, the greatest threat becomes the lack of clarity around where my data is, how my networks are segmented, how I’m effectively monitoring third party risks, and the emergence of cloud based solutions, which really has enabled business leaders to pursue digital solutions without always interacting with or betting cybersecurity until it’s post contract. And I think that’s when you start to see data risk exposure, when you haven’t kind of taken a step back to look at, are we programmatically thinking about how we’re going to have a business outcome, with the right level of control, protecting both patient health safety, as well as patient data safety.

We’re at a revolutionary point. And I know that sounds bold, but we are at a revolutionary point in history with respect to access to data, enter connectivity options, use of medical devices, and how those medical devices connect to other devices. And this increasing attack surface that malicious actors are preying on and the velocity by which emerging healthcare treatments are being introduced and performed, as well as the mechanisms by which data is stored, and by whom is continuing to increase with use of the cloud. Knowing that the health care organizations, the government, and independent firms alike are trying to move at a similar pace is important for folks to know. The threats are known. The velocity by which medical providers and technologists and independent assessors and consultants are trying to attack it, it’s not quite there, but I think folks are really doubling down. So my recommendation, you know, for the audience would be kind of in the meantime be safe, stay healthy, and look out for one another and know that your clinical and technical teams are really doubling down to protect you.

Maria Palombini
You have shared so many great insights today and I want to thank you for joining the conversation and being with us. And many of the concepts TR mentioned today are just in various activities that we have at the IEEE Standard Association Healthcare and life Sciences Practice. And most notably, we are doing a five part virtual workshop series on global connected healthcare cybersecurity, I invite you to visit ieeesa.io/cyber2021 to learn more about the series, so if you want to get involved in any of our work, I invite you all to visit our website at ieeesa.io/rethink, and we look forward you to joining us in our next episode until next time.

Maria Palombini
Hello everyone, and welcome to Season Two of the IEEE SA Rethink Health Podcast Series. I’m your host, Maria Palombini and I lead the IEEE Standards Association Health and Life Sciences Practice. The practice is a platform for multidisciplinary stakeholders from around the globe who are seeking to develop solutions for driving responsible adoption of new technologies and applications that will lead to more security protection and universal access to quality of care for all individuals. I would like to welcome today Ashish Mahajan, for a discussion on how cybersecurity and connected health can be an accelerator for more innovation. He is the Non-Executive Director of IoTSec Australia, and he’s Chair of IEEE SA IoT Ecosystem Security Industry Connections Program. So with that, Ashish, why don’t you tell us about the great work you do in IoTSec, and then a little bit about this industry connections program you’re leading at the IEEE SA?

Ashish Mahajan
Certainly. I want to start by saying the IoT space is expected to grow to 25.1 billion by 2025. And that could be worth up to 26.1 billion by 2027, with the compound growth around 19.8%. This growth we’ll see in the next five to 10 years. But what it means is that it will likely have touched every aspect of our life from our refrigerators to our shoes, to medical devices, to car automation and home automation. And of course, cybersecurity remains a key issue concerning broad technology, as well as data related activities. So while IoT devices can greatly increase the productivity of our business, there’s an old saying that new rewards come from new risks and cybersecurity of IoT devices is a big challenge for us. Now, the work that we are doing at IoTSec in partnership with IEEE is to bring them in across the community. IoTSec is a not-for-profit organization, it looks at advocacy on the research initiatives that helps to ensure the proper awareness or the awareness of the secure practices by the ecosystem and we will be working with IEEE SA to publish white paper, reports, proposals for standards, guidelines, and probably webinars to bring awareness across our community.

Maria Palombini
I know that IoT across multiple industry domains is flourishing. It’s really important to call out the fact that it’s not just about medical devices. There are so many devices on or around us that are not obviously specific for medical application, but still impact our overall wellness and daily lifestyles and things of that nature.

Ashish Mahajan
I always say, when it comes to IoT and security, the industry is too late to consider security and we are kind of catching up to embed security in IoT devices and also the future IoT devices.

Maria Palombini
Cyber breaches and security vulnerabilities are a major concern, when we think about the current state of connected health devices and obviously the trajectory for the future of mobile health. From your expertise and your experience, what do you consider to be some of the major impacts if cybersecurity and digital health space are not addressed effectively?

Ashish Mahajan
I guess there are two folds to this question – the trajectory of the future of mobile health. Now in the past few years, there has been a cultural shift and a technology shift from variables focused on promoting wellness to those designs to post real time tracking and also the monitoring of patient vital signs. According to research, the average person is likely to generate more than 1 million gigabits of health related data in their lifetime. As you can tell, this technology has huge potential to not only improve health literacy and wellness levels, but also to reduce global health. According to one estimate, remote patient monitoring might have saved nearly 200 billion across all conditions over the next 25 years. If you consider this, being able to remotely monitor patients in their home is a significant opportunity for caregivers and for industry alike. And most importantly, for the patients, this is going to change the whole gimmick of how patients will be treated at hospitals and remote patient care, not variable technology. There are agents that are also propagating a cultural shift in how conventional drugs and therapies are formulated and delivered. If I remember correctly, 2017 saw the first FDA approved pill that was packaged sensor tracking patient usage. Now that was a dramatic change in how patient care can be done. The other question is the major impact of cybersecurity challenges in the healthcare sector. The healthcare sector is going where the IoT devices are going and where the patient care is going. While IoT has opened up the door for innovation or innovative new services across industry, the adoption of the IoT system within the healthcare sector is crank. And that’s why the numbers are huge.

The other risk is that the cybersecurity risk is now among the sectors most targeted by illegal markets globally. The predicted health information is more than what you create. Now, I think the question is why, and it’s due to its immutability, the state of not changing the information exists to help data breaches of particular interests or cyber criminals because your blood type doesn’t change for your personal health information contained in your medical file along with insurance and help provide information that is not going to change. There is a higher motivation for cyber criminals to target medical databases. If you look at the most recent research in the past few years, 83% of the medical imaging devices are running on unsupported operating systems. I guess the question is why. And the answer is because healthcare is always about saving patient’s lives.

Maria Palombini
It is amazing how much data these devices can generate. And we thought the human genomes could generate that much data, but we seem to have quite a bit of a proliferation of data. But I think it’s a very important fact that you highlight, because I think people often miss is that health data is so rich with immutability that it becomes so much more appetizing for cyber criminals. It’s definitely true that a credit card, you take it, it gets stolen. You call your credit card company and they erase it and get you a new one. It’s all fixed, but who do you call to say, you know, my blood types have been breached. Like there’s just no ID help desk here. So I think it’s a very important fact. And you know, many have argued that regulators should be doing more from a point of view of requiring the developers of the hardware, the software, and connected devices with regards to building in more security and protecting those vulnerabilities from an engineering perspective. How do you perceive the problem being most effectively addressed?

Ashish Mahajan
Very good question, Maria. I recall giving a presentation in 2018 where I talked about that everyone has a role to play from enforcing security to devices, to understanding the basic security advice. And I’m talking from regulators enforcing security controls that enable security in IoT devices to organization and practice, they choose to make a conscious choice of that using those IoT devices. Most regulators have just started to consider recommendations in this fast evolving setting and are moving slowly. Manufacturers are creating an incredible variety and volume of IoT devices. 5G devices should be prioritizing security by design, especially considering the potential detrimental consequences of a breach. We are stepping in the right direction and I’m going to take a couple of examples. Here is the California IoT law, that requires manufacturers to equip the devices with reasonable security features, regulators shouldn’t force what needs to go bare minimum in the main IoT devices as part of their implementation. Consumers should be able to make a conscious choice. Should they be using the IoT devices without risk management? For organizations also, do you want to use the IoT device? Should we be using the IoT device? What is the consequence of using this IoT device? What if the breach happened? I think those sorts of questions must be asked. The responsibility starts from regulators. They need to enforce. Then it goes to manufacturers. From manufacturers it goes to practitioners, and practitioners could be consumers also.

Maria Palombini
Very interesting. I think it is an all hands-on effort. One of the interesting aspects is we all want to know what’s going around the globe. Do you find that what you see in Australia differentiate from other geographic regions towards addressing this issue of the need for cybersecurity and the use of IoT and these mobile health apps and wellness applications?

Ashish Mahajan
Today, consumers across the globe are taking an increasingly proactive approach to manage their health. And technology is playing an important role. One in six Australians use mobile apps and variable technology to track nutrition, exercise, sleep patterns, energy levels, and even stress. And with that number of connected wearable devices worldwide expect to grow over 1.1 billion by 2022. From a health care practitioner’s point of view. They’re now adopting these technologies for patient monitoring and to drive improved health outcomes. Not just in Australia, it’s probably the trend that we see across the globe.

Maria Palombini
Obviously Australia was one of the first regions of the world to come out with a contract tracing application for COVID-19. We know that COVID-19 disrupted many of our norms and introduced new ideas. Some were great. And some maybe not so great. I know that contract tracing apps globally did not do well. There were a lot of concerns with them, but were there some concerns specifically in Australia, citizens about privacy and data security? Did you see any special way of addressing and mitigating it that you would like to share with our global community from that point of view?

Ashish Mahajan
To answer that question, I’m probably going to talk about why aren’t COVID tracing up more widely used. As you know, we’re in the flood of coronavirus apps that were launched in the first half of 2020 across the globe to quarantine the infected individuals. That was the intent of that. And the true promise benefits of these contract tracing apps have not been realized to the full potential anywhere in the world, but the Australian government launched the COVID CFR. And there were clear concerns by citizens regarding trust, transparency, security, and privacy. Among that, user acceptance was the biggest challenge for many reasons. And if we consider from a technology point of view, there were concerns about the battery consumption now from a security and privacy. There have been serious concerns around user data. The COVID apps used to ask our users for their name, phone number, postcode, and the age range before they can register with the app.

Ashish Mahajan
The question was how well the application was tested in the way that data is stored? And the next question is the reliability and effectiveness of that. There is no rule for testing or approving the accuracy and reliability and effectiveness of contact tracing apps. And at the same time, I don’t think that there’s anyone to be blamed. We are facing an unfortunate global pandemic and everyone did what they could do. Some things worked and some didn’t. The one that didn’t work for us, we should take that as a learning for us.

Maria Palombini
Any final thoughts you would like to share with our audience?

Ashish Mahajan
Security is everyone’s responsibility. And I would like everyone when they are going out in the market and buying not just the IoT device, but any device. They should understand some basics of security to make sure our community is safe and secure.

Maria Palombini
I want to thank you for joining us today and sharing this wonderful insight, and I will thank you, the audience, for tuning in. I just want to share with you all that many of the concepts in our conversation with Ashish today are addressed in not only the IoT ecosystem security industry connections program, but we have many different industry connections programs within the healthcare life science practice. Our work in telehealth connects to the accessibility and security for all. And obviously the work we’re doing in decentralized clinical trials, as well as the work we are doing in cybersecurity. And this podcast, season two is going side by side with a full year virtual workshop series we’re doing on global connected healthcare cybersecurity. Both information on that opportunity is at ieeesa.io/cyber2021. If you want to learn more about the Healthcare and Life Science practice, get involved in any of these programs we talked about today, or you would like to instantiate a potential program, please reach out to us at, ieeesa.io/rethink. And with that, I want to wish you all to continue to stay safe and healthy and look forward to you joining us next time.

Maria Palombini
Hello, everyone, and welcome to season two of the IEEE SA rethink health podcast series. I’m your host Maria Palombini and I lead the IEEE SA Healthcare and Life Sciences Practice. Coming off the premiere season introducing some of the more inspiring technology compelling us to rethink the approach to better care for all, this season, we will focus a little bit more on the growing threat that could impede the trusted adoption of these great technologies and applications. And we’re going to bring experts from all corners of the globe to talk about the regulatory technical application side for connected healthcare systems and where cybersecurity is the pediment to getting trusted adoption. When we look at all the IoMTs, the artificial intelligence, the blockchain, or traditional health wearables. Today, I’m very excited to have with me, Florence Hudson, she’s going to be talking about the growing challenges and alternative ways to address cybersecurity in a connected healthcare system.

Florence Hudson
Thank you, Maria, for that wonderful introduction. I’m delighted to be here today and to be able to speak with all of you about this very important topic, and also to share opportunities for you to consider how you can participate from anywhere around the world to join us in this effort. I’m the Executive Director of the Northeast Big Data Innovation Hub headquartered at Columbia University in New York. I lead one of four big data innovation hubs funded by the US National Science Foundation. And we are a collaboration hub, a community convener and a catalyst for data science innovation. And as you know, in connected healthcare, it’s all about the data. How can you leverage the data? How can you move the data? How do you access information about the patient, and the medical records? And then how do you keep everything secure and protect the patient? So that’s one of the key areas we’re focused on. In the Northeast Hub, we partner with the other three NSF Big Data Innovation Hubs around the country, and through IEEE and other activities like our COVID Information Commons and partners to extend our reach around the world.

And I’m very fortunate to be the chair for the IEEE UL, which is IEEE and Underwriters Laboratories working together. Our P2933 Standards Working Group on Clinical Internet of Things Data and Device Interoperability with TIPPSS.

Maria Palombini
And for those of you who don’t know what TIPPSS means, it’s trust, identity, privacy, protection, safety, and security.

Florence Hudson
And TIPPSS is a framework that we envisioned with IEEE, actually in February 2016, at an end to end Trust and Security for the Internet of Things workshop at George Washington University in Washington, DC. And we’ve made tremendous progress since then, on better understanding the challenges and risks and connected healthcare and clinical IoT related to TIPPSS. And what we’re doing as a standards working group is envisioning the technical and process standards that we can recommend to improve the trust identity, privacy, protection, safety and security, with the purpose to enable secure data sharing, and connected healthcare that improves healthcare outcomes while protecting patient privacy and security, and mitigating risks in data and patient protection and safety. Everything is hackable. So all this great technology we’re using also creates risks. So anyone who wants to join us, they can. You can look up IEEE P2933. You don’t have to be an IEEE member. And it’s free to join.

Maria Palombini
Well, thank you very much for it. So when I first met Florence, and we were sitting I believe in a car in a taxi together, Florence happened to share with me that she was an aeronautics engineer. And I’m looking at her, I’m like, do you know how the planes work kind of thing? And she was like yeah. But now you’ve gone into health care. So maybe you could share a little bit what motivates your passion to be involved on the healthcare side of things?

Florence Hudson
I’m really trying to protect the humans very honestly. My mother died the day I was born. And of course, I couldn’t protect her then. So I’m always trying to keep humans alive. It’s just a general need that I had. And I know being a technologist that the connected healthcare devices are hackable, the data is hackable, the sensors are hackable, the actuators are hackable, there’s way too much bad stuff that can happen. I feel like it’s our responsibility as the technologists and the providers and people who care for patients to work together to keep the patient safe, as well as to leverage technology and data to improve healthcare outcomes.

Maria Palombini
We are collaborating on a five part virtual workshop series focused on cybersecurity for a connected global healthcare system. And IEEE SA Healthcare and Life Sciences Practice, the P2933 group, and the Northeast Big Data Innovation Hub are all collaborating to present the series. So what do you envision as the objectives and goals of this five part premier series that we’re doing in 2021?

Florence Hudson
So at the Northeast Big Data hub, we actually have a cybersecurity risk initiative. And we have an award. Some funding that goes along with that. And we did an initial workshop about a year and a half ago. And we talked about Internet of Things. we talked about clinical IoT, and then some other aspects. I decided that because I’m leading the P2933 Working Group and working so closely with you and IEEE Standards Association, that this is a great opportunity to go deeper. It ties in so well with the health focus area at the hub with a responsible data science focus area at the Hub. Before I took this role at Columbia, and the Northeast Hub, I was actually working for the NSF Cybersecurity Center of Excellence, Indiana University. So this is like my zone.

What I want to do is to help us work together to increase awareness about these challenges, these TIPPSS, challenges and trust, identities, security, and privacy and safety, and then help us work together to address these challenges. So through these workshops, we want to invite everyone who can to participate. Then what we want to do is funnel our work from workshop to workshop and then into the standards efforts.

So as an example, the first workshop, which is the global connected healthcare, cybersecurity risks and roadmap workshop, will have us talking about the specifics of security. And then what are the other elements, what’s going on with privacy and ethics? What about interoperability? We actually lay the groundwork. What are the challenges? What could a potential roadmap look like? What could we possibly do in the future?

We look at where we are, and we envision where we could go. The next workshop is privacy, ethics and trust and connected healthcare, which is a very important topic, a lot of new policy and regulation is coming out. And it’s very related to security, because you need the security for privacy. So it’s very connected. But we want to go deep on the privacy as well as the ethics and the trust related to that. Then the next workshop, building what we continue to build is on data and device identity, validation, interoperability, and connected healthcare, when we’ll talk about how do we maintain trust; how do we validate identities of the devices and the humans and then working with each other; should this device trust that device, should trust that human, should that human trust that device. There’s a lot to think about. That would be the third workshop. The fourth workshop is around connected healthcare Integrated Systems Design bringing this all together, what does this whole picture look like; how do we leverage artificial intelligence machine learning to potentially improve the integrated system design, identify potential risks, and then do something about it. And then the one in November is connected healthcare technology and policy considerations. In our first workshop in February 2016, where we created the TIPPSS framework, we actually had an IEEE technology workshop, a technical workshop in security for IoT. he next day, we had this Etap workshop, which is for experts in technology and policy. And so our vision here is to get more of the policy people involved, then we would have people from all around the world and regional experts as well regarding GDPR in the EU, HIPAA or new things in the US and other areas. We can talk about the technology and policy considerations from multiple perspectives, and then decide from there what would our recommendations be? Do we actually want to have deeper discussions at a regional level because the policy is so different, and those are the type of things that we can work together.

We want this to be very collaborative, where we’re identifying the problems together, and identifying potential solutions together, and then funneling that into some of the standards work if people would like to get more involved.

Maria Palombini
All of the workshops will be available on demand. If we cannot join us on the live date, we can definitely make sure you catch us on demand and all the information is available on the cybersecurity workshop series website, which is accessible from the IEEE SA Healthcare Life Sciences site, just click on cybersecurity workshop series. How do you think this workshop series can really move the issue on cybersecurity?

Florence Hudson
What we decided is that we would have the first workshop to kind of talk about the overall connected healthcare cybersecurity risks, then roadmap, but then go deep in each workshop so that we can pull it apart. Look at the problem, find the right tail and the right wing and then put it together with the fuselage and make it fly with the standards working group P2933. We welcome people to funnel into that with us. And we’re hoping we find new people to come in and add to the solution.

Maria Palombini
If people want to get involved, what would you say to them? Like, why should someone who’s an expert in any of these fields want to be a part of this particular workshop?

Florence Hudson
That’s a great question. I’ll give you an example of someone we’re very excited who is involved with us in our region in the northeast, Julian Goldman, who’s at Mass General in the Boston area, as well as at Harvard. And so he’s going to be our keynote speaker in the first workshop. He’s had the integrated clinical environment view that he’s had from a technical perspective while he’s a doctor, and we hope that as they come in, they’ll be able to leverage their expertise as a device manufacturer. One of our vice chairs of P2933 is William Harding, who is in the Technical Fellows Leadership Program at Medtronic. Another one of our vice chairs is on the provider side. He’s the chief information security officer at Indiana University Health, Mitch Parker. Our secretary is at Draeger Medical Systems, Ken Fuchs. We have people from Cerner, we have people from all sorts of organizations. So you can all be part of the solution because we all see a different part of the problem, looking at the elephant overall for the series. The learning outcomes include understanding the risks and threat vectors and connected healthcare and IoT systems, advanced technologies that can be leveraged, as we discussed to address these risks and societal challenges. And then standards efforts in related technology and policy opportunities to address the risks. So it’s really understanding the challenges, and then seeing how you could actually get involved to be part of the solution. Registration is free. We look forward to engaging our region as well as the world in this challenge and opportunity together.

Maria Palombini
Thank you so much, Florence. And I want to thank everybody for tuning in. This is obviously an area of important interest for any single person, any patient that’s interested in this area, you can access information about the global workshop series off the IEEE SA Healthcare Life Sciences Practice site, which is easily accessible at ieeesa.io/rethink. And with that again, Florence thank you for joining me and we look forward to seeing you in one of our workshop series this coming year.

Maria Palombini:
Welcome, everyone, to the next edition of IEEE SA’s Rethink Health podcast, today. We’re gonna be talking about the great debate in contact tracing technologies and applications ethical considerations and protecting personal privacy and public health. I’m your host Maria Palombini. I’m the leader of the IEEE Standards Association Healthcare and Life Sciences practice.

You may want to why are we doing this podcast series. There’s so many new technologies applications, scientific breakthroughs and more frequently. Recurrence of unexpected, natural disasters such as pandemic. That makes us really have to think, how are we going to rethink the healthcare system, so that we can deliver better care for you me, and anyone it was a patient we’re all patients? So we all should have the right to better care. This series will feature guests for technology, ethicist, clinical, medical researchers, advocates, and any other committed or passionate stakeholder who is pushing the boundaries in our approach to better healthcare.

We’re not just talking about bedside practice or therapy development. We’re looking at any aspect that impacts our care. And how do we make it better? And how do we make it universal for everyone? So, with that today, I would like to welcome, Ali Hessami, to our discussion. He’s going to talk about this contact tracing technology. An application that is a very hot topic, thanks to COVID-19. They’ve been around for a while, but now they’ve come to a center stage and it’s something we’re all debating public health versus private, a private personal data privacy.

So, with that, I want to first, thank you Ali for joining us and welcome to the series. Tell us a little bit about the work you do as innovation director of biggest system, but I know you’re heavily involved in a lot of the work and IEEE SA’s ethics programs. So, perhaps you can give us a little information about that.

Ali Hessami:
Of course, my role and regular systems has been really largely focused on tackling critical problems through innovative, technical technology, and solutions basically. So that borders with many aspects, such as system systems engineering, that’s my general background as a physicist as well as knowledge and risk management practices that I’ve been doing over many decades in industry, largely at the top involvement in the academic research publication and teaching. I got involved roughly four years ago being an arguably member for over thirty-five years. But with SA, I got involved with P7000 technology, ethics standard initially, as a working group member and ultimately honored to accept leading work as a chair to basically process manage and architect and approach to ethics certification. For SA, I was given a very brief free made and since then I’ve been largely involved in the ethics certification program for autonomous, and intelligence systems. For short. We have been exploring what kind of qualifications are needed for technology embedded products and services, largely autonomous and a category to make them ethically acceptable societally and make them successful. And one latest initiative has been the application of similar approach on thinking towards contact tracing and proximity tracing, risk mitigation technologies

Maria Palombini:
So, when it comes to everything being virtual, and we have great experts speaking on our podcast. But I always like to humanize the person behind the expertise. Perhaps you can share with us. You’re very passionate about this topic. And I know this, because I see all the different people involved the P7000 series and the ethics programs. Maybe you could share a little bit about what personally drives you.

Ali Hessami:
If I may indulge – I’m a follower of mysticism of the Eastern nature, a couple of people I revere in my life had private life. These people are really focused on paths to fostering harmony into society and spirituality. I can just quote from my favorite work from Rumi. He says this world is the deep trouble from top to bottom, but it can be swiftly healed by the palm of love. And that frankly translates into what can build bridges for good will and understanding the barriers being encountered in life. To me, ethics, respecting other people’s differences is an excellent bridge building environment. That’s what enthused me to get involved in P7000 series of standards and a number of them indeed. I’m later greatly honored and embraced the responsibility of developing ethical certification criteria, again with the same aim to promote a faster ethical value in technologies that’s ultimately device for the benefit of humanity.

Maria Palombini:
Great, thank you. And for our audience who may not be familiar, IEEE has a globally renowned initiative on autonomous systems. You can definitely find it on our website at https://standards-dev21.ieee.org [or a link in the resources section of this blog post], if you’re interested and just as passionate as Ali and the rest of the hundreds of other individuals who are participating in those projects.

Right now, I want to get to the core of what we’re here for – contact tracing technology. So we know they’re in the news. Everybody’s talking about it thanks to COVID, but they’ve been around for a while. It’s just not so widespread. Most people don’t know that, but in your research, what does it actually mean when we say a contact tracing technology and applications, regardless whether we’re using for an infectious disease, such as COVID or some other public health matter?

Ali Hessami:
Going back to the story around how human societies effectively and globally have responded to the threat and the major scourge of this pandemic, we have really not been very successful. We haven’t been prepared adequately. We haven’t responded with sufficient insights and effectiveness. It gave us the impression that as IEEE’s tag line implies we are really trying to contribute to the advancement of technology for the benefit of humanity. Since there was already an ongoing project on ethically qualification of products and services, in consultation with the Managing Director of SA and we managed to agree that the line of work on how to make contact tracing more successful globally, as the current only technological solution that we have available to us to mitigate the risks of the pandemic would have been in line with our strapline and our philosophy in IEEE.

So, contact tracing is basically using any form of technology or proximity tracings sometimes, to identify how close we have been to other contacts in any context, family, social, general public contacts. In the event that one of those people who have been in proximity with ourselves have tested positive regarding possibility of having caught the virus, then it informs others to take protective measures and stop this spread. So any technology, whether it’s an application that you download on your mobile device to any valuable technology is subject to the study that started some eleven weeks ago and in a fairly fast track project, we managed to get to the bottom of essential ethical that captures any such technology and not just a particular application of it that is necessary to the public trust in these technology, so that they will become more effective and ultimately end up saving lives.

Maria Palombini:
For sure. It’s definitely something. I think people still grasping, from a common citizen to technologist to everybody. In the last six to eight months since contact tracing technology started to surface, we’ve seen various challenges with them, whether it be some sort of central repository information, or we find that they’re using a Bluetooth proximity tool, so that you could see somebody within fifty feet, your app would dictate that that person has it. All of these as with anything they come with deficits. So what are some of the deficits that you’re seeing in these tracing technologies or applications that you really feel that the technical community, ethicist, scientists, or whoever has to come together to ensure that we have citizen consent to participating them but as well as that we can safeguard confidentiality.

Ali Hessami:
Indeed. If you look at the history, and this is only the last few months of successes and lack of successes of rolling out these technologies as the short term solution, while we’re still waiting for vaccines against the virus. To imagine the global community, technologically, this is one of the very few promising solutions that we have. But as any technology, this has been a quickly put together as a means to an end in the sense that the end is to try and reduce contamination, reduce the spread. And this is one very simple and technically a feasible solution that we don’t need to do a lot of R&D on.

Of course, on the downside, there are many dimensions, but those mentions are often to do with ethical properties in terms of: How transparent is the way technologies operate? Who are behind these developments? What is the mindset? Is there a clear concept of operation? Is there a reasonable attempt of ethically architecting such solutions, so that our data are not kept on central servers and hacked and abused? Is there any form of confidence in the ecosystem behavior? It’s not just the technology, it’s the other players. And all of these, including how do we operate and how do we keep vigilance during the operation. And eventually the demise and retirement of such technology, whether it’s a downloadable app or electronic product.

Technologies have got some shortcomings such as lack of precision in proximity measurement, what does exposure mean, how long is long enough to be considered to be at risk. Because it uses Bluetooth low energy that’s embedded in most mobile devices for other purposes as means of proximity detection with other people. On the ethical side, matters of transparency in communicating with the society citizens you’re trying to protect, how is the device architected? How is the overall operation? What are our stakeholders? Who would have access to our data? Would it be shared with other government agencies, et cetera? There’s significant lack of transparency in such matters. Governments, rushed by desperate necessity to come up with a solution to get out of lockdown and go back to some form of normal economic activities are rushing these technologies from private enterprises without sufficient clarity or transparency.

The second part is lack of sufficient accountability in the sense that we want to know who are the key decision makers, where our grievances go, when things go wrong, who are the responsible people or bodies or entities especially since we are talking about massive, large scale adoption and implementation of such solutions in such a hasty manner. The formal aspect is matters of privacy. We know that in Europe, we have protection of privacy by legislation called GDPR. But we’re talking about ethical privacy: in what manner our personal data is respected and regarded as private to us, rather than become some entities’ property, whether it’s a public entity, government entity. etc.

So these are three matters where the focus of the fast track study that we started sometime in late June, and they managed to put a fast interim report on what kind of actions, behaviors and practices on policies can safeguard against abuses in accountability, transparency and privacy. Hence a report was issued in July as the interim report, and the team and myself, have been working hard to complete this study. I’m pleased to announce that the studies being completed. Now we are in the final stages of putting a more comprehensive set of criteria on a report that’s going to be shared by SA as a Creative Commons global attribution, as a non-commercial product, where the whole international community with the focus of helping governments – city and states, public and private duty holders – to actually declare how they have gone about preserving these attributes of privacy, transparency and accountability in the architecture and the solutions that they’re rolling out, providing trust and confidence in the public and more effectiveness of technology to save lives.

Maria Palombini:
I can very much sense your passion and your advocacy for this work. I mean, you already answered two of my next questions on transparency and accountability, because I was having the same concerns of wondering how you all were addressing them. Now we’re coming to our final segment, which is an action. We need to take an action, right? The idea of Re-Think Health is that we want to actually do something to make it better. In this case, I know you’ve already sort of previewed the paper and we’ll leave that to the end to tell the audience how they can get to it. But there’s a lot of stake because I believe that contact tracing technologies, thanks to COVID, maybe sustainable and used in other applications. So I think we need to understand what will allow it to be sustainable, but in a way that people feel like it’s responsibly used and we can establish trust in the use of it. Where do you and the team feel like it’s needed there?

Ali Hessami:
Well, when we started this work, we were all passionate about how quickly we can generate a workable, comprehensive solution for supporting governments’ and private and public enterprises’ efforts towards rolling out such mitigation technologies against the pandemic. We actually decided that the most insufficient time and huge urgency with sensible parameters in terms of ethical assurance. We tapped into the work, the ethics certification program that we have developed prior to COVID. Last year we developed three sets of ethical criteria for certification of autonomous and intelligence systems on ethical transparency, accountability, and freedom from unethical bias. And we decided that the best solution was to adopt one of those and configure, adapt, modify and tailor that to the needs of contact tracing.

Fundamentally, it was around accountability and transparency models that we had already developed and these models have a huge body of criteria for ethical assurance. We basically decided that, because of the urgency, we couldn’t afford the luxury of a comprehensive ground-up sort of green field site study. We could build on some of the criteria that we already had and that’s exactly what we have done. That’s why we have two phases. Within roughly ten weeks we have reached a stage where we can share some of the findings to an interim report, which we have already published, and the work continued to completion. We’re hoping that before end of October and in November, a final report will be shared under this Creative Commons attribution for global access and benefits. Basically any entity who’s got these solutions is aware of aspects that are highly conducive to generating public trust. For example, don’t cover up any aspect of technology behavior; do not cater for any feature that can lend it open to abuse; and on the plus side make sure there are sufficient competences into design and understanding and governance of the institutions who generate such technologies, declare their intent and concept of operation with everyone transparently architected in such a way that it doesn’t lend itself to hacking, abuse, and loss of data; make the users aware of how they are interacting with the systems. Generally, make human supervision and oversight a feature of such systems rather than total and autonomous systems based on AI. And ultimately manage the operational risk.

So these were the concerns that are all factored in our fast track study. Our first report covers part of these issues, and our final report covers all of these issues to a fair amount of detail. Just to give you a feed, our first report has roughly fifty-five parameters for ethical transparency, accountability and bias in contact tracing. Our second report is likely to be doubling that.

Maria Palombini:
I’m sure there’s going to be a lot more. So on this paper on pandemic and ethics and contact tracing application, are you still open for comments and feedback? Is there a timeline for that or what’s the process there for that?

Ali Hessami:
The report was published late July and is available for free download from the IEEE SA site. It’s called The IEEE Use Case Criteria for Addressing Ethical Challenges in Transparency, Accountability, and Privacy of CTA/CTT, which stands for contact tracing application, which is contact tracing technology. Our focus is a global call for consultation.

We’re sharing our insides and criteria with the global community. We believe these are a comprehensive and reasonably broad set of ethical promises that can be accepted across many cultures. The deadline for commenting was also announced to be the first of September, but recognizing that August was a holiday season we have extended it to eighteenth of September. So people are still welcome from any institution or as an individual to send comments. This was an interim report and we are in the final stage of creating a very comprehensive set of ethical criteria by end of October. We are also planning a webinar to explain this to the global community to explain our intent, approach and value proposition from this non-commercial sharing of insights for the benefit of humanity on the tenth of October, ten o’clock, Eastern time. The experts and myself as the chair and vice chair of the ethics certification would be present to explain both the way we have worked together and benefits for others, and also rationalize why do we need to invest energy and time in making technology trusted before we rolled it out for the benefits of the society.

Maria Palombini:
And we will feature both the links to sign up for the webinar and for the paper on the IEEE SA site. You can find the information and we will be posting the webinars. I believe it’s already open for registration and we’ll have a link there as well. So we’re actually coming to our close. There’s been so much great information and we could do this for two hours. Is there any final thought that you would like impart to our audience? Something for them to think about because it’s something on our mind that’s very current in front of us.

Ali Hessami:
It actually pains us to have medicine solutions but no trust. If you look at the lack of takeoff of these technologies, which are currently the only medicine we have, if you like, against the virus that the majority of global community are suffering from. This is one technology that could be successfully rolled out, as problematic as it is in some aspects in terms of lack of precision. Nevertheless, we have a solution and the only failing on behalf of the global community has been the mannerism of explaining and respecting public opinion.

So the final thought I would suggest is that, as a global responsibility, it is upon all of us, especially decision makers, to actually not just think technologically for quick fixes, but also why should the public trust such quick fixes? Look at the process it takes to generate a vaccine. And why do people trust the vaccine? Because it goes through an enormous amount of verification and validation. We haven’t done that successfully for contact tracing. Our attempt is to get into what makes it transparent, accountable, and respectful of people’s privacy, to try and support understanding and trust in these technologies. Then if the majority adopt, adapt and apply it, we are going to hopefully maximize protection for the society and much faster return to normal social and economic life.

So it is really amazingly indicative of the necessity for humanizing technology to care for the society by explaining what happens to people’s data, who owns it, how it’s shared, what is the sunset criteria for technologies, etc. None of those have been done virtually anywhere that I know, with a catastrophic consequence that in most societies you ended up with countries that suffered most where the general public face only single solution on the horizon that could protect them automatically with the use of commercial kits, such as a mobile phone, and decided that they were not entrusting data to such technology because they didn’t understand how it was going to operate it, in what way they could be victimized or used for surveillance. In some countries, statistics show that less than 3 percent of the population, even though they are suffering from the pandemic, trusted and downloaded the application. This is desperately poor in time of crisis. We need to do much better than this. Our attempt is just one gesture on how to do better.

Maria Palombini:
I think that’s very well said. The statistics that you pointed out – something that we really need but yet we don’t trust so we don’t engage. Thank you Ali for this really insightful, interesting conversation. I’m so delighted that you joined me today. And I want to thank our audience for listening in and I hope you will check out the rest of our episodes on the podcast series. We’re covering everything from clinical research, wearables, decentralized health technology – everything that we can to make it better for all of us.

And if you want to get involved in any of our activities like incubator programs for decentralized health technologies and toolkits to drive adoption of decentralized clinical trials, establishing privacy and security in the use of wireless connected, medical devices, our newest program coming up will be telehealth, privacy, security, connectivity for all in a world of pandemics. Please visit our website at https://ieeesa.io/hls. Thank you everyone again and I look forward to joining us on our next episode. Bye.

Maria Palombini:
Welcome to the Rethink Health Podcast Series. I’m your host, Maria Palombini, leader of the IEEE Standards Association Healthcare and Life Science Practice. You may wonder why we’re doing this podcast series. So much is changing in the world of health. We have new technologies, tools, applications, all of which should make us think, how can we rethink the approach to health so that we have patients, like you and me, end up with better health. We bring you experts, advocates, researchers looking at rethink the process anywhere in the healthcare ecosystem from bench to bedside to get to where we need to be healthy. So I’m delighted to bring you one of these experts. Michael Ambrose, director at USP is an exciting organization. You know, when we think of quality, we think of USP in the scientific standards world. So Michael, why can’t you tell us a little bit about what USP does and the great work you’re doing there with them.

Michael Ambrose:
Thank you very much for this opportunity and good afternoon, everybody. I am the director of product quality and analytical methods within the digital innovation division. Our group explores and evaluates emerging technologies and trends that impact public health, especially in terms of medicine and therapies. We begin to really work together with the intersection of therapies and technology. USP is a global leader in building trust in medicines like patients and healthcare providers, industry, regulators, and such. We do this by setting standards, that ensure the quality, safety and promote public trust in these medicines, USP, is that doing this for just over 200 years? We started in 1820. Today we are in use in over 150 different countries throughout the world.

Maria Palombini:
Excellent. A fascinating organization. Now we’re in the world of COVID and everybody’s in a virtual environment and I’d like to humanize the experience. So for our audience, let’s hear a little fun fact about you, something that you do in your downtime or nice, interesting place you’ve traveled before, something that you would like to impart with our audience.

Michael Ambrose:
Besides science and technology, I actually have a number of different hobbies. One of the ones, the longest ones I’ve had so far is I am a guitarist. I’ve been playing guitar and blues for about 40 years now. I’ve also recently got a 3d printer and I’ve been having a lot of fun printing things and designing my own jewelry and such. So we also have fun outside of work as well.

Maria Palombini:
So we have a little garage biotech type of situation going on now. All right. So why don’t we get to the core, what do we really need to rethink with digital therapeutics? People talk about them, or people don’t even understand when I say people – patients, doctors, clinicians, we hear anything from an app to be a digital therapeutic or some other application of a technology, which gives us a bit of concern. From your point of view, how would you define a digital therapeutic?

Michael Ambrose:
Digital therapeutics and digital health in general is, as you just stated is a multifaceted area. Uh, we do concentrate on digital therapeutics and we’ve kind of defined it as a modality that uses high quality software programs that provide an evidence-based therapeutic intervention. This is to prevent, manage or treat a medical disorder or disease. These digital therapeutics can actually be the therapy in and of itself, or it can be in conjunction with other therapies as well.

Maria Palombini:
It’s a fascinating area that seems to be growing very rapidly. You know, what are some of the trends in the use of digital therapeutics? You know, we’ve seen the new norm, a lot of conversation about using them for mental wellness due to a lot of emotional distress, but also in pain management. So we’re seeing quite a different use cases for them from your side. What do you see them as a growing trend?

Michael Ambrose:
I see the trend as continuing where it is now to some degree in that the different types of applications for these digital therapy, therapeutic products continue to grow. This is both in areas where the digital product itself is the therapy. And I think that’s one of the weak aspects of it, where the software is therapy. We also continue to see the growth in digital therapeutics in conjunction with not only the therapeutic itself, but in areas where patient and doctor actually develop a different type of relationship outside of just the office visit with the change we’ve had with the COVID-19 the areas of mental health and such is an area where the ability to use digital therapeutic products is really starting to emerge the ability for the patient and the doctor to interact again, outside of the office. Some of the other areas that we’re starting to see is, is in areas of augmented reality and virtual reality applications as well. I think that is one of the larger areas that of study starting to actually trend down.

Maria Palombini:
We’re seeing something very similar as well obviously through the, IEEE standards association, the rise in augmented realities of Fidessa applications. So do you think the best use cases, just from a point of view of industry and patients and doctors and consumers is the best use cases for a digital therapeutic on the commercial side, or maybe from an FDA regulated application kind of thing?

Michael Ambrose:
That’s a tough question to ask because we’re really not in a position to say one way or the other newest. USP is for the quality of medicine that public trust and such. The applications, I think it’s between the patients, the doctor, the healthcare provider, the regulatory agencies, and such. I think there are a couple of different examples, where we can talk about the different types of digital therapeutics companies, such as well doc, there we star products for diabetes, intervention, and interactive. They just got their digital therapeutic endeavor cleared for the treatment of ADHD in children. And that’s an example where the therapy itself is the software or the others such as care therapeutics. They recently had reset, all clear. And that’s an example where the digital therapeutic is used in conjunction with an ongoing outpatient treatment of opioid addiction. Again, that’s where we’ve actually combined both the counseling aspects, as well as traditional therapy with this new digital therapeutic product as well.

Maria Palombini:
Definitely. I think it’s, it is a hard question, but we have to ask. We’re getting to the good part. Now the call to action, right? There’s a great new opportunity in the market for health digital therapeutics mischief makes us rethink a therapy. But now with the rise of something new, we always have to ask questions. There’s always a challenge. So what are you finding with the rise of these therapeutics to be some of the more concerning issues then perhaps need to be a little viewed closer or need a little more attention?

Michael Ambrose:
Sure. I’m not sure one would call it an issue, but it’s something that is extremely important that I think we all have to keep in mind in this new modality, digital therapeutics, these products treat people. We need to keep in mind that in the end, the patients is coming to a healthcare provider or a medical condition. And the provider is trying to treat that patient, that patient can be treated in the number of different modalities. The newest one will be emerging. One we’re talking today, digital therapeutics, it’s still treating patients. And so we have to keep in mind that these are there to alleviate discomfort they’re there to treat the patient. I think that’s one of the things we have to continue keep in mind. Sometimes when you talk about all of the different aspects, it doesn’t always come through, but I think it’s back of everybody’s mind, but the agencies, the FDA, the doctors, the manufacturers, that is the key aspect. I think we also need to make sure we keep that in mind.

Maria Palombini:
I’m so glad you mentioned that because in the world of new technologies applications, we’re so focused on the tool working. Sometimes we forget who the tool is for, and the patient is definitely the center of the healthcare ecosystem. So we must never lose sight of that. And I’m so glad you brought that up. So I think maybe the question, like what adjustments or what really needs to be considered when you think meaning a practitioner or someone who says you should be using this digital therapeutic needs to evaluate and assess it for its patients, what are maybe some considerations you all feel that that would be there?

Michael Ambrose:
Sure. I think if we go back to the premise that we’re treating patients, we start looking at it from the point of view of a patient where again, the patient has to have this trust. So it does have this trust in that this therapy either prescribed or recommended by that healthcare provider is going to have a positive effect on whatever condition they are being treated for the patient, just as in any other therapy has no way of knowing the quality or whether or not that product is going to do anything or do anything positive. And therefore, I think what we need to do is continually to evolve the ability to assess and evaluate the quality of that therapeutic product from the manufacturing, make sure that they have their quality management systems in place that they do the proper testing and evaluation. The regulatory agencies evaluate that product, not only from a software point of view, but this, but from the actual point of view of it being a therapeutic, there are a number of different quality management systems and quality standards out there for a software. But I don’t see many of them talking about the quality needed for actual therapeutics. I think that’s one of the areas that, that, that continues to be addressed. When we talk about software, we talk about security, data management, privacy ownership, we build into the hat and such. So I think all of those areas need to really to be considered even more importantly again, because these are treating patients first.

Maria Palombini:
So speaking of quality, how does USP see its role in helping to establish some sort of standard quote unquote equality for digital therapeutics?

Michael Ambrose:
Really good question. And I’m going to address that by going back a little bit of time, USP’s again, been around for 200 years. Through those 200 years, USP has evolved along with all the different modalities to continue to work with those industries to create the standards needed to assess quality. So we’ve gone from recipes and tinctures back in the 1820s and such to advance chemical medicines and the use of analytical technologies to evaluate quality to today with a complex biologics and such. USP is our ability to convene the appropriate stakeholders, industry leaders, thought leaders, academia, regulatory agencies, and such to convene and work together to try to understand what the quality measurements are for these different modalities and working together to create what those standards are and how to assess them. So I see USP, looking at this, not as a revolution of therapy, but just as the next evolution. Again, as we move from botanicals to typical medicines to biologics now to digital therapy, it is the evolution of the therapeutics and USP has, is continuing to want to do a history of addressing those in bridging technologies, working with the industries to actually create them.

Maria Palombini:
I think that’s really important and a fun fact for our audience out there. IEEE is a little over a 100 years old. And as Michael said, USP is 200 years old. So we are talking to a company who’s a hundred years older than us right now. So that’s awesome that we have some sustainability going on. Okay. So how did I come to learn about USP’s involvement in digital therapeutics is when one of Michael’s colleagues showed me this great paper that they’ve developed. So, Michael, do you want to talk a little bit about the paper you did and how maybe people can find out about it?

Michael Ambrose:
Sure. We just recently published a white paper on digital therapeutics where we go into a lot more detail about, our approach not just to digital therapeutics, but are the USP for appeal approach to reference standards and to the use of quality standards overall, and the value. We do this by first addressing the typical quality parameters that we have in more traditional therapies, such as identity, strength, purity, performance. And also, the question is, are these the correct terms? Do we need to adapt the definition? How do we determine identity and the software or the string, or do we to get, do we need to have a different set of terms that measure the quality of the software? Again, not just as a software, but as a therapeutic software. The paper can be found at http://www.usp.org/dtx . And in that paper, we actually address what your comments, comments, and the industry comments. Everybody’s reading the paper as well. Anybody listening to this podcast, maybe we’ve set up a special dedicated email just for that site, just so that you can submit your comments and thoughts. And that is at [email protected]. We look forward to hearing your comments and thoughts.

Maria Palombini:
And we will be sure to put both links. We’re going to write a blog about this podcast, and we’ll put both links on the blog post as well. So people can find it from there as well off the IEE SA beyond standards blog site, we make sure people have access to that. For sure. So everyone out there listening digital therapeutics are here. They’ve been here, they’re growing. I definitely think you should check them out, read this white paper, do a little research. We they’re helping us rethink the healthcare system. So if you want to get involved in some of the work we’re doing, um, at the IEEE SA, we’re doing, we’re talking digital therapeutics and clinical research. We’re looking at it from a point of view of wearables in our, you know, whammy certification program, many different applications and areas. Michael, I want to thank you for being a part of this podcast for sharing your insight and time with me.

Michael Ambrose:
Thank you very much. Appreciate that.

Maria Palombini:
And you know, it’s been a great collaboration. We’ve been collaborating with USP on some of these unique applications, such as smart pills, and now we’re talking together on digital therapeutics, and I think it’s a great collaboration between science and tech.

Michael Ambrose:
Thank you very much. And just one last statement for those that want to learn more about you to learn more about USP and standards setting such. So you please visit us at www.usp.org. You can see what we do with food and dietary supplements, biologics medicines, global public health, and such, and learn how you can, you can work with us as well.

Maria Palombini:
Yes, definitely. Uh, if you’re into this area of quality, definitely you want to talk to USP and for everyone out there, thank you again for joining us. We look forward. We have our next podcast next week coming up on artificial intelligence and blockchain in the world of epidemiology, which is another application of how we really need to rethink epidemiological research. But for now, thank you again for listening and we look forward to your participation and engagement in helping us to bring new solutions to drive adoption in the market.

Michael Ambrose:
Thank you very much. Bye bye.

Maria Palombini:
Welcome to the Re-Think Health podcast series. I am your host, Maria Palombini, leader of the IEEE Standards Association Healthcare and Life Sciences Practice. You may wonder why this podcast series so much is changing in the world of health, new technology tools, applications, all of which should make us think, how can we rethink their approach to health care so that patients like you and me will end up with better health. We are bringing you experts, advocates, researchers who are looking at how we need to rethink the process anywhere in the healthcare ecosystem. So we’re talking from the bench to bedside and all with the goal to get us where we need to be healthier today. I’m delighted to bring you one of these experts, Jennifer Goldsack, executive director of the Digital Medicine Society. Our episode today is entitled taking a stand moving health wearables to the necessary next level. And by the end of this short broadcast, you will understand why and how to get involved. So Jennifer, welcome to the podcast.

Jennifer Goldsack:
Thanks, Maria. I appreciate you inviting me today.

Maria Palombini:
So tell us a little bit about yourself and your work as a digital medicine society.

Jennifer Goldsack:
Yeah. So if you said I’m the executive director here at the digital medicine society or dying Maria, we’re a 501c3 nonprofit. We are a member organization and we are committed to advancing the safe, effective, ethical, and equitable use of digital medicine products to improve lives.

Maria Palombini:
Excellent. So this is how I came to know Jennifer because we have a lot of alignments here. We were talking about ethical, responsible use of technologies. How do we advance medicine? How do we save lives? So you want to give us some examples, some of the great work that Digital Medicine Society has done.

Jennifer Goldsack:
Yeah. So it was still quite humorous. So we were founded in May 2019. At the time of this recording, we are at sort of 16 months old, we held us to a high standard, like if Maria is doing clinical quality wise on a text timeline, we recognize that there’s huge opportunity to use new digital technologies, whether that’s access to new dataset or whether it’s on a face, but it’s computing power to improve lives. We also recognize that the pace of innovation and health technology is moving a little bit faster than all of the stakeholders find it easy to understand, and certainly at faster than our pay to regulate and control it. So we are very focused on making sure that these technologies are really deployed in the service of health and that we don’t miss that. A critically important part of that. We believe it’s bringing all of the different experts to the table for citizen scientists and bioethicists through every flavor that is clinical and engineering. It’s basically scientists to regulators and payers. If everyone isn’t at the table, we are not going to have the success and improving outcomes and improving lives that we should. And we may also submit step along the way. So our role here at DiMe is to try and coordinate expertise and collaboration and unifying frameworks and languages using digital technologies.

Maria Palombini:
Absolutely agreed and well said. Before we get to the core of what our conversations about, you know, we’re in a very digital world. So I would like to ask you, what is one little fun fact about you that would really humanize your voice, your expertise with our audience?

Jennifer Goldsack:
So I tell you this, it makes me feel older than I can shake. You may notice that my accent is British. I found myself in the US in 2007. My mother’s actually American. So I always had dual citizenship. And, um, I also graduating from grad school at a university about outputs. I actually spent a few years as a professional athlete. So when I came to the States, I’ve been on the British rowing team for a few years and they changed to the States, use my American passport and actually competed on the U S seven 15, um, in Beijing in 2008. And Maria, I intended to go straight into your mouth today calling back to London, but I really loved the safety. So having sort of retired from my athletic career, um, I got into, uh, sort of health research here in the States. Um, and I’ve been here ever since. So that’s probably my contacts. And we’ll say here in the US.

Maria Palombini:
That is fascinating. So we have an Olympian on our podcast. Very exciting today.

Jennifer Goldsack:
Yes, that’s right. Very stubborn. I feel like doing the right way.

Maria Palombini:
That’s exciting. We’re getting into our next segment. The core of the whole podcast is what are we trying to rethink here? Therefore, big tech in healthcare, we’re hearing more about digital therapeutics. We know there’s a growing use of wearables. There is reports all over from all kinds of the big consultancies to the big research writers saying anywhere from 120 million health wearables to be utilized by 2023 sensors in the body, on the body, around the body, wearable, ECG, monitors, wearable, blood pressures, fitness trackers, excellent. Every 75% of the population wants to use them to go towards better health. But here’s the core question. What are we doing with these wearables? What are we not pushing the bounds on? So, Jennifer, my question to you is in your words, what do you think is being issue with health wearables as it relates to clinical research?

Jennifer Goldsack:
Picking just one issue is a bit of a challenge. And I used to be that not to be negative about weather, but because I think it’s moving really quickly. I would say these two things I’d want to highlight Maria. I think we’re at a moment where people have taken their eye off the ball, not everyone, but I think that there’s a misnomer right now, even in some of the statistics that you just quoted, that more digital, more health tech is better. Um, and I think, um, I think that’s the wrong way to look at it. And there are persistent challenges that we faced in health tech and in clinical research is lack of access, unaffordable, affordable cost. We still have crushing conditions like Alzheimer’s that we have no disease modifying treatment for. In the US in particular, we have particularly poor outcomes despite spending 14. These are the problems that we should be focusing on. And I think that digital and wearables and technology are a very important tool that can help us address these problems. I see huge bias in. But I think that, one of the challenges right now is just rubbing digital as a problem. Thinking more about the digital solutions rather than its unique applicability to today’s patients or clinical or business problem we’re trying to solve for.

Maria Palombini:
Excellent. What do you perceive your road’s perception of wearables? We hear a lot that they can’t trust them. They’re concerned about patient adherence. There’s some corruption in the communication or security vulnerabilities and transport of data. I mean, there’s a whole list of things we’ve heard. But do you find that the trucks of these technologies for validating efficient use for research would really push pharma to do more comfortable with the use of these, of these tools? Or what do you think is all the challenges?

Jennifer Goldsack:
I really liked that you used the word trust because I think that’s what it all boils down to is. And, you know, we were chatting at the beginning of the podcast about how this is probably one of the most interdisciplinary fields that we can think of. And I think that that is at the core, the challenge with trust that isn’t yet a unifying the language or the field. If I say validation to a data scientist, to a hardware engineering, to a regulator, they all mean different things. So we, it’s not easy to communicate. It’s not easy to collaborate. We also don’t yet have shared framework for evaluating what good even looks like. Whether it’s from a measurement point of view, whether it’s from a security or a data rights point of view, whether it can be used the better at the end. You tell it to the point. That is, I think until, until we can overcome the silos of expertise with vendors sitting at arm’s length outside of pharma and CRM wave out a common unifying language without common framework, we are always going to have a trust problem because people they understand what’s going on. That sort of list of problems is really at the core of what we try and address paradigm. We’re getting everyone together, making that comment, unifying language, creating those common frameworks. I know that we share those goals with your team, Maria, at IEEE Standards Association.

Maria Palombini:
Excellent, agreed. We’re very aligned on some of the challenges that we’re seeing. So we talk a lot about challenges in medical devices. We’ve seen challenges all along normal point of view of interoperability, compatibility, and portability. We see all these big devices coming into play from diagnostics and therapeutics. What’s going to you think is going to be the catalyst when it comes to wearables, like who do you think is going to be the true big entities or big players to catalyze this change that needs to be done with it comes to portability, interoperability and compatibility and the use of wearables?

Jennifer Goldsack:
I think ultimately it comes down to recognizing that this is what patients want. If we talk to patients, if we talk to research participants, they want to be able to take their data. They want to be able to go to the provider or participate in the trial that they want to. They also recognize that it is their right to access their data. And so I think increasingly as patients and participants are exposed to technology and how that allows them to transport information in other areas of their lives, they’re going to expect that when they come into contact with the healthcare system. I also recognize that I think we often burden patients to be the catalyst to change. And I think on the industry side, we need to step up, recognize their needs and realize it, um, something that we’ve been thinking about a lot recently at dying. And in fact, on the clinical research side in particular I think that by the pharma industry, standing shoulder to shoulder and demanding bare minimum standards around compatibility interoperability portability from vendors coming into this space. I think that essentially that buying power could be a very powerful letter and effecting change in compatibility and interoperability on you. You mentioned we’ve seen him in the medical device world for decades. However, with wearables, we are at an exciting time, um, all of this new sort of stuff, the old, and I think we do have the opportunity to bring everyone to the table if we are strategic.

Maria Palombini:
Definitely a great thing. Strategic is the key term there. We’re coming up on our final segment. You know, the podcast is called Rethink, which means we want everybody to take an action. Therefore, when we think about all these use of the rise in the use of digital therapeutics, wearables, what kind of challenges are we really thinking about? Like what keeps you up at night about the use of these devices that really give you that fear that we can’t yet trust them?

Jennifer Goldsack:
So it’s really interesting. I don’t think that there are any gaps in our knowledge or our capabilities to deploy these tools in a way that is ethical is safe, effective, and ethical. It’s equitable. I think the challenge is that we’re not quite well enough aligned yet. We haven’t quite assembled the jigsaw puzzle pieces well enough to ensure that always the case. Maria, I can have a bit of a flare for the dramatic sometimes, but you know, the way I think about these things is this is a critically important juncture in the evolution of the field of sort of digital health and digital medicine. I think we have this opportunity to develop and deploy digital products as powerful, powerful tools in the service of improving health, equity, health outcomes in reducing healthcare costs and improving access. So on and so forth. I also think that we’re in the precipice of some pretty big risks that, you know, that there’s a risk of instead of developing precision therapy kits and precision approaches to help test and to reset. We actually just doubled down on the surveillance economy that instead of, um, using these tools to try and immediate right health disparities, we actually make them worse. So what picks me up at night is are we moving quickly enough to make sure that that ethical and that lens of equity that ends up that, that lens of safety, um, is sort of keeping pace with the promise of these technologies? Are we really using them as a tool and not well.

Maria Palombini:
Very well said. I mentioned a little earlier that you and I came to class cause we’ve had very common alignment on the use of technologies in clinical research. So how do you envision the digital medicine society and triple collaborating to figure out how it was a great solution to really leverage these wearables beyond monitoring?

Jennifer Goldsack:
Yeah. So I’m going to go back to your question earlier, Maria, that to honed in on issues of sort of interoperability and compatibility. I think that is an opportunity for us to work together and to bring all communities together. And I think the timing is right, and I think we both have sort of the energy and the expertise to actually move the needle on that early enough, that it, if it comes to sort of a permanent and an impactful change on this rapidly developing industry, I honestly think standing shoulder to shoulder and what we define as that common unifying language, helping folks understand what sets the purpose really means to each and every use case. I think if we can put those forward, we’ve done a lot of that work already at dime. I know that you guys have some initiatives on the way. I think if we can continue to sort of collaborate to support the field rather than sort of fracturing, um, and coming up with competing frameworks, I think that’s something that I’m very proud of and as I’m sort of standing together and making a commitment to the field that we will share and combine our knowledge and our best practice to best the industry. That’s something I’m really proud of. Um, and in particular, I think that, you mentioned going to scale, I think a lot of that is going to come down to the interoperability and compatibility pieces. I think in less particularly pharma companies can be confident in that compatibility, for example, over time or that, um, something as simple as continuous hot right, is actually defined as the same thing, measured and recorded at the same thing across technologies, across studies across populations, with always going to be hamstrung in trying to take these technologies.

Maria Palombini:
Exactly. And for patients out there, you might think this is a wearable and this is a wearable, and when it comes to clinical research, there’s always a difference. And this is the heart of what we want to get to the point where we can make these things work in a way so that the patient experience is seamless for them as well as for the clinical research process. That’s exactly what we want. We want it to make it seamless, but we want to make it work.

Jennifer Goldsack:
I think that’s really important. I also think it necessary, for example, for the patient has to be bud instead of in the weeds and I’ll use the continuous thought right. Example, right. There are some smartwatches that might report that as sort of average hall, right. Across 10 seconds, but reported per minutes, others might do it sort of average pub beat. Others might do it over 60 seconds. Um, and so until that’s sort of standardized, it’s always impossible to make sure that the patient or the participant can actually get the technology that they want to use that works best for them because we’re going to be constrained by reporting it and in a particular way. So, yeah, I really liked how you framed that, keeping the patient right at the front of mind.

Maria Palombini:
Absolutely Jennifer, you call it there an opinion piece, which I enjoyed reading called the wild West, the data. And I actually liked the title more. And how can some of the listeners read on what you guys wrote?

Jennifer Goldsack:
So Maria, what about you? You gave us some really good support. As we put that piece together, you read a draft and I’m very grateful for you. So, with Jordan Bryanov of the Data Sciences Institute of Takeda, and Bill Byrom from Signant Health, we did recently publish news, but it’s opinions when it is in these called the wild West of data. And now we were talking about this challenge that we’ve spent some time on this morning. You were talking about the challenge of the pharmaceutical industry in particular has spent many years now completing many successful proof of concept studies using technology. Patients is telling them that they’re comfortable using them, that they want to use them. And their COVID-19 crisis has made us realize that we have to get better quickly at becoming less dependent on data collected in the clinic. And that we can not only keep patients safe by keeping them out of the clinic, but we can also capture much more complete information about their experience with and without therapy using these cities sense, the technology. The problem is it goes back to what we were just talking about with our example, the part, right? With our example of continuous heart rate monitoring, we’re not comparing apples and apples, even when there’s some of the language suggests we off and until we can get off on the teachable call, each sufficiency, that technologies are going to be back compatible over time that they can select the technologies that work best for their participants, that data is reported in a way that it can be synthesized to be more than the sum of the parts we aren’t going to make for progress. And I think that tremendous work has been done. And I’m proud of Don’s role in doing some of the work around identifying what good looks like in terms of measurement and performance. For example, we propose the B3 framework, verification, validation, clinical validation. But you know, until we can take that to scale, we aren’t going to see technologies making the impact on speeding the development of new medical products patients until we can guarantee some bare minimum level of interoperability. And so, yes, we get into that in much more detail. And I can send you the names if you’d like to face it with the podcast. And within that, there’s also a link for folks to sign up if they are keen to join us, we will be working together to advance that notion of bare minimum standards that if trying to send the whole industry.

Maria Palombini:
Yes, for sure. And we’ll include a link to it. We’re going to write a little blog about this podcast on the Beyond Standards blog, and we’ll include the link to the op-ed piece. For sure. Jennifer, you’ve given us so many great insights today and so much to think about. And I want to thank you for joining me and being a part of this podcast series.

Jennifer Goldsack:
Thank you for having me. And it’s always a pleasure. I think that I’m very proud of us, your organizations and communities being so committed to lessons together. So it was a pleasure to be your guest this morning. And I look forward to continuing to work together.

Maria Palombini:
Absolutely same here. And I want to thank all of you for listening. And if you’re interested in taking a stand and joining Jennifer and the digital medicine society and IEEE SA to tackle the challenge of moving wearables beyond monitoring, or to help address any other challenges, solutions in the clinical trials research process and the healthcare ecosystem, and just end at the end of the day, to make sure that we have a better chance for all patients to have access to better health, please visit our website at ieeesa.io/hls, and you can look us up and find more information and how to get engaged, want to wish all of you to continue to stay safe and well. And hopefully you’ll join us on our next episode where we’re going to tackle the quality challenges around digital therapeutics until then enjoy the rest of your day. Thank you.

Maria Palombini:
Hello everyone, welcome to Re-Think Health, a podcast series powered by, IEEE SA Health Care and Life Sciences Practice. I’m Maria Palombini. And I’m your host and I’m delighted that you’ve joined us today.

Maria Palombini:
It’s a really exciting discussion on digitalizing clinical trials, what I like to call removing the pain and enhancing patient care, and I’m honored to have with me Walter De Brouwer, founder and CEO of Doc.ai and the volunteer chair of the IEEE SA Technology and Data Harmonization for Enabling Remote [now entitled Decentralized] Clinical Trials Industry Connections Program. As you all know, for those of you who are actually members, we put a lot of words into a lot of our programs. So just a little bit about Walter. He is an adjunct professor at Stanford University School of Medicine and a visiting professor at the School of Management. He runs the Harvard Medical School spinoff XY.AI, which actually pioneered the digital twin algorithm in medical research and created the geo-intelligence system to study the cosmic burden on genomes. That just a sentence alone just makes me think how amazing and grand that work is. He also participates in various other programs, including the Growth Data Science Coalition and other organizations. So and he has many interesting interests and interests. He’s looking at five key cognitive radio, quantum computing and everything in between. So, Walter, thank you for joining me today. It’s a pleasure to have you.

Walter De Brouwer:
Thank you for having me.

Maria Palombini:
So we know whoever’s in the pharmaceutical health care domain that there are some systemic challenges in clinical trials. So let’s start with who clinical trials are supposed to help patients? Why do patients feel so out of the loop when it comes to the ability to make decisions about their health in their care? And what are some of the trends impacting drug development, cheering and ownership of this health data?

Walter De Brouwer:
Well, first of all, I think it’s common for too many people that we have a delivery problem for health care in the United States. And delivery problems always arise when it’s just some of the scaling per square kilometer and the inhabitants of scale kilometers. And it’s also a symptom of the complexity of industrialized civilizations, of course. But in the states, really to get an appointment with the doctor or specialist, it’s really painful. And also the costs associated to that are horrendous because we are in a situation where medical bills are the first cause of bankruptcy in the United States. And then if the results were great, perhaps we could understand that a little bit. But the results are abysmal because we have the lowest life span, the lowest life expectancy. We have the highest mortality of babies. So we have the highest rates of suicide.

So there is something between the collection of price and value that is completely wrong. And also our health care is linked to our job. So you mostly get sick when you’re not having a job because you have too much time. Time is also a bit of like a medication. You know, you can overdose if you have too much time. But just when you don’t have a job and then you’re also your health care falls away. And then there are all these layers, like I call them the five piece, like the patient is one.

But there is the provider, the physician of pharma, the politics, the regulator. And all these create actually and the pay are of course, all these create an enormous layer of bureaucracy where the patient has to find its way.

And for the moment they don’t find their way in and they just do the best they can. So Americans aren’t a society of whiners, so they just make to make the best of it. But being out of that digging, that side loop is, of course, of course, one of the reasons our mental health problems also go off.

Maria Palombini:
Absolutely. There’s just the whole complexity of problems. Speaking of an interesting problem, we are all in the midst of our fourth or fifth month of this covid-19 pandemic, which has been which has opened the Pandora’s box for the idea of telehealth, remote health and care. And we also know that many clinical trials, unfortunately, had to be paused or canceled as a result of the pandemic. So when the clinical trials IC program was born at the end over a year ago at the IEEE Standards Association, we had not envisioned covid-19 pandemic. At the time, we were trying to address some of the challenges we saw in the clinical trials industry and low and behold, the future became today.

Maria Palombini:
So my question to you is, how do you think the group can impact the continuation of trials in the future even? With covid-19 and beyond to whatever the next potential challenge might be, how and what do you foresee happening as a result of it?

Walter De Brouwer:
Well, first of all, there’s a lot of new things that have happened in technology that still have to go into drug development, which will dramatically reduce the costs of medical research. You know, why have all these clinical trials forced now? Well, first of all, there’s this paranoia set in. Patients don’t want to see doctors because they think they’re infectious and doctors don’t want to see patients because they think they’re infectious. So and so they find each other on the screen and that they now know that it’s a lot easier. And they can also do it digitally, which is we have evolved towards a synchronous communication society. We’d rather actually do things writing or chatting than ever having actually voice calls, which you can never interrupt because there’s a guy, you know, sitting in his living room talking about this life for an hour. So all these things are actually very good for people to realize, hey, you know, there’s a new kind of delivery there and it works very well for doctors and for patients. And why have these trials now paused not only because of that, but because people start to realize I don’t want to go to a site where there are doctors, where I’m actually handled in an unfriendly way, almost like patronizing way. And there is another way for us to do it. If I want to be in a trial, I don’t want to do it for eight dollars a day and risk my health and go through all this hassle.

So people who organize clinical trials have to rethink this relationship today because, of course, nobody likes change. You know, my wife always says that I only change to avoid change, which is probably true, but probably work for everyone. But, there’s something worse than change and that is an irrelevance. And this is the time to change now. And of course, if your bread and butter and if you make a great income, it’s very hard to persuade people who make a lot of money that they have to change, you know, but it has to be.

So let’s look at the drug development. How can the technologies of today, how can we make this a lot cheaper and a lot better? First of all, there is a big wave coming and now it’s covid-19. This has brought momentum and acceleration. So patients and they are realizing it. Patients are becoming the buyer’s market. So the seller’s market is over more and more. They will be in charge. They want a Yelp industry of doctors and providers so that decentralization from a central point of hospitals where people have to go and to a doctor. And so they want to do it, you know, like what they are experiencing now. They want to keep it going.

And this also translates in our technology because we now have we build up the cloud, you know, like where every enterprise is using the cloud and every user is using the cloud. But now everyone has a smartphone. So if you think of it. And so, first of all, if you have a smartphone, you are basically a researcher. And that’s a new concept that we have to tell people, as is the story that we have to tell people now, and that we have to actually admit to people that medicine we don’t know everything.

Basically in medical research, we use a lot of statistics to basically hide our temporary ignorance of facts. So we should also share that with people that they are researchers, the participants are researchers, and they can do that on their smartphone and in that smartphone. We will use from the technology side every component in that smartphone to extract medical information. And that smartphone itself will be a remote device where a hub where we can connect to all the other devices around us and extract medical data. And then the technology is now there to both ensure the privacy on the edge of the device, because now if you have a smartphone, you don’t need to go to the cloud anymore, you know, as an individual, because I can store more on my smartphone than on my laptop. I can compute on my smartphone. But until recently I could not train a model. I could not make my smartphone learn.

Now, at Federated Learning, we can do everything on a smartphone. So that means in the future. Now, how does it work? Like we have a lot of daytime companies have a lot of data. They put it in the cloud, which is a sort of a public toilet, you know, like because you never know who goes before, who comes off to you and you just want to wash your hands and get out. Now, we can do it on our smartphone and we don’t have to go back to the cloud and process some information that is there. It is on our smartphone and what where it is created, it will be continuously computer. And so we are going for health care as a discrete function. And with the discrete function, I mean, like your bank account, you know, something goes in, goes out. It’s a bit like a patient, you know, like you false that put them in a hospital. A week later, they will come out and that’s where the protocol ends. And then, you know, you see people crawling to a cup and there again in the world, in the real world, and they don’t actually know what happened to them.

So that’s because health care is a discrete function. We only need, you know, engineers who are once also discrete. We only corrected bugs in the system, but now we don’t do that anymore. Well, we’re still correctable bugs, but I mean, we are looking at what we are doing as a marathon. We are continuously looking for security and looking for mistakes. And health care will be a continuous function, just like a plant that grows that is only to singularities.

You are born and you die. And everything that comes between is a superposition of you are healthy and you are not healthy. But by getting a lot of data on that, we will you know, patients will learn to know themselves and they will if they have a disease, they will even become expert patients after that, you know, to tell other patients, because if they give me the opportunity, if I have a disease to talk to an expert doctor or an expert patient who went through it, I first want to talk to the patient. So all these things are happening now that decentralization and another big thing is happening that is real world data. And I want to explain that a little bit, because this is going to be so important for the future.

Up to now, our medical research worked in controlled studies with the placebo control group and another group, some group got the real bill. The other group got the placebo. You know, people always have placebo for you. You know, like, you know, I have the placebo pill that basically – you come to a situation where they come to people like us, you know, mathematicians, and they make us a model because it has to go through the FDA. And these are the standard deviations that the FDA will follow. So for us, so that we white boards, because we know the success of getting through the FDA is basically how you calculate error.

So we are making a model of a world and we stipulate what this world is. And in this world, the model works and the drug works. But please don’t go out of this world because it’s a world. It is not the world. So then afterwards you go into the world and there you have something like pharmacovigilance, which the FDA does, and then you see how a drug performs in the market.

Now, why do we do that? It cost a lot of money. It’s basically mathematically controlled into an ideal world while we could do real world data and real world evidence. And where is that? Well, for instance, it’s in claims that its claims are payers, insurers, and they have already actually paid out for a disease. And we sure, if they pay out, you really have had that disease, you know, because they check every step of it so that that’s the placebo. So you can give people a bill and then you take, you know, like a big amount of data where you make digital twins. Basically, you say like we want the same people, the same BMI, the same age, the same gender, the same condition, and that is the placebo. This will speed up medical research enormously. And so out of that comes real world evidence.

Then another thing, that’s why I mentioned this, everything on extra computing and the learning for the first time in the world, probably we have found a way which is non zero sum up to that. You know, for data up to now, everything was a zero sum. If I get something, I have to take it from somewhere else. So that’s why people don’t want to give their data because, you know, everyone keeps their data in silos because if they give it, they don’t no longer have what we have done.

And basically on earlier research of Google in 2015, we were the first actually that worked on that for medical research because what does it mean? Well, in Federated Learning, you give a model to people who have data and you say, you know, populate that model and give us the encrypted answers, which is mathematical formula. And that is actually the essence of the learning. You don’t know any of the data. You haven’t touched the data. You don’t even know the structure of the data. You certainly don’t know who is behind that data or, you know, you don’t have to identify it, but then you can exchange the answers and both win. It’s a win-win. It’s not a zero sum. So this will help medical research enormously because in academia, we always have to beg for data. Now, with that new situation where A.I. has come on through learning, we can even do it on smartphones. People can collect their data on their smartphones. And then what we do is we put all these smartphones together and then everyone because of a smartphone. I know how I am doing, but I don’t know how the others are doing. So I have no point of view. But if I then have how I’m doing and all the learning of all the others, I not only learn, but I also know where I am in the perspective to the.

So also we have recently you know, there is a big problem with privacy and with learning privacy won’t go away. People think that, you know, at one point we’ll give up our privacy. I don’t believe that because our DNA is unique. If I give my DNA to someone, I expose my germline. Perhaps my grandchild someday will be brought up because his DNA is mixed up with other DNA and he gets in through Jalabi by some, you know, like because I didn’t check my sources when I did that the privacy will not go away. But you also have to learn. So how can you how can our models learn with privacy data? And of course, we have all sorts of we can use hashes and cryptography, but there’s another way we can just leave it to the user, to the patient, and we can tell them, because how does privacy work? We are adding randomization. So we are adding a lot of random noise to something. If you take a picture and you want it completely private, you won’t recognize yourself in that picture anymore and nobody will be able to decrypt. But then that picture cannot learn anymore. When you tell people you can you yourself, you can actually Parise that if you want 50 percent privacy and 50 percent learning, that’s what we will give you.

If you want 80 percent privacy, 20 percent learning, because you see that is the equilibrium. What do you want? You want to learn or do you want to be completely private? And I think that’s the best way to leave it to the people. This creates markets. You know, perhaps medical research wants people who are complete. They want to know everything so they will have to pay more because this is going to be a gig economy, just like doctors are basically now already in the gig economy. If you do telehealth, you find them on several systems, the same doctor. It’s a bit like you drive for people, you drive for Lyft and then concierge doctors, they drive the limos the same thing. And now patients will also go into that gig economy because in their downtime on their phone, they will add some, you know, medical information for which they will be paid because in micropayment, every time they do that, so they will make you know, they will make a bit of money. And so, for instance, one of our sisters, we have integrated Amazon or no cryptocurrency or just Amazon. Amazon goes. So what does that mean? Well, people make points on Amazon and they can buy everything on Amazon. Basically, it’s really become the world’s store.

You can buy everything. And people like it because that’s the new way of going to research, I think. I believe all these new technologies will dramatically reduce the cost of medical research. It will give Thayer’s, for instance, who have a lot of data, which is real world data, the ability to sell that data and reduce their premiums. It will give people like Walmart or Verizon enormous ability of getting that data and also sell it and therefore reduce their prices. So everything is reduced. The bias market comes up, services go up. People are friendly. And it may be an idealistic world, but it’s one that I want to believe in and as a scientist, we are ready to make this happen, but we need leaders who go behind this. You know, we need leaders of large corporations to say this is what we’re going to do, a little bit of channeling and consensus. But in the end, this is the vision. And we also need this to be accepted by clinical research. We need publishing. We need to publish about this is how we did it with placebo as well, how we did it. We’re not placebo. This works. This doesn’t work. So if we get these two things together, so then we are in a completely different world.

Maria Palombini:
And so, well, that was very fascinating, your vision, I mean, you have set out quite a task for your team on this industry connections program. For those of you not a part of our legal system, maybe in the connections program, you can understand as an incubator program. And it’s to take a team of 12 groups working with Walter to sort of test and make this sort of vision happen. Right. And what does that look like from workflows to changing the process? I think it’s just unbelievable. One point that I think is really you covered so many great points on benefits to patients and benefits to sponsors of clinical trials. I guess you touched on this. This is a very I don’t like to use the term disruptive in medicine because it makes people feel uneasy. But this is really revolutionizing how we think about trials in the process. And what do you what will you do you believe is going to be the element that’s going to get all these stakeholders to sort of change and accept this new approach? This is the way we have to go. What do you fundamentally believe will drive home? That is a policy like FDA writes it in. Is it through the development of standards? Is it your consensus of the system? Like what do you feel will be the turning point? Well, I have to say I have to be part of this. I have to engage this.

Walter De Brouwer:
Well, I think the industry, as it now is, is a bit like the post office. And we basically bungled the post office. The physical aspect is now Amazon and the digital aspect is email. And we’re all happy with the delivery. So when we see US Postal or coming to our door, say, I was only able to even think about this anymore, I think that we are going for and now everyone is aligned. We are going for what I call the de-carbonization of health care. And with de-carbonization, I mean fewer and fewer humans, you know, carbon based units, the highest form of carbonization is hospitals. It’s, you know, because you need more than one human and then you need more than 10 humans through a project and to bureaucratize these other humans. So it’s the number-one line item of cost. A lot of people go to hospitals and they shouldn’t go there. That’s why we have you know, we have a delivery problem there. So people should just stay in there. You know, I think there are a couple of startups now already working on the strip at the hospital rooms up at home where you just if you just need an ultrasound, you can now buy one for two thousand dollars. You can rent them at a hundred dollars a month. And since you have a virtual health care on your screen, you know, a doctor can say, oh, that looks like this, or you can even do this now. Or, you know, like there are companies like seven cents. You can just put it on your arm. There’s so many things available now. And you know what? The number one, that item that people go to hospitals for is an I.V. drip. You know, like say like, you know, you can really do that at home. You know, like a nurse can do that or, you know, they can show you once and in training you have to do it through each other. The next level of carbonization is the physical checkup.

Now, before you have a telehealth, you first have to meet this doctor who sits on the other part of the room. You are both masked. No, actually, it’s not necessary. You can even do it immediately. Telehealth is the third line, you know, like hospitals, doctors, telehealth, telehealth is a little digital. But there’s still like a doctor that on the other side before it’s de-carbonization is digital. And that is you can chat, you can go email, you can look at the response group, you can text your doctor. And you really love it because, you know, I prefer to text my doctor about medication and my medication arrives at home then really to go there and talk about it. It’s no use. Of course, I’m a declarative person. I do not seek a regulation. And then the last part is mobile, we have an agent’s identity for mental health that we are getting ready now. We put all the clinical protocols in there because there’s a lot of anxiety around now, because the more you give data to people, the more anxious they become before actually providing in the human being. So serenity is so great. People love it. Why? Because it all stays on your phone.

If you want to talk about mental health issues and anxiety, I don’t want to be on a corporate server somewhere. I want to give it to Google, you know, like before you know, it ends up somewhere you don’t want to. I want to be on my phone own device, not going to the cops. And this is possible. So this is the funnel. Hospital’s physical doctor, then virtual health, digital health, mobile health, because we will never be comfortable with getting the human out of the loop. You know, we thought so 20 years ago, 30 years ago. We thought so with banking. We optimize the hell out of banking. And in the beginning, every banker thought they were going to lose their jobs. But guess what? There are more bankers now than ever. And also there are more computer scientists working in banks every time we introduce technology. It doesn’t reduce jobs. It creates, of course, probably not with the same people. But that’s the learning thing that you have to actively work on, not becoming irrelevant. And also and it’s fun working alone. Just learning brings you adrenaline. It gives me a little probably. Well, I think it gives everyone that you just have to learn them how to learn, you know, and yeah, that’s how I see that funnel going from hospital to doctor to virtual to digital to robot. And this will scale doctors because no way we will create 10 times more doctors than we have now in the next five years. That’s not possible.

Maria Palombini:
Well, there’s so many great pieces of information and insight you share with us today. Walter, we’ve come up on time just if anybody’s interested in joining the clinical.

And Walter and his cohorts have been leading this incubator program, please visit standards that are too big. This is a great participation. If you are a pharma company or a technologist, a chain company, if you want to see clinical trials really revolutionized, this is the opportunity to be a part of something that will definitely put a football front in the ground. Walter, thank you so much for your time today. I will be sure to invite you again to see how the team is progressing and definitely get a little more insight into how you’re seeing the future of trials going and how we’re starting to make that change for everyone else. Thank you so much for joining us. Until next time. Stay safe and be well.

As a Biochemistry and Molecular Medicine professor and co-director of The McCormick Genomic & Proteomic Center at The George Washington University (GW) and while working at National Center for Biotechnology Information (NCBI) at NIH, and UniProt Dr. Mazumder has worked closely with national and international colleagues in developing international molecular biology resources and using these resources to identify therapeutics, diagnostics and vaccines targets. His research focus is on developing novel methods for data-to-knowledge discovery through national and international initiatives in biomedical sciences such as GlyGen and OncoMX, and community driven bioinformatics projects such as the BioCompute initiative. He has experience in scientific coordination, bioinformatics infrastructure building, and through NCI, NSF, NIGMS, NIAD, pharmaceutical, non-profit and FDA funding he has been involved in genomic and bioinformatics research associated with cancer biology, glycobiology, and metagenomics. Dr. Mazumder is also the co-developer of High Performance Integrated Virtual Environment (HIVE) which is approved for use in a regulatory environment at US FDA. In addition to his research activities he mentors faculty, graduate students, and directs the Bioinformatics M.S. graduate program track and co-directs the Ph.D. Bioinformatics and Genomics program at GW.

Follow Raja Mazumder on Twitter. Learn more at https://orcid.org/0000-0001-8823-9945.

Jonathon Keeney is a Research Assistant Professor, Managing Director for the Executive Steering Committee for the BioCompute Public Private Partnership, and lead for the High-performance Integrated Virtual Environment (HIVE) bioinformatics platform. He was Secretary for IEEE 2791-2020, the BioCompute standard, which is now a published standard adopted by the FDA and others. His work develops novel approaches to research questions that comprise both strategy and bioinformatic framework, and which have included neuroscience, microbiome, and virus research. He has contributed heavily to the development of the BioCompute standard for the communication of computational analyses, genomic copy number variation in the developing human brain, and strategies for adventitious virus detection.

Follow Jonathon Keeney on LinkedIn.

Maria Palombini:
Hello everyone. I’m Maria Palombini with the IEEE Standards Association. I lead the Healthcare and Life Sciences practice. So much is changing in the world of health. We have new technologies, tools, and applications, all of which should make us think: how can we rethink the approach to health, so that we as patients, you and me, end up with better health.

I’m very excited to have with me the chairs of IEEE 2791 Raja Mazumder and Jonathon Keeney. Just for all of you who don’t know what P2791 is, we just actually released that standard last month, very fresh off the presses. And it is the IEEE standard for bioinformatics analysis generated by high throughput sequencing to facilitate communication. Yes, it is quite a mouthful, but very important, very cutting edge application of this technology.

And you will see, it is important today even in the middle of this global pandemic. Just to let you know, Raja is a professor of biochemistry and molecular medicine and co-director of the McCormick Genomic & Proteomic Center at the George Washington University. And Jonathon is an assistant research professor in bioinformatics department of biochemistry and molecular medicine also at the George Washington University. And he’s a member of the executive steering committee for biocompute. Let’s get to the great stuff, Raja. We hear genome sequencing seems to be talk within the science community about solving the position medicine puzzle. We know genomes generate great insight, but a lot of it in many different places, therefore, what exactly is biocompute and how will it help address this growing challenge?

Raja Mazumder:
Thank you Maria, and that’s a great question. Genome sequencing, in my mind, has revolutionized the way we do biomedical research. We do biomedical research worldwide. When sequencing started happening, it became really easy to generate a lot of data and analyze it. Now, the problem that happened was that the data, but it was not being well documented. So biocompute helps organize this information in a way that is human and machine readable.

Jonathon Keeney:
I would add to that. I think you’re right, that genome research can really generate really great insights, but exactly how sometimes may not be clear. For example, the degree of variation in some sort of certain spot in the genome and whether or not these contribute to disease or just normal variance is sort of an ongoing question. For example, in genome research is still fairly new. So there’s still thousands of questions like this. And the way that genome data gets turned into useful information depends on the question that’s being asked and the way that the researcher is asking that question and the way that they’re trying to answer it. And so, because of all that variability, it can be very hard to follow what someone did. And so there’s, there’s been a real need for some way of communicating that information in a clear and articulate way.

And some labs have tried to standardize the way that they report that sort of information on their own. And that’s really great, but it’s often specific to the way that they do things and not widely adopted. And so biocompute has been great because it’s, it really abstracts away the process of a computational analysis from any specific way of doing things. It doesn’t matter which software you use or which platform or which strategy and so on. You keep doing things exactly the way that you have been. And because there’s been such a big community investment in building the standard that will help meet the needs of the most number of people. So different groups will know exactly what to expect when communicating their work to each other.

Maria Palombini:
Fascinating. I know I’ve talked to your colleague Dr. Vahan Simonyan many times, and he tells me, we’re just starting to scratch the surface of the amount of data we can get from human genomes alone. And he said that a year ago and it really holds true. This is fascinating work. So, Jonathon you know, we know that biocompute is a public private partnership and we kind of would like to know how it came about with the FDA and, you know, besides university and the FDA who are some other partners involved and more or less like, what are the motivating factors to join forces? I’m sure this was not born overnight.

Jonathon Keeney:
No, it wasn’t. Well, there’s a big difference in a standard in the application of that standard. Maybe you could standardize a cigarette later for your car and they have the same dimensions and the same power and the same safety, et cetera. And then people go and start using it to charge their electronic devices. So, you know, there’s a big difference between the way that something is standardized and the application of that standard. And so the public private partnership is meant to tackle issues like that. It’s a great vehicle for a federal agency that’s considering using the standard as a means to communicate next generation sequencing information to them.

So they say, you know, this is what we’re considering doing as a means to apply that standard. And the partnership will facilitate development evolution and use of the standard. For example, that could be in terms of joint projects with a common goal or formal integration of the standard into institutions or building extension domains that have their own consensus. One of the cool things about biocompute is that it’s got this, this user defined extension domain. So biocompute will work for probably 99% of all use cases because it was built on this consensus, but there’s going to be some specific applications where it may not. And so in order to deal with that, there’s this extension domain built in so that different groups can kind of modify it in their own way. The partnership can kind of help my building, some of those and things like that. The partnership is actually brand new, as you mentioned, the standard just published. And we’re recruiting for it right now.

Raja Mazumder:
In addition to that the partners that we have been working with for now several years will contribute it to the development of the standard, our industry partners pharmaceutical companies, bioinformatics platform companies, and so on, and also academic institutions. So a standard is only useful when different groups use it to communicate with each other also. For example, academic institution may develop this really amazing protocol for detecting viruses or detecting Rapids mutation and viruses. And then industrial partner can then take it to the next level and make the product a diagnostic product. And then they submit the product it’s a whole ecosystem. And at every step, there could be dozens, maybe sometimes more than that, people involved in developing this product. And it’s critical that when something like this is being developed, that every step of the process is correctly recorded and also standardized and biocompute helps achieve that. So it’s the whole process from all the way from the bench all the way until it reaches the bedside biocompute actually has a very important role to play. Last year we did publish a paper in plus biology with several of our collaborators on how biocompute helps precision medicine.

Maria Palombini:
I can totally see that Raja. I mean, I’m so glad that you highlighted the point because there are not many standards out there that I’m aware of that can really give you the gamut from bench to bedside. And this is one of the unique applications of the biocompute standard, you know and the other interesting about this Jonathon, was that I noticed you guys had a heavy focus on making it an open source standard. Do you want to maybe just explain a little bit why there was such a commitment or dedication to that concept?

Jonathon Keeney:
Yeah, sure. I think there’s a couple of answers to that. One is that we’ve taken great pains to make the entire process adhere to what’s called the fair standards. Findable, accessible, interoperable and reusable. And so this is a big part of that effort. And that’s a very big effort in academia right now. And in research generally to try and make research that conforms to that fair standard. The other thing is, you know, like I said, individual labs have standardized the way that they’ve done things and it’s great, but the real power of language of communication, like this is when lots and lots of people use it.

And we really needed to go through a formal standardization process. It’s well recognized and has a far reach, but we wanted to do it in a way that still empowers the individual researchers who are very independent minded. And having an open, open source repository allows different groups to build off of it in their own ways that might be integrated into their own systems. You know, so for example, if there’s a private company that has some sort of proprietary process that they don’t want to expose, and they there’s something about it, they want to keep to themselves, but they still want to build an internal way of handling that that is compatible with biocompute, we’ve made it very easy to do that, so they can fork off a branch of the repository and kind of build off of it in their own way.

Maria Palombini:
Excellent. P2791 is actually one of the first projects of the IEEE SA open source program. Everything just fell into the right place. Speaking of that Raja. So we’re focusing on the standard, the publishing of the standard, but there’s a little bit more to biocompute in the full suite of opportunities and services that it can provide just beyond the actual standard. Maybe we could talk a little bit about them and how they actually all work together and help in the entire process.

Raja Mazumder:
Yes. So using the biocompute, creating a biocompute, reading a biocompute and so on to get there. We do realize that sometimes it makes sense to have demos in our training. Right now, for example, we are providing treaty to FDA regulatory scientists on how to evaluate and use biocompute and these types of framings, you know, we are also recording and we are going to make them available through biocomputeobject.org and other places, really at a level where people can look at the reporting YouTube video kind of things. But on top of that, there is another thing that we have already started doing, which is registering the domain space for biocompute. For example, if you are a pharmaceutical company and you’re a big company and you have multiple products, multiple groups working on many, many projects, and you want to register a particular space for the view, which means, let’s say you are company X, Y, Z. All your biocompute starts with XYZ. So we have a mechanism in place which allows institutes companies, whatever have you to register their succession space within our compute object registry.

So this will allow them to be, to have unique identifiers for their biocompute objects as they go along so that they can refer to it when they’re submitting something or submitting some research work to a journal or, or even for their own in house lab note. This is really important. You also have ways where our mechanisms for people who do not have the resources to create their own biocompute object database, and their own interfaces to create a biocompute. So there are links which will take you to some tutorials to create a vital object that gets stored within the within the biking.org gaming space. Those are some of the things that we are working with. There, there are a few others that are going to come out within the next six months to a year. And we are really looking forward to it. Actually we are already working on some of the COVID-19 and the SARS related issues that is all on everybody’s mind. So biocompute is also playing, or at least we are trying to go to create right computer objects, which might help in that direction.

Maria Palombini:
You took the words right out of my mouth for, with regards to COVID-19, because we know this omnipresent pandemic may consume all of us. We know that the race is on right to find the vaccine hundreds of companies are getting into it. So my question to you is how, how can really biocompute help the researcher right now and beyond just COVID-19 what are some, what would you in your mind say, this is a great use case to use the biocompute standard, whether it’s in vaccine or some other sort of application within the healthcare ecosystem.

Raja Mazumder:
You know, that’s something, I mean, I’m wondering use the, the, the COVID-19 as an example, then I can talk about a little bit about a few other things. Right now there are thousands off genomic sequences for the SARS strains that are being generated. Many of them are getting deposited at NCBI or GIS aid or other places. And many of these genomes people are calling variations. They say these genomes of SARS strains, which were isolated from let’s say, Germany is different than what has been isolated from Australia. There’s a big bioinformatics application that has to happen for you to make those kinds of statements, right? You first, the next generation sequencing, you assemble all of the reads, and then you identify what are the new stations based on the restaurant strain that they’re using.

If I use the Wuhan reference string, for example, and you use a different reference strain or mutation profile a little bit different, and trying to dig in who is using what it’s time consuming and actually makes it very hard to figure out how to compare and contrast results from different groups from around the world, if people are losing biocompute objects. So when you tell me these are the mutations, and this is the biocompute object that defines exactly how I found it. Then when I analyze it, then I can know easily what exactly you did. And this is going to be important. And not only in identifying what are the different mutations circulating mutations right now in the human population, it’s going to help people who are working on vaccines or working on antivirals. We’re working on drugs to see how the mutations are happening.

Let’s say in the spike protein, which is one of the most important vaccine targets, the spike protein, which is a glycoprotein. So this is important. Now it has been important in the past. It has, it will be important in the future talking about the past. So several years ago, there was an outbreak of food pathogen in Germany, and next generation sequencing data was used to identify the pathogen fast forward several years. There was another outbreak of a similar pathogen over, in all care in the U S. Now, if we had the biocompute objects on the Germany study, then we could apply it and see, okay, so we are using the exact same methods to see if we are able to detect the pathogen that was detected in in, in Germany. So it saves a lot of time. It just saves a lot of effort, but on top of that, it helps us also see how by informatics methods and other technologies are evolving over time.

So, for example, what if the current methods are more sensitive? So you use the old biocompute object to then improve upon it, to say, hey, now we can detect at a much lower level, our faculty at it using this biocompute because you’re using a much more sensitive software and the name of the software and the portion of the software, then wouldn’t biocompute. So all of these things are not only important to save time and money, but also helps us understand, are we actually getting better at doing some of these things over the years, or are we just at standstill? And the algorithms are not getting better? So this is an easy and a quick way to evaluate these and the things because my computer objects also has a computer also has the input files, the output files, and also what are the possible errors that one can generate. And the validation that is associated with the, biocompute in together, all of this can help a user to run analysis what the original authors of the biocompute object had used an envision of what the sparkle should be.

Jonathon Keeney:
Yeah. That was a really great answer. The one quick thing I would add to that is that there has actually been a similar use case that I’ll mention really quickly which was something called the RE TB pipeline. And that’s a pipeline that the world health organization adapted for the detection of tuberculosis. And so one of the researchers who was funded by the Bill and Melinda Gates foundation actually came and presented at one of our workshop, the ways that they’re using biocompute for that pipeline for, for ways similar to what Raja was talking about. And so I think that’s a great example because it’s a situation where you have lots and lots of researchers that are all very geographically distributed around the world, and they all need to be on the same page fast, and they don’t have time for these big errors in communication and things need to be very clear.

And so biocompute is perfect for that. And it lets researchers as we said earlier, keep doing what they’re doing without needing to change anything about their workflows. It just gets everyone on the same page as far as how that communication happens back and forth, and it sets expectations for what data is in the document and where it exists and so on. And since there is so many similarities with, with COVID-19 research, I think that’s, that’s a really good use case example to kind of pattern some of this work after and it also kind of helps demonstrate the utility, you know, it sort of sets the precedence for using bio-computer in that kind of a way.

Maria Palombini:
Excellent. I mean, I automatically could see right away once I read the full standards deck about it. So, so Jonathon, this is not something you can maybe so easily just pick up and go with. I imagine there may be some training, obviously in today’s situation. It might be virtual. Do you guys have anything going on? How can people find out about if there’s any kind of training or a virtual training?

Jonathon Keeney:
Yeah, it can’t, I mean, we made it tried to make it as easy to understand as possible. You know, that’s sort of the fundamental idea is grouping all of the information into these conceptually meaningful categories. If you want to know the parameters, you go to the perimeter parametric domain, if you want to know the IO files, you go to the input output domain. So, you know, at a very basic, yeah, I get it kind of level. Hopefully it will be relatively easy to understand, but you’re right. It’s, it’s got a lot of depth to it and a lot of advanced things that you can do. And so as Raja mentioned, we are building training modules for the FDA right now to explain how to read a BCO, what information is in it, what to do in certain circumstances and so on.

And we can certainly build training modules for other groups based on our experiences, too. I think at this point, it’s safe to say we’re sort of subject matter experts in this space. And I think the best way to do that is just to reach out and to contact Raja. And I we are putting together a lot of different training modules and materials. We have a BCO editor that can help people. It’s a, a web based a form-based way to build BCS that’s on the web and it kind of walks you through building it. But as I mentioned, there’s more advanced things that you can do with it. I talked a little bit about the extension domain. There’s a lot of things that you can do in that kind of a case. If your, your project is very specific, you wanted to build a bibliography domain or a supplemental domain or something like that. There’s a lot of really cool things that you can do with it. And we can, we can most definitely help out with that and the best way to do that. It’s just to directly contact Raja. And I great.

Maria Palombini:
So we’re up on our time. I want to thank Raja and Jonathon for joining me today. I feel like we could have maybe made this interview for like two hours, cause there’s so much great stuff in there. We didn’t even start to scratch the surface of the opportunity for 2791, but also I want to share with all of you out there that 2791 is actually part of a new pilot we’re doing in the healthcare life science practice called the rapid activator program. And it’s exactly how it sounds. The idea is a recently published standard that we want to put to work and try to get some feedback on how it’s performing its environment. So if it’s a form of biotech company or a research organization using it and that way we can actually help educate on how to use the standard and what outcomes to look for and that kind of thing.

So if you’re a researcher out there or, you know, in a pharma or a biopharmaceutical company, or within a government research organization who feels that this would be a great opportunity for them, please do not hesitate to reach out to me. It’s [email protected]. Also, as Jonathon mentioned, the training and all the suite of opportunities, if you’re interested in learning more, you can visit www.biocomputeobject.org. There’s a whole bunch of great information there even how the, the whole biocomputer object came to happen. So I think that’d be a great resource and to learn more about the actual standard and other IEEE standards. And also P2791 is featured in our contributions and work we’re doing for COVID-19. You can visit standards that standards-qa21.ieee.org.