Predictive analytics and artificial intelligence are no longer futuristic concepts in healthcare; they are active components of modern strategy. Yet, many sophisticated AI models fail at the "last mile." They can predict an adverse event with stunning accuracy but remain powerless to prevent it. Why? Because data alone doesn't change outcomes. People do.
In a recent Strategy of Health podcast episode, I spoke with Joseph Vattamattam, co-founder and president of Healthmap Solutions, a company that has built its entire model around this truth. They are proving that the true power of predictive AI is not just in its forecasts, but in its ability to be translated into actionable, human-centric interventions that empower both physicians and patients.
To build a program capable of tackling a problem as complex as chronic kidney disease (CKD), you first need to build an exceptional team. Healthmap Solutions has assembled a roster of industry leaders, and according to Joe Vattamattam, the "secret" is a culture built on an actionable and realistic mission.
This mission-driven culture is centered on aligning the company's financial incentives directly with patient well-being. “We have such a strong culture of mission here," Vattamattam shares. "...we align the money to the mission. Meaning the only way we get any revenue is by reducing the cost of care." This isn't just an altruistic talking point; it's a hard-wired business model. Healthmap only succeeds if patients stay healthier and out of the hospital. “The way we reduce the cost of care is by reducing, you know, the unnecessary admissions and visits to the emergency department," he explains.
This alignment creates a powerful sense of purpose that attracts and retains top talent. When a team's success is defined by measurable improvements in patient health, the work transcends the day-to-day and becomes a "noble cause." Furthermore, Vattamattam notes that great people want to work with other great people, and the company's leadership has leveraged past professional relationships to bring in proven, successful teams from prior ventures.
Before a single predictive model was built, Healthmap Solution's used its deep analytical expertise to challenge long-held assumptions about kidney care. Vattamattam, who has a background in mathematical finance and investment banking, brought a quantitative rigor to the company's initial strategy. They didn't just accept the industry's conventional wisdom; they let the data define the real problem.
This data-driven approach uncovered three critical, counter-intuitive insights:
Myth 1: Focus on the sickest patients. The assumption was to focus on End-Stage Renal Disease (ESRD) patients on dialysis, as they are the most expensive on a per-member basis.
Myth 2: Focus only on nephrologists. Kidney disease is a nephrologist's specialty, so they should be the only physicians to engage.
Myth 3: All CKD patients are high-cost.
This last finding, in particular, made the strategic path clear. To manage the cost and improve the outcomes for this population, they had to develop a sophisticated predictive model to identify that high-risk 30% before they became high-cost.
Healthmap Solution's predictive model is its "secret sauce," capable of forecasting adverse events 6 to 12 months in the future. But Vattamattam is quick to point out that a prediction is useless if it's trapped in a "black box." The challenge with many advanced AI models is that they can tell you what is likely to happen, but not why. To solve this, Healthmap solution's built a second, related model that functions as a "driver report."
Here’s how it works:
Prediction: The AI model analyzes a massive dataset (informed by over $30 billion in healthcare expenditures) and assigns a proprietary risk score to a patient.
Explanation: The "driver report" model then identifies the top clinical and non-clinical factors for that specific patient's risk. It translates the complex "why" into simple, actionable terms (e.g., "neurological and musculoskeletal issues," "running low on anti-convulsant medication," "recent ER visit").
Action: This simple, clear report is delivered directly into the workflow of a Healthmap solution's frontline clinician.
This transforms the entire care dynamic. Instead of a generic wellness call, the clinician can have a highly specific, high-value conversation. “They're able to converse... at a very meaningful way to say, ‘Hey, we noticed... you're running low on these drugs... We also know you have chronic kidney disease. Let us help you navigate the next 30 days...’," Vattamattam describes. This connectivity is where the true value is unlocked. “I think the connectivity between the AI ml stuff and the technology platform is where the magic really happens for Healthmap Solution's”
This brings us to the core thesis of Healthmap's success and the title of this article. All the data, analytics, and predictive models are ultimately just a means to an end. The real goal is changing human behavior.
“They [analytics] don't really make any difference unless you can change some human behavior," Vattamattam states definitively. “At the end of the day, we need a patient to change their behavior, potentially a provider to change their behavior.”
This is why Healthmap Solution's refused to create a data-only solution. They knew from the beginning that a "pure data model" that bypasses clinicians would fail. These patients are complex, often seeing three to four different providers and taking 15-20 different medications. You cannot effectively manage their care without becoming a trusted partner to their physicians.
This philosophy is what drove Healthmap Solution's acquisition of Careium, a technology platform designed to operate at the "healthcare delivery edge." This platform acts as the final-mile conduit, connecting Healthmap's insights, the patient, and the provider's care team. It's the tool that facilitates the behavior change.
This integration also opens the door to new data streams, such as remote patient monitoring (RPM) and wearables. While Vattamattam says it's still early, the company is excited about the promise of integrating biometric data from weight scales, blood pressure cuffs, and glucometers to provide even earlier leading indicators of risk.
When asked what's next, Vattamattam sees a clear path forward: replicating this model for other complex, multi-chronic conditions.
The Healthmap program, while focused on kidney disease as the "ticket of entry," is already a comprehensive, whole-person care model. “Once you're in, we're working on everything with that member," he says. “We're working on their cardiac issues, you know, COPD, behavioral health, social determinants of health.”
Because they have already built the clinical programs and predictive models for these comorbidities (like heart failure), expanding to new disease states is a natural evolution. The core asset is the replicable process: a technology platform that combines powerful predictive analytics with a human-driven, clinician-integrated workflow. This model, Vattamattam believes, could be a game-changer for population health across the industry.
The Healthmap Solution's story provides a vital blueprint for healthcare leaders navigating the AI revolution. The value of predictive technology is not in its computational power, but in its application. True transformation doesn't happen when a server flags a risk; it happens when that insight is demystified, translated, and placed in the hands of a clinician as a tool to build trust and guide a patient toward a better action. This isn't about artificial intelligence replacing human judgment; it's about augmented intelligence supporting the critical human-to-human relationships that are, and always will be, at the center of healing.
<p>They don't really make any difference unless you can change some human behavior. At the end of the day, we need a patient to change their behavior, potentially a provider to change their behavior. [Music] Hello everyone and welcome to the strategy of health podcast. My name is Cole Lions from the American Journal of Healthc Care Strategy.</p> <p>Joined by just an incredible guest today from a company that I've been working with for a while who is doing just really incredible things not just for the kidney population but also as a a template and an example for the rest of the healthcare industry. Uh please uh introduce yourself. Uh Joe, >> nice to to talking me. Um Joe Vadam, I'm the co-founder and president of Healthmap Solutions.</p> <p>um started the company in 2013 with some other co-founders and um you know I'm happy to say we're still here and uh doing great things for um the the chronically sick population specifically those people who have chronic kidney disease or endstage real disease. Uh we've been doing that uh in particular for the past 10 plus years.</p> <p>Um, and we've helped tens of thousands of people across the country um have improved health, avoid adverse events, um, and you know, we'll be as bold to say is that we've we've saved some lives. So, uh, really excited and proud about what we've accomplished here and what we continue to do at Healthmap Solutions. And before that, um, I worked at a company called Care Centrics that was focused on homebased care, post-accute care. I led the medical economics team.</p> <p>We built products while we were there. So, I was part of a team that would do that and a little bit of um acquisitions of of certain companies uh to be able to really drive care into the home. >> And prior to that, I worked at WCare. We saw what things were like on the the payer side of of the fence uh serving government programs, government uh so Medicare and Medicaid and uh and prior to that I was an investment banker. Um but pleased to be with you here and excited for the conversation.</p> <p>>> I'm pleased to be with you as well. And just for so the audience knows the context, we've had of course Eric Rmmer, he's uh Ramer, he's um CEO right now as well. We've had him on twice. We've had Dr. Stephanie Toth Manowski on once, Beth Dr. Beth Malco on, uh Tom Gaffne, and so we've had most of your kind of pee on uh or you know your senior team and I think they've really impressed the audience with a lot of things.</p> <p>One of the questions that I have for you, how did you get these skills to build such a good team and to get so many of these great people that you've kind of surrounded yourself with? Uh I mean, how did you do that? How did you get that that skill set? >> Oh, um well, look, I I I think um we're we are very fortunate to have the team that we have, right?</p> <p>So, I I don't know that I've ever worked with such a strong management team that has such a great background of success um in other areas and has the amount of passion and energy and excitement around doing what we do here at Healthmap.</p> <p>Um I'd say there are a lot of just even beyond th those executives that you mentioned and the other people that are sort of in the seauite so to speak I would say all of our leadership uh and and for that matter almost every employee we have I would venture to say a lot of folks here could be doing other things they choose to be at Healthmap because we have um such a strong culture of mission here right we're really focused on improving the lives of people who have chronic kidney disease or multiple chronic, you know, conditions as people with kidney disease do.</p> <p>And I think that gives people a great sense of purpose, right? To be able to put their their talents to use um on what is really a noble cause. And I always like to say um we always, you know, that our mission is real because we align the money to the mission. Meaning the only way we get any revenue is by reducing the cost of care.</p> <p>>> And the way we reduce the cost of care is by reducing you know the unnecessary admissions and visits to the emergency department um that's how we really drive value. And so while it might sound altruistic to say it's very missiondriven um it's very realistic for us right because that's how our economics are structured.</p> <p>I I also think that you I'll attribute a lot of a lot of that towards um a lot of the leadership team and and and being able to attract folks um less about a skill set that I've acquired and more about uh just you get one great person from a place and and good people want to work with other good people that they've had success with in the past. When you look at our team, we have a lot of that, a lot of um connections in the past. I mentioned I worked at Care Centrics.</p> <p>Eric was the CEO of Care Centrics. And uh when I started this company, I sought Eric's advice immediately before me and the other co-founders started the company. I talked to him. I said, "Hey, here's what I'm thinking of doing. What do you think?" And so in in an unofficial way, he'd been involved at least from with me from the from the very start. And when you look at Tom Gaffne, he and I worked at Care Centrics together. Um a lot of folks worked there.</p> <p>Some folks came from Carecore or Evercore. uh if there's a little group there and and it's fun to be all working together again in this one common cause. >> I've noticed that a lot that there is this deep kind of pride and appreciation for the work and that kind of goes to my next question.</p> <p>you know you have an MBA you have a mathematical finance background you know kind of the one of the questions is why you know when I Google you know Joe Vadamatam today you are known for quite well in the healthc care space and and you say it's not altruistic and it is and it's very realistic I've you know talked about the numbers a lot with Tom the growth numbers but at the same time it is a very kind of altruistic mission uh and it is a very positive mission so why when I Google you today are you this kind of very health focused you know you care a lot about the patients.</p> <p>What what didn't you why didn't you go into investment banking, I guess, and and what skills did you kind of learn from that time period with your math background, with your MBA background, with your investment banking background that maybe you didn't expect would benefit you so much at first?</p> <p>Yeah, I mean I think the all that all the quantitative work that I've done in my past has served uh me well in the work that we do here at Healthmap and and in starting the company and um really sort of setting a strategic vision. I I think we're very different from our competitors.</p> <p>Um and I do think that a lot of that has to do about with um our approach when we first decided the kidney disease space is the space for us right we looked at it and um really was focused on how do we reduce the cost of care by improving clinical outcomes and when you look at that it really like sort of drives a product market fit and I think that's what set us apart from others and has helped us to have a lot of success and A lot of that had to do with analytics in the very beginning.</p> <p>Just how do you even approach this? And I I would even say some of the work from banking and figuring out how to create a business that can create value um and have the right types of economics with the right types of aligned incentives all mattered a lot. I I'll give you some concrete examples. >> Yeah.</p> <p>started down this path and um intuitively when you think about the kidney population you think ESRD members who are on diialysis or have a transplant are your highest cost members start there like that's where you should try to drive the most savings um at least in on a per member per month basis they're going to spend the most and that's true on average that is very true um but what we learned over time in speaking with physicians because it's such a clinical program.</p> <p>Uh we we learned that if you expand the aperture and you go from CKD stage three, chronic kidney disease stage three, which is mid-stage, all the way to end stage. At that point, ESRD patients represent 15 to 20% of your costs. >> Stage three members who are mid-stage will represent about half of your cost. So half of your opportunity is going upstream before you even get to those really high cost members. Um and so for us we said oh wow you know that makes sense analytically.</p> <p>So let's go upstream and it also makes sense clinically because it's your window of opportunity to be able to drive better care so that hopefully you never progress towards the late stage or even the end stage. The best way to reduce your dialysis cost is to never need dialysis. Right? and and as a as a human being, you much rather never need it than than to have to have it. So So that's one example.</p> <p>Another one, intuitively, people will think, you know, we should be working with nefologists to manage these members. And that's true. That's absolutely true. And Healthmap works with nefologists very closely. But what we did realize is when you look at the data, 60 to 70% of CKD members have not seen a nefologist in the past 12 months. And that's true. Not exactly those same percentages, but a big portion of members who are stage four, stage five even have not seen a nefologist.</p> <p>So we realized if you're going to be effective in being preventive upstream, you have to go broader. You have to work with nefologist, but you also have to include PCPs, primary care physicians. You have to include cardiologists and endocrinologists and other physicians. So we we realized and and again I'll credit analytics there to actually be able to reach all of the members you want to reach you have to include nefologists and include some of the other specialties.</p> <p>And then the last one I'll give you because it has a lot to do with AI and machine learning. We looked at the population everyone would say look if you have chronic kidney disease you have multiple other coorbidities. You're going to be an expensive patient. Um that's true some of the time. What we found is 30% of the population tends to represent 80% of future costs.</p> <p>>> So when we saw that and we saw that it was consistent, we realized we have to develop a predictive model here where we can identify that 30%. make sure that we're managing them as best we possibly can in collaboration with their physicians and with them of course to be able to stem and and bring down future cost.</p> <p>Um so that was kind of like the start of it right now doing all that analysis was strategic analysis to say is this the right space to go into when we saw all these opportunities all these gaps we said yeah it is and then that informed our strategy how do we have to build this program to be able to make sure that we're successful in managing a population >> in engineering school they will talk about how bad humans are at predicting events specifically like kidney disease specifically actually like crash dialysis or a lot of the you know um hospital acute issues that come up humans are really bad at that and so many companies forego dealing with clinicians right they say I don't want to deal deal with clinicians because I can figure this out from the data but that and some companies have found success with that right they produce you know pure data models and and that's all they do but you have taken a very different approach you didn't just produce kind of an AI model or a computing model or um you know a predictive analytic suite you didn't do any really of that uh standalone, right?</p> <p>That this was very different and you from the very beginning were working with clinicians, right? This was not a oh, we're starting to gain steam. The model is working. Let's bring on some clinicians. So, you had a very different approach entirely than some competitors, right? I >> I would say every one of us has approached this every competitors from a clinical standpoint, right? So, I I would give them all that that credit.</p> <p>Um certainly I mean when you're working with uh a population that's as sick as ours and as complex as ours can't be cannot be all analytics. You have to have a very strong clinical background and presence and knowledge base and and candidly that informs and works with all the analytics that you do. Um, you know, we everything we we try to drive with our provider partners and with our members is based on evidence-based guidelines, right?</p> <p>Um, it's just a matter of being able to take the hundreds, thousands of guidelines that are out there and distill them down to the thing that matters most for that patient and that provider at that moment in time. And that in itself has been an entire AI um exercise for us. We call it next best action and it's what is the next best action for that member at that time.</p> <p>Um, but the reality is like you could never, at least in my opinion, you could never really be effective trying to operate this program and just going direct to the members because these members do see three to four different providers, physicians in a given year and they're on 15 to 20 different medications in that given year. All prescribed by different people. if you want to affect their health care for the in a positive way, you're going to have to work with their physicians.</p> <p>Um, and you know, the physicians are just a central part of it. So, so yes, from from early on, we said, look, this has got to be a clinical program, uh, an analytically and economically sound program. And so, therefore, we do need to work with the physicians really closely and be partners with them. >> That's great. I very much agree with that approach. It's funny going back to the engineering school.</p> <p>One of the things that a lot of people do not realize, you know, as they're building these these healthcare centric projects is what happens when you go to the implementation phase and you have not involved clinician leaders. Do you feel like you've do you feel like it's a bit easier when you're discussing with health systems about potentially partnering or health plans about potentially partnering when you have clinical staff already and and even yourself, right?</p> <p>Coming from an NBA background, you must be have become much more uh used to clinical terminology and familiar with clinical terminology as time's gone on, right? >> Oh, yeah. Absolutely.</p> <p>I I um I you know early on we didn't have the the luxury of having a chief medical officer and so you know I I had to learn as much as I possibly could and um of course that falls far far short of being a doctor but but uh it at least allows me to converse um in a way where I understand some of the challenges that the the and can articulate some of the challenges the population is facing.</p> <p>Um but really yeah the second that you want to start working with health plans u you know it's a it's a clinical value proposition >> um that the that the company provides. >> So therefore we're talking to the chief medical officer or or their team or chief population health officer uh which also tends to have some clinical folks on that team uh when we're saying suggesting that they work with us and so we have to have that same clinical team and you mentioned um Dr.</p> <p>top who you spoke with. So, practicing neurologist and um we have Dr. Howard Shaps who's our chief medical officer. >> I forgot to mention Dr. Shaps. I can't believe I knew I was missing someone. >> Yeah. So, we have we have a great clinical team um that's really understands nephology, you know, kidney care and also managed care, what it's like to be on the payer side of of this trying to manage a population. So, yeah, absolutely. We we we have to have that capability.</p> <p>Um, and like I said, it's part of the program, part of the product, always has been. Um, and so we want to make sure that we have clinicians with us to help bring that to the forefront in any conversation. >> That's great. And and thank you for Yeah, I really wanted to hammer that home because my next question is about the AI part of things, right? Right. And so I wanted to make sure the audience is aware that you know clinicians are such an integral part of the process.</p> <p>But there's also this kind of I like to call it the secret sauce of kind of healthmap solutions is what I tell people is this predictive kind of analytic system that is looking 6 to 12 months in the future which is crazy because a lot of predictive analytics programs only look at when the patient enters the hospital right and and those are are you know of course complex but you must be dealing with thousands of variables and you know just reading in AI class about you know random forests and whatnot as you increase kind of the number of uh potential variables you kind of increase the correlation between them and and it's very complicated but you've seem to have found a real solution to this and then there's also this kind of acquisition of carium and a lot of things happening how are you able to get a model that's so successful in predicting something that is so far into the future you know six to 12 months I mean that's impressive >> well I I appreciate that um all of that it is it is a challenge I'll say um First, I think we recognized going upstream and identifying those members who have a lot of volatility in their healthcare utilization was important because if you if they have volatility, it means while some might utilize a lot, others utilize less.</p> <p>And so like if you bring the high utilizers down um and that's possible as evidenced by the lower utilizers, that's the goal. That's what you're trying to do. And so for us, you going upstream is incredibly important. Being able to take in all of that data um and create a predictive model. I say, you know, there's there's a couple of components here. One is just our experience. We've been doing this for over 10 years.</p> <p>We've at this point analyzed over $30 billion of healthcare expenditures related to people with kidney disease. potentially one of the richest data sets um of kidney disease in the in the country.</p> <p>Um, so that's enormous because it allows us to be able to take all of that data, pull it together, and um, analyze it to a point where you can identify and classify members into different sub segments, cohorts, and off of that be able to identify certain patterns that happen and related attributes that would indicate that that pattern is likely to happen. and that pattern being high cost admission, ED visit etc.</p> <p>So just the fastest of the data that we have is um part of it I would say um you know once you come up with a a predictive model like that it can come across as like a blackbox type of structure. So our a IML team has done a great job of creating what we call a driver report. Uh so it's sort of an indication of what might have made a person very high risk, right? So we run all the data through our our predictive model.</p> <p>Um that predictive model then indicates if somebody is high risk, medium risk, low risk, which really like kind of oversimplifies it because everyone gets an individual score.</p> <p>Um and then at the end of that we also have a driver report that would say hey for instance this person has a neurological and muscularkeeletal issue and you know they've been on anti-convulsants and like this is why they're really risky and oh by the way they had recent healthcare utilization um you know they they had a certain they're starting to run out of certain supply of medications and so this is something to look out for and this is why this person could be high risk >> when you couple that predictive model with the driver report, then you want to be able to put that into the hands of a clinician um on our what we call our front line, right?</p> <p>Affectionatally, meaning they're on the front lines of working directly with physicians and directly with the patients. Uh so they have this information and they're able to converse uh at a very meaningful way to say, "Hey, we noticed you're running low on these drugs. we noticed you've had these neurological muscularkeeletal issues. We also know you have chronic kidney disease. Let us help you navigate the next 30 days, 60 days, etc.</p> <p>And by doing that, they're dramatically reducing the risk of that person having an admission going forward. So, we're changing that outcome by virtue of giving them that right risk level and the right information. And I do want to credit I I mentioned our a IML team separately.</p> <p>We have an entire technology team who is tirelessly labored over our tech platform to be able to take in all of those insights and make it seamless for those frontline you know clinicians and non-clinians working with providers and members um so that it's all within their workflow. It's very clear what needs to get done next for which patient um and then they can move on into the next patient. It just allows them to operate at the top of their license.</p> <p>And I think the connectivity between the a IML stuff and the technology platform is where the magic really happens for Healthmap to be able to at scale and and being nimble enough to be able to effectuate the right change and make the right impacts that we're seeking to make. >> How were they able to do that be? And I ask this because the the better a model is usually generally the more of a black box it is, right?</p> <p>like the harder it is to identify, you know, the millions of weights that kind of contributed to that. And so when you were looking at a at a patient, how were you able to kind of have the data go into the machine and have it give them a risk score? And is that is that a one to 100? Is that how that works or is that a proprietary score that scoring model that you guys have in terms of that? >> It's a proprietary score. >> Um and then the driver report is like a model on its own.</p> <p>Oh, so that's how it's you have a you have a separate model for that. >> Yeah. So it's like a model in its own that needs to then pull out the right information. So so I would say they obviously relate, right? And so you have the the the risk score that gets generated and then a related model will say well here are the drivers of it. I'd also say you know you you mentioned Carium Cole which has been um just a phenomenal acquisition for Healthmap.</p> <p>Um, you know, I think one of a few of the things that really stand out for us, um, with the capabilities we acquire here, when you think about the role of our organization, um, all of those analytics are great, but they don't really make any difference unless you can change some human behavior. At the end of the day, we need a patient to change their behavior, potentially a provider to change their behavior.</p> <p>Uh it's one thing for us to use the power of science and analytics to identify an opportunity for a patient, but ultimately we need that patient to for for it to come to life for them and for them to drive it. And that's what Kerium does for us. It operates, our CIO always likes to say, and I like this, it operates at the healthcare delivery edge. uh it's really focused on enhancing our abilities to deliver our programs um to patients and providers, right?</p> <p>And to be able to do that in a very intuitive way. And ultimately it connects not only patient provider but also health map clinician to be able to ensure like hey any leading indicator signals that we get uh could be from a wearable it could be from something else gets factored into all those analytics and then presented to all those stakeholders at the right time for the right action. So the health map model is it's going back and forth between carium essentially.</p> <p>>> It's feeding that data in and it's pulling data back. >> Karium's like the a phenomenal conduit that then >> also helps us to visualize all of this complex information in an easy to act upon way. >> Wow. Quick question. This is a bit of a side question. You mentioned wearables. um how recent was that that you integrated that you know into the model? Have you seen any interesting results?</p> <p>And I ask this because a lot of people talk about it as a feature and then when it comes to integrating it, it doesn't usually you know go very well. So I'm intrigued to to to hear about that. >> Yeah. So um Curiums have that capability. It's one of the things that they've been doing for years now. So, as we've brought them on and and help Map has the capability, precarium, but I, you know, probably just multiffold uh boosted our our abilities by bringing them on.</p> <p>Um and so that's been um really kind of a bit of a gamecher and and adoption is we're just getting it started, just getting it going. So, we're early, a little too early to talk about any results to it. Um, but we're really excited about the promise of it. And I know that, you know, Karium's had plenty of past success leveraging one patient monitoring, uh, you know, we mentioned wearables, but I also think of RPM in the same bucket.</p> <p>Things like, you know, data from weight scales or cuffs or, you know, etc., like glucometers. Um, so, so for us, like it's really more that type of biometric data that's really interesting.</p> <p>um in addition to what you get from wearables and I know that there's some out there that says look you know maybe the heart rate off of an app you know a watch a smart watch might not be as accurate and that that may be the case um it's hard for me to opine on that necessarily we haven't I myself haven't done a ton of research on that but I do know that there's a lot of value in the remote patient monitoring data set >> that's exciting so a future podcast episode then we're going to have to we're going to have to get you on and that that's kind of actually the last question is about the future state I talked to Tom about this and He said, "Oh, you know, we're we're really focused on the the kidney, you know, the CKD right now." But I just see this as such an opportunity for CHF, for COPD, for so many more things.</p> <p>Uh, and not I'm not just talking about the technology. I'm talking about the team as well. I mean, you know, it's it's where you find a team like this and and a company culture as well is so geared to it. What do you see the future as being, you know, what is next? What, you know, in 2030, where are you guys going to be at? you know, and of course, you know, not asking you to share anything secretive, but anything you can give us is is definitely intriguing.</p> <p>>> Well, I I'll tell you, I'm so excited about what we're on the cusp of, right? We're leveraging this AI boom. We're leveraging some of the technology platform build that our I mentioned our team has been working so hard on and the combination of that with carry and our clinical know-how, right?</p> <p>and and by combining all those things, we're sort of right there at the point to be able to completely change the way population health gets done for the kidney population um and drive even greater improvements from where we are today. >> I do think that that can be replicated across other very chronic conditions or multi-chronic conditions. I do think it sort of is a gamecher overall and it could be industrywide as well.</p> <p>So on the horizon for us is um yes other disease states that look similar in terms of you know the the sort of clinical value prop that that kidney has. Um, when you think about what we do here, we manage much more than just the kidneys, right? A person has kidney disease, that's sort of their I always say that's their ticket of entry into the program, but once you're in, we're working on everything with that member, right?</p> <p>We're working on their cardiac issues, you know, COPD, behavioral health, social determinance of health. Um, so it's a pretty comprehensive program. um to focus on a different disease stage has a lot more to do with the profile of that population. What are the big spike clinical events? What I mean by that is like in in in kidney disease would be oh we have to go on dialysis.</p> <p>Um in cardiac it would be oh I have you know heart failure with reduced ejection fraction right half for ref we have models for that as well uh predictive models for that because it impacts our population I think for each one of these disease states you could find that big event and try to manage ahead of it to try to prevent it from happening or manage the patients um care really well through those events if they unfortunately do have to happen but even beyond that I think um the technology platform and and the process and the way we're working with our own clinicians and then others is a model that can get replicated and and you know I would love to see that um used all over the country with as many payers as possible.</p> <p>>> Wow. So stay tuned is the is the wonderful. So everyone thank you so much for tuning in. Joe Vadamatam, co-founder and president of Health Map Solutions. Thank you so much for joining me Joe. It's great to meet you for the first time. uh you know face to face here. I hope you'll join us again and I hope the audience enjoy.</p> <p>You know they have your LinkedIn healthmapsolutions.com of course is the the link for any of those who are interested in learning more and I hope that we get to work with your team again in the future. >> Thanks so much Cole. I really appreciate the opportunity. It was great to speak with</p>
Want to reach healthcare executives and decision-makers? Join industry leaders like HealthMap Solutions on our podcast.
Become a GuestDiscover related content across the AJHCS ecosystem
Articles on the same topic in AJHCS
Abstract Healthcare contact centers are undergoing a structured transition as health systems move from legacy telephony to cloud-based, AI-enabled omnichannel platforms. These platforms increasingly function as centralized digital access hubs for scheduling, triage, navigation, and patient communica...
ArticleAbstract This article presents a comprehensive analysis of hazard-focused frameworks as a strategic imperative for modern public health administration2. As a systematic and proactive alternative to traditional reactive models, this approach enhances preparedness and response to a full spectrum of ev...
