How Digital Therapeutics Are Changing Disease Management, Diabetes Care

In this roundtable, Daniel Sontupe, managing director, The Bloc Value Builders, moderates a conversation with Todd Prewitt, MD, corporate medical director, value-based health strategies, Humana, and Yash Prajapati, consultant, ZS, about bringing digital therapeutics for diabetes and other chronic conditions to market.

Read the full transcript:

Dan Sontupe: Hello, everybody. And welcome to Population Health Learning Network's panel on how digital therapeutics are changing disease management in diabetes care. My name is Dan Sontupe. I'm the managing partner of The Bloc Value Builders, a market access communications agency. We're here to have a wonderful discussion today, and let me start and introduce our panelist, Todd Prewitt from Humana. Todd, would you like to introduce yourself?

Todd Prewitt: Hi, Dan. First, I want to just thank you for having me. I am Dr Todd Prewitt, Corporate Medical Director at Humana for Value-Based Health Strategies and CMO of Humana Care Solution, our ACO Reach program. I'm a family medicine physician, a proud graduate of the University of Kentucky College of Medicine. After about five years of clinical practice, came into managed care, and in that role I've led clinical operations of a fully integrated utilization management, disease management, case management wellness platform at Carewise Health. Then I moved to a Louisville, Kentucky–based health insurance company called Humana to expand my experience in the Medicare space.

Before my recent move into the value-based health strategies division, I initially led chronic condition strategies and clinical best practice teams, enterprise clinical policy in the technology assessment forum. I've co-chaired the Pharmacy and Therapeutics Committee and been an integral part of our population health strategies work across all these efforts. Diabetes care management has been an integral component of my work, given that 30% of our senior population lives with this condition, and nearly another 30% are at risk for diabetes. It drives a sizable share of our health-related cost. It's an important space for us.

Dan Sontupe: Totally makes sense, Todd. And wow, you're a busy man. That's all I have to say. No time to go through the Louisville Slugger Museum, I'm sure. Also, let me introduce Yash Prajapati. I hope I said that right, Yash, from ZS Associates.

Yash Prajapati: Thank you, Daniel. Happy to be here. And similar to your reaction to Todd's vast experience, I'm excited to hear his thoughts. I'm pharmacist by education, consultant at ZS Associates. I'm part of the practice called Digital Connected Health. I'm part of 200 brilliant people who work with digital health solutions on both sides of the aisles as innovators, as well as adopters. My background in pharmacy led me to pursue health care management. I’m an alum of Johns Hopkins. Started working with digital health solutions early in the days when they were being adopted by the hospital systems and ended up pursuing that dream further with the other ecosystem partners working with specialty pharmacies, EMRs, and most recently, prior to ZS, I was in the state of Nevada working with COVID testing and monitoring solutions using, again, the digital health component. I'm really passionate about it. To Todd's point, diabetes is one of the chronic conditions that has really embraced digital health, and it has made impact and happy to share my thoughts and what I've learned from the industry.

Dan Sontupe: That's great. Well thank you both for joining us for this panel discussion. Digital health is starting to explode and it's challenging on how it's covered. What we're going to do, we all know about ChatGPT, everything is happening and the environment is changing dramatically. Let's jump in, and I'm going to start with Todd. How have digital therapeutics impacted disease management, patient access, and all these other considerations across health care today?

Todd Prewitt: Well, Dan, I'm old enough to have been in practice before we had any of this stuff and to have seen from the care management side a lot of the evolution of digital therapeutics and really have been focused a lot in the diabetes space. I joined Humana in 2011 to lead our chronic care strategies, which focused on kind of the rising risk population. We saw diabetes as a real critical threat to the health and well-being of our patients and our members. Our initial efforts were less about managing active diabetes but really wanted to concentrate a little bit in the preventive space. That's really where digital therapeutics kind of got a hold for us there. We were just trying to prove first of all that senior-aged persons would engage with a digital tool. That was kind of our first challenge, though we didn't realize how challenging the simple act of identifying persons at risk for diabetes was going to be.

It was clearly identified as an ICD code at the time as prediabetes, but of the nearly two and a half million members, we had a full year of data on from 2010, mind you, we only identified 9,000 members with a code for prediabetes. Based on the epidemiology at the time, we'd assumed about 30% would meet the definition, so we should have seen probably around 750,000 folks. So, before we could even get into the digital therapeutic space, we had a struggle trying to find these folks. There was a big gap there. Initially coding was scanned, so we leveraged some clinical analytics tools, predictive analytics to really identify conditions that were kind of leaning into metabolic syndrome where we had more data. We had glucose levels, cholesterol levels, height, weight, BMI that suggested there's likely going to be a blood sugar problem in this group of folks here.

And so, we identified a much larger population. Our initial effort was, “Let's test two tools against each other in the digital therapeutic space.” One was Canary Health, formerly Diabetes Therapeutic Solutions, which had a little more of a legacy kind of disease management platform, telephonic, they had online, they had some digital tools with it, but it leaned more towards the traditional disease management. And then a new starting company called Omada Health, which was fully online, asynchronous coaching, connected scales, app for education tracking.

In our first study, we saw similar engagements and outcomes from both of them. That actually encouraged us that digital therapeutics was at least as good as traditional disease management in terms of getting the outcomes and that our seniors were actually willing to engage with it, which was a big concern in the early days. We continued our work with Omada Health and even published our initial study of the 10,000 individuals that we found. But believe it or not, we only found 500 people who actually engaged with the device and sustained it sufficiently to get the outcomes for us.

And this validated our findings. We also noted that seniors were more regularly engaged with a digital tool than commercial-age members. We kind of put to rest this concern that they wouldn't use the tools. We saw a greater percentage of those folks actually achieving targeted weight loss. We're targeting a 5% body mass loss over a 12-month period of study. Subsequently, we followed these folks for another year, and we published a 2-year follow-up indicating that, while not quite sufficiently powered to indicate statistical significance, we decidedly saw trends toward improved strain on health care resource utilization. Digital therapeutics seemed to activate patients in their health and this was sustainable. That was the prevention space. Diabetes was really a driver for us, and once we proved value in the prevention space, we moved to work with digital therapeutics across the disease spectrum, but specifically in diabetes platforms which integrated multiple conditions adjacent to diabetes: hypertension, weight management, diabetes distress, depression.

We were concerned about the negative consequences of years of poorly managed diabetes resulting in foot wounds, kidney disease, eye disease, not to mention all the cardiovascular comorbidities. In these areas, we saw the development of digital therapeutics that included foot pads measuring changes in temperatures suggesting the development of a foot wound. Socks that had temperature sensors woven into the threads, layering in of biometric measuring devices like the glucometers, insulin delivery devices, scales, blood pressure cuffs, exercise monitors, tracking tools, cameras that could measure wound size in an app and give us consistent wound size and depth measurements. Software that would help members with these chronic conditions take actions incremental to improve their health if they chose to act upon the advice. Many tools integrated with patient support networks to allow patients to engage with each other in solving real-time problems that they encountered managing their diabetes. Consumer experience proved to be critical we saw thought to the success of these tools.

And finally, as the diabetes digital therapeutics have exploded in condition management and they will continue to evolve, AI and machine learning are going to more fully integrate these data streams and embed into the workflows of physicians who are managing these patients and payers like Humana, whom I work for, who are trying to really get access to broader data than just claims and all to help better understand the risk within their populations. I think the digital therapeutic tools that survive will demonstrate strong patient engagement that is sustained and it'll evolve with the patient's changing circumstances and they're developing clinical risk and it's going to integrate with the online tools and resources both at the patient level, so it becomes part of their just daily experience, as well as in the physician's workflows.

Dan Sontupe: That's incredible. And the amount of knowledge you have about the diabetes space and digital health is, I think, second to none. Yeah, Yash is agreeing. I want to pull us back a half a step, Yash, and think about just even beyond diabetes. How is digital health actually affecting health care access, disease management programs? If you go beyond diabetes, what's happening?

Yash Prajapati: Based on the experience, and not as vast as Todd's, but what we have seen is the early 2000s started seeing the rise of EMR systems if we go back to the true IT engagement that led to the digital health boom. In the practice or care flow, it starts addressing the administrative inefficiencies. That's how sort of the adoption of digital health tools start. And what we are seeing is from that administrative point of view, most of the care workflow integration starts with chronic care management, and diabetes is a great example. The other lifestyle diseases can also be part of it. We have seen great adoption in the COPD space. We see that oncology care, which is again the high risk, high reward and personalization kind of space where therapeutic areas need more resources to be thrown in, that's where digital health is evolving. And triangulating it back where digital health can have efficiency and personalization, together, now we are seeing, to Todd's point, where AI is coming in, learning about patient behavior, something that we have seen in finance, something we have seen in consumer tech where your behavior, your adoption can be changed with technology is now slowly creeping into health care.

And we are seeing that more and more consumer tech is now becoming patient tech. Similar to solutions which are, let's say Omada or Welldoc or Livongo, which played in the health care world initially just focused on measuring this one outcome. If they can have engagement, if they can show utilization, if they can measure HBA1C or even BMI, which again as a physician, Todd, may or may not refer to as let's say a level one of outcome and he would like to understand more of the patient, that's where digital health is evolving and trying to add more data points so that we can create a holistic picture of the patient. And it's not just happening with diabetes, it's also happening with, like I mentioned, some of the other chronic diseases.

Dan Sontupe: That's great, Yash. As these organizations are starting to launch digital medicines, one of the blocks for them is the idea of who's paying for it, how do they monetize it, right? And so, one of the big challenges comes back to the payers, market access. What do you see as the challenges related to getting these products approved and essentially paid for or implemented within payers?

Yash Prajapati: I'm happy to take that, Todd, and as a payer, I'm sure you have more answers there. Based on what we are seeing, some of our clients who are digital health solutions, their first struggle is not really knowing who their clients are. Even within payers, we see the markets of the national payers, we see regional payers, the ACO models. We also see some of the more employer-focused, self-insured plans, right? The US health ecosystem is complex, to say the least. And more often than not, these solutions as they're trying to be more patient and product focused, forget that they still have to be part of the ecosystem. The first challenge is knowing your position, knowing who you're attracting, why you're attracting them, and where you want to create that path. More often than not, we end up helping them identify their market access strategy to understand that where should be the first impact. How do you start building more and more evidence so that you buy yourself the seat on the table when you're talking to the national payers?

Once you have gone through the initial struggles of being a startup, the second challenge I would like to say, the teenage challenge of a company comes when they're thinking of a broader or sustainable reimbursement. And that's where we have to rely on the big behemoth, CMS. CMS has adopted digital health. I don't want to say they haven't. They have tried infusing value-based metrics. Again, the success or failure of that is debatable. But some of the things that they have tried is there was a program called MCIT, they were trying to reimburse for evidence generation. That was rescinded in 2021 and there is a new proposed rule called TCET. These different programs allow innovators space to utilize evidence generation reimbursement and start building their evidence.

But, having said that, getting reimbursement from CMS is really tough. It takes years of effort and I don't even want to quote how much money it's going to require because more often than not, startups just cannot afford to have that. Hence, when it comes to finding a long-term growth path, they have to find the right partners, they have to find the right path to work with them. And like I said, the first thing, know your position in the market and the ecosystem. These are the initial challenges, and I'm sure Todd can elaborate more on when it comes to payer side how the brokers, actuaries and benefit design becomes step two of the challenge of being adopted.

Dan Sontupe: Makes sense. Todd, anything specific you want to add?

Todd Prewitt: Well, Yash brings up the biggest payer, CMS. And I mean when I think about the journey we took in the diabetes prevention pathway here, and when CMS finally decided to cover that, they specifically left out purely virtual digital therapeutic type of solutions in that space, which really presented a huge access issue for getting patients who did not have access to an in-person type of diabetes prevention program. Agree with him, CMS is probably the beast that most needs to be conquered in the digital therapeutic coverage type of space here.

But when you think about it from a payer perspective, I think about it from in terms of engagement, in terms of ROI, and in terms of integration slash consumer provider experience kind of stuff. From an engagement perspective, I continue to believe that the identification of the patients who are correct to engage in a digital therapeutic, who timing-wise are going to receive the most benefit, who are most ready and willing to adopt to a specific digital therapeutic tool and to sustain it sufficiently long, as Yash was talking about there, that you're going to actually create behavioral change and that's going to result in a biometrically observable improvement in health. That, we're targeting, because we know, ultimately, it's going to reduce health care resource utilization.

That's how you get to proving the return on investment at the end of the day for both the patient as an investment of their time and the physical changes that they actually have to implement and adopting these new behaviors, as well as the health system. And I think that's the biggest challenge. Towards that end, I'm currently working with the University of Houston on our Humana Healthcare research team to develop an AI tool identifying patients with diabetes who are progressing and/or likely to progress up the diabetes complexity and severity index over the coming 12 months. And then really trying to drill in through AI to identify the true drivers of that risk in terms of gaps in care or specific actions that if the doctor took it and they had this information at the point of service, they're likely to be able to prioritize that care intervention in a much more effective way.

So, trying to more efficiently get information into the hands from all these data resources that are out there in the cloud and connected data universes here, impacting those drivers of health will improve the outcomes, will improve the resource utilization. And the point of that is around this ROI construct here. When you demonstrate to a health payer or a physician group, remembering that many of these physicians, particularly in their primary care space, which, and Dan you mentioned earlier, type 2 diabetes is a main focus here. Primary care is where majority of the type 2 diabetes care gets managed and these folks are moving, these provider groups are moving into value-based care contracts, and thus they're accountable for the cost of these digital therapeutics at the end of the day. The specific population they're managing, knowing who's most likely to engage and get results and being able to prove to them the value of your digital therapeutic tool with that group will become much more evident as the studies come out and you're able to put that information into their hands. And to the extent that you can take a sample of their population and run it through your analytics and show that you know who to identify within there and can project out savings, that's going to be really critical.

The other real key piece here though, I think, in this is leveraging the doctor and the physician office as an engagement tool. Getting them that information or leveraging them in some way as a screening tool is going to be a big component of that. Now, transparency aside, I work with a company here as a clinical advisor. It's called Prevent Scripts and they're really focused in the early stages here on the prevention space and specifically prevention of diabetes. But they found a really unique engagement strategy where they leverage the physician office to actually perform the screen and then that information gets pushed through their EMR directly to the physician at the point that they're engaging with the patient. That allows that physician to have the conversation about, "Hey, we're heading down this path. We have a tool that we'd like you to leave with here. It's a digital therapeutic that can then actually be uploaded by the office staff before the patient even leaves the office."

And so, instead of writing a prescription or e-prescribing or having a payer or whatnot push information to a patient separate from that healthcare engagement, it seems to be a really unique way to do that. And then they teach the doctors how to manage the tool that's actually in their EMR to monitor that patient and the doctor can actually get reimbursed for it. That's one way, I think, that you can solve this problem in the fee-for-service space here. And we also know by doing that, strong patient engagement comes from knowing that my physician specifically has prescribed this tool, their office helped me get that app loaded, I was enrolled before I left. It avoids all that enrollment-engagement-marketing type of issue here and the patient just not picking up their medicine as we said.

I think the more unique ways that digital therapeutic innovators can find to embed these tools into physician workflows and into patient daily life flows, which is really critical, the more consistent utilization we're going to see—and consistency drives quality and that's going to drive improved health.

When I talk about integration for a second, Dan, let me just finish this point, sorry. But as for approvals and physician buy-ins and getting onto payer formulary specifically, clearly you've got to have the published clinically valid study, it's essential. But remember, patients also don't typically only have one condition. How does the multichronic patient with this tool operate? That consumer experience is really critical to success. How does your digital therapeutic adjust recommendations? No, not based on known comorbidities. For instance, a member who has diabetes but also has heart failure and wakes up with a high blood sugar, does the app recognize that they have heart failure and instead of recommending eight ounces of water and retest in 15 minutes not knowing whether or not that'll push them over in the fluid overload, it will adjust those recommendations accordingly. Will it account for that?

I think that's critical to adoption at the physician level, but as a payer, I want to know that you're thinking about the whole patient. And then if you can integrate the consumer experience of health management and as an online, virtual, cloud-based world and make it feel seamless to me, the consumer. Does it demonstrate a true deep understanding of not just the patient condition, but my lifestyle? What are my learning preferences, what are my personal health care goals, how do you incorporate those insights? This will be essential, I think, to the expansion and the adoption of very useful digital therapeutics and medical treatment. And based on developments we see underway, it's really an exciting time, especially as AI is starting to take off as a more real solution and understanding all these learnings and studies and being able to elevate the right solutions at the right time for patients. Machine learning, the sensor monitoring tools that are being developed that are integrating into everyday practice for our patients, our physicians, and providers, I think the future's really bright in this space.

Yash Prajapati: Todd, something that you mentioned, value creation and value differentiation for multichronic conditions and identifying which part of a digital therapeutic is really creating impact. I'm curious to know your thoughts there. When a payer is evaluating a tool and based on what we are learning out there, total cost of care, again, becomes very important, especially in value-based care arrangements. However, it does not need to be limited to just one payer paying for one patient. There are more than one stakeholders in the system who are sharing value. More often than not, we are seeing the construct of two stakeholders coming together, getting into this arrangement of a payer or a provider, but we have this pharmacist, we have the pharmaceuticals, we have some of the other stakeholders who are not sharing the burden.

Curious to know your thoughts as a payer. How do you think about evolving this model to a multistakeholder value proposition? The role of data brokers, data stewards, we have seen them since the seventies, eighties, now they've become more of a middleman, but the need for a shared or unified data stewardship to identify, document, and distribute value for digital therapeutic to evolve into the model that you're describing where value identification, differentiation becomes more unique and pertinent to what the patient is actually experiencing.

Todd Prewitt: The team I'm on currently, Yash, that is really a huge part of our focus. Value-based strategies is trying to help define that. And quite honestly, there's way too much to be learned in this space still. We talked about primary care kind of being on the lead front of value-based care contracting, right? The specialties are starting to go down this pathway. We're really deep into late-stage CKD, ESRD, value-based care contracting with the nephrologist groups. But then you think about how many of those patients also have cardiac conditions or endocrine underlying conditions and stuff. As the cardiologists want to go down the value-based care space, as the endocrinologist go down that space, you have all these specialties where there's a lot of overlap. How do you define as a payer or really anyone which ones of those condition spaces is going to drive the most value in terms of outcomes for health for the patient, but that ultimately is going to create that ROI and how do you tease out those variations in there? And I think that's one of the big challenges we're facing in this space today.

Bundles are a little easier. It's around a procedure or it's been maternity care, you can bundle all the care around that. It's an orthopedic or a neurologic procedure kind of stuff. As you look at total cost of care and total health and defining ascribing specific drivers of value within there by specialty or by conditions, it gets really complicated really fast.

Yash Prajapati: Yeah. And sorry to go off script, Daniel, but leaving with last thought on that thought, specifically solutions which are not point solution for one therapeutic area, but the core value of prevention, patient identification from data or monitoring, these are some of the jobs to be done in the market. When you're really good at doing it for one therapeutic area and you're able to use the tool to create the separate workflow for another therapeutic area, in our view, then they become more important to a payer. Now you're addressing more than one therapeutic area or a multichronic patient. To Todd's point now, rather than having to contact with 10 different solutions, solving for 10 different problems for one patient, industry is now looking for solutions that can address the whole patient, multiple conditions together. And going back to just the ROI, you are able to measure ROI better if you have a good risk model at the start so you know where the risk is, and you have a better monitoring or measurement model at the end so that your evidence meets up against the goals.

Bringing it back up in the practice, what you're seeing is there are, Omada being a staple of how to prevent prediabetics going into diabetes and just identifying the right patient, we also see that when it comes to treatment, the WellDoc or Virta, integrating it into the clinical care flow, bringing the provider in. And in the treatment and monitoring side of the house, we have seen tremendous solutions from connected devices all the way to patient monitoring apps. They come into picture with examples like Livongo, Onduo, we see Dario Health also playing in that realm and similar solutions even in the blood testing realm where they're coming up with patient-facing application like One Drop, all these numerous solutions are coming in the market. The challenge remains because one patient's needs change as far as their lifestyle changes, the time in the condition changes. Solutions need to adapt to what the patient needs as part of the phase of the disease they're in, not stay stagnant. And because this is a thriving ecosystem, solutions which figure out how to follow patient and meet where they are, are going to be more successful.

Dan Sontupe: Yeah. No, Yash, I think those are wonderful points. The challenge that we deal with is a lot of the digital medicines that come out today are based on one therapeutic area. The same way these companies have built for one therapeutic area, a pill or an injection or an infusion for that therapeutic area. And that's the model they continue to go on. I think we could all agree that it makes sense to look at the whole person and if I'm Todd making a decision, I don't want a one diabetes and a one heart failure and a one cholesterol lowering and a one, that's too many.

There'll be other organizations that come in with a whole body approach, and share a voice is going to be very interesting to see how they approach the Todds of the world in the future.

Additionally, how does a product like that get covered? And that brings it right back around to how does CMS cover it, how do those other organizations cover it? But you mentioned Dario Health as one of the things that we've talked about. There are lots of digital platforms, data is showing positively, Todd, you mentioned you've got to bring data to the table. What do these organizations have to do to really have an impact at a payer to really show that there's engagement? What is the data, what do they have to show, how do they really get in and get deeper? Yash, I'll start with you.

Yash Prajapati: Sure. I'll pick back up from Dario. Something that they've done really well is published their clinical results. There is no replacement of hard work. And as a digital health solution, you have to come in, you have to prove utilization early on. You have to prove the effectiveness that they're bringing to patient as well as the stakeholders. Again, if you check out Dario's website, they have shown that they can reduce HBA1C levels. They have shown that they can have an impact on patient's weight, some of the indicators of controlling diabetes or controlling the patient who might, again, end up increasing in risk. These effective measures have to be put forth when they're having conversation with the payer.

Now, once you have those as part of your case studies or as part of your pilots or even clinical trials, that only does step one of buying yourself a conversation with a payer. You will be required to also impose that on Todd's population. He's managing, let's say, 1.8 million lives. And out of that, how many are relevant patients that you can actually address? And more often than not, startups end up making the mistake of overpromising and underdelivering. And the reason why I say that is if you have seen success in one, let's not have optimistic goals of having the same impact in a new population. As someone who has been in health care, I recognize, and I'm sure most health care consultants will agree that population is unique, your health can be global, but your patient has to be regional. They have to be treated at the level they are. And digital health solutions have to be conservative in proposing what they can and cannot make an impact to. Start small, learn with the payer and to be honest, connect the real-world evidence in their practice before they start making big contracts and big strides. As sad as it might be, health care is slow and we need it to be a little faster, not disruptive, so that everyone can adopt to it.

Dan Sontupe:Todd, we're getting close to wrapping this up. I'm wondering how much of a utilization management impact do you see coming from the Dario Healths of the world and these other products in digital medicine for you and your colleagues and your peers in the health care insurance space?

Todd Prewitt:I think the better question to ask in there isn't how big of an impact, but how long does it take to actually see the impact?

Dan Sontupe: Right.

Todd Prewitt: The further up the stream from active disease management you get in the prevention space, the longer that tail is to begin to actually see an impact on cost within health care resource utilization. It's been one of the biggest challenges, I think, for a lot of where this space really started intently is in that prevention space. It takes a long time to prove a null event that somebody didn't develop a condition because they made these changes and prove that they actually did those changes.

So, I think it's a combination. My advice usually in this space is start with a real near-term issue that you believe can be impacted by your device. Whether that's emergency room visits, whether it's observable process changes like seeing a specialist or seeing a physician at an increased frequency. And then to the extent that there are some early indicators that you can measure from lab or biometric tools that begin to show progress toward there, I think you're on a good footing.

But then proving that to an actuarial certainty, which is typically required on the payer side here that it has actually paid for itself through reduced health care resource utilization. Those changes have to live within that patient population for a long enough period of time that we can now measure it in health care dollars and cents. And so that is a multimonth, multiyear process typically. And typically, we like controlled studies where we've got a good test and control group that are well-matched and those are expensive. Those are hard to do and they take a long time. Coming in with expectations that a 6-month ROI study is going to be bought by all the big payers might be a little overestimating the ability to impact it or to Yash's, good point, it worked in this population, we're sure you'll get the same results across the board. Which, when I first came to Humana, I was working more in a commercial-age population. It's a different world. And those two segments of population health do not get the same returns on programs like this.

I think those would be my major cautions. It is possible, but really defining how you’re going to do that and where you're going to make early impact versus how long you think it's going to take to get to a measurable, provable utilization outcome, I think, are critical in those early studies.

Dan Sontupe: That's great, Todd. I really appreciate it. Yash, anything quickly you'd like to add?

Yash Prajapati:Yeah. I want to add one, and again, this is one point to the actual analysis and its impact on utilization on the commercial side and how it's reimbursed. Prior to, say anything out in the industry, actual analysis hasn't evolved to real-time data that we get. I've had conversations with actuaries, some of my close friends are actuaries, and there is consensus amongst at least the optimistic group that we are seeing the industry rapidly changing. To Todd's point, even though ROI does not or cannot be realized within 6 months, Todd from experience, please correct me if I'm wrong, more often than not within 3-6 months, you have a good indicator of if this can scale, if this can really make an impact on the population. Now, if we have a positive or negative reaction to it, the question then becomes how much?

And I think that's where the industry gets it wrong. A good solution has to be nurtured, and the digital health industry right now is taking baby steps, it's slowly growing. And the emphasis for any solution to be adopted—or the burden of adoption—will rely on the stakeholders who are able to move mountains. In this case, the payers. Their willingness to work with solutions which are showing positive impact, positive utilization, support them with enough reimbursement that can help them survive and thrive so that they can start seeing the return is going to be the path for success.

Now as I say that, I know it sounds too good to be true. There are other factors at play, but Humana, for example, some of the other competitors of Humana, we have started seeing payers adopt to pilots, adopt digital health solutions in specific areas like I mentioned, COPD or diabetes. And I think those are positive signs for digital health innovators to latch onto that. Don't be greedy, don't ask for too much, make sure that you prove value as you grow, and you keep pushing the envelope further. Same as we have seen with some of the other services when they came along in nineties or early 2000s. DME has seen the path to growth decade over decade when they started proving more value. And digital health has to learn from how other solutions came into this industry and how they adopted.

Dan Sontupe: Yash, very insightful. And this is the process that all new therapies and all new products go through.

Yash Prajapati: Yeah.

Dan Sontupe: Completely makes sense. I think we are at time. I want to invite Todd, if there's any last comments you'd like to make.

Todd Prewitt: First, just want to thank you again for inviting me to share my experience. This is a really exciting clinical treatment space and I want to encourage your audience to really consider the need for a digital therapeutic and improving the quality of life and health outcomes of patients living with diabetes. What gap in care are you identifying that it's driving risk in that population, for which existing physician care disease management solutions have failed to resolve? What makes your population a good fit for a digital therapeutic? Assess the clinical evidence that any digital therapeutic company brings forward critically. Push to understand engagement insights and to ensure that a sufficient number of your patients are likely to use the tool. And in the end, consider putting the developer of these tools in an at-risk contract based on shared savings, targeted enrollments, sustained engagements in order to achieve outcomes. And I think the more you lean into that, it reduces and shares some of that risk and improves the likelihood that you're going to get some adoption of these, and really we need to learn how to fit that into this whole treatment range of options that physicians have and it'll help bring more proof points to them as well.

Dan Sontupe: Wonderful. Yash, anything you'd like to add?

Yash Prajapati: No, I again, thank you for allowing me the space to share my thoughts. It was exciting and inspirational. Todd, thanks a lot for sharing the experience that you have, not only building solution, adopting them, and your thought process on how they should be adopted further in the industry. And all I would say is digital health solutions have to have the evidence before they start asking for reimbursement. We take pride in working with some of the solutions that we work with, and we try to just make sure that we are on the same page as far as timelines are concerned. It's going to be a slow burn, but that does not mean that there is no light at the end of the tunnel. We have seen it post-COVID as well. There is sustained adoption of these tools. Industry is changing, and we are lucky to have leaders like Todd and some of the other payer-providers who are adopting new tools that is going to hopefully improve the system for the better.

Dan Sontupe: Couldn't have said it better. Todd, Yash, thank you both for this insightful conversation. To our viewers, thank you for joining us and participating in this day for Population Health Learning Network. Thank you. My name is Dan Sontupe. This has been a wonderful conversation.

Todd Prewitt:
Thank you, Dan. Thank you, Yash.

Yash Prajapati:
Thank you, everyone.

This transcript has been edited for clarity.