00:01.09 Ratnadeep Bhattacharjee Hello and welcome to another episode of Leaders Perspective. I’m your host Ratnadeep Bhattacharjee, co-founder of TechVariable, where we focus on solving some of healthcare’s toughest challenges through interoperability, data, and AI.

00:14.19 Ratnadeep Bhattacharjee Today, we are diving into a critical conversation, you know unifying data for smarter Medicare Advantage decisions. Medical Advantage is one of the fastest growing areas in US healthcare, but it’s an in incredibly complex one as well, you know with fragmented data, diverse risk profiles, and increasing regulatory over oversight. rate Joining me today is someone who is at the heart of these challenges, and in fact, solving these challenges one after another, Dave Wallenberg.

00:43.82 Ratnadeep Bhattacharjee Dave is the VP of Enterprise Data in and Analytics at ScanHealthPlan, a Medicare Advantage-focused health plan. In his role, he oversees analytics as well as data architecture and engineering, helping to drive the company’s transition into the AI era. ‘

00:59.11 Ratnadeep Bhattacharjee Before scan, and Dave worked as a consultant at BCG, Slalom, McKinsey, supporting healthcare clients on data and strategy initiatives. He also served as VP of strategy at Rite Aid, where he led analytics for the retail front-end, ah pharmacy, and PBMs.

01:18.39 Ratnadeep Bhattacharjee Dave, it’s a real pleasure to have you here. Welcome to the podcast.

01:22.65 Dave Oh, thank you so much for having me. It’s a real pleasure.

01:27.13 Ratnadeep Bhattacharjee Yeah. Sure. Dave, before we get into Medicare Advantage, I’d love to hear a little bit about your journey. you know You have worked across consulting, you know pharmacy, retail, and now Medicare Advantage.

01:41.51 Ratnadeep Bhattacharjee What has shaped your perspective on the role of data in healthcare?

01:47.67 Dave Great question. So as you noted, I worked at a few consulting firms early in my career, and I was your standard issue strategy consultant, if you will, solving a broad range of strategic questions, whether that be growth or operations or go to market. worked across all of healthcare. care So I saw payer, provider, pharmacy, pharma, and med tech,

02:13.14 Dave So I really got a broad overview of what’s happening in healthcare. care And the more exposure i got, and the more I realized the real strategy is happening on the analytics side. you know, if you don’t understand the data, you don’t understand the numbers really in depth, and you’re not able to view what’s happening within your company, what’s happening in the marketplace, you know, what you think is going to be happening in the future.

02:38.44 Dave know, you’re really not going to have a grounded view into where this dynamic industry is going. And so over time, i evolved my role to become more and more technically oriented first on the analytics side and then gradually onto the underlying David Price- Data as well, because that line between data and analytics is increasingly blurry as we enter the world of AI, I think it once upon a time you could have said David Price- was more business facing and the other is maybe more back office more IT like that I think that’s really breaking down because you know in the world of.

03:14.51 Dave AI in particular, if your data is not well organized and in good shape and well governed, then you’re not going to be able to do types of analytics that you need to do. And so the modern platforms out there, whether it be Snowflake or Databricks or more niche platforms, they bring data and the analytics so tightly together that you almost can’t even draw a distinction between those two things anymore.

03:39.67 Dave So it’s really exciting to to be on the forefront of what’s happening. ae yeah in AI and data and analytics in healthcare, care because you as everyone knows, it’s ah it’s it’s a very dysfunctional industry. I don’t think I’m saying anything controversial by by saying that.

03:55.75 Dave There’s challenges from a clinical perspective, from an experience perspective, and of course, from a cost perspective as well. And so I think i think data and analytics is going to be at the heart of solving those issues you know one step at a time.

04:10.87 Ratnadeep Bhattacharjee Oh, completely agreed. You know, it’s not perfect, but, and know you know, with every imperfection comes opportunities, right? So I think we are at ah we are at a very critical juncture of the industry and AI has come at the right time to solve a lot of problems potentially, but then again, only if used correctly.

04:29.92 Ratnadeep Bhattacharjee I agree with you, ah Dave. And with people like you, I think you are paving the way for, you know, a better ah healthcare. per se, right? with With right use of AI, right use of analytics for different use cases.

04:43.24 Dave hope.

04:44.92 Ratnadeep Bhattacharjee Yes, yes, we you definitely are, Dave, you know. ah Dave, and Moving on to Medicare Advantage very specifically, Medicare Advantage is projected to cover more than half of all Medicare beneficiaries in the coming year, if I’m not wrong. right With this growth, you know also comes great complexities. right From your experience, ah why is data unification such a critical issue in Medicare Advantage today?

05:15.64 Dave Yeah, great question. And so like you said, the Medicare Advantage program has grown to the point where over half of beneficiaries now use Medicare Advantage, which for any of your listeners who aren’t familiar with the program, and it’s traditional Medicare is administered by the federal government.

05:34.26 Dave Medicare Advantage is a similar program, but it’s administered by private organizations. And it’s a you know you you as a consumer as a medicare beneficiary can choose who your medicare advantage uh administrator is so i work at a company called scan which is a non-profit uh medicare advantage organization based in the southwest of the us uh we have about 300 000 members you know some of the larger more well-known competitors are united aetna for example um the various blue cross plans out there so we compete against companies like that so know why is data

06:12.67 Dave So crucial. ah we We want to take a holistic view of our members and treat them as, of course, you know full human beings, whether that’s their clinical experience you know as as a patient or just as ah as a as a human, but of course, also um the experience that they have you know beyond the clinical experience.

06:31.05 Dave aspects of their lives, speaking to sure that they’re well treated by by us you know The insurance company sometimes has a bad rap for how they they treat their their members. We try to do things a little bit differently. So we want to have a holistic view of the member.

06:44.25 Dave Data comes from so many different sources. So you know from the more clinical side of things, claims is probably what most people have heard of. Claims are when the doctor or the provider of the hospital submits say ah you know effectively a bill for reimbursement.

06:57.53 Dave Dr. Jason Lepojarvi, M.D.: That claim has a structured aspect to it, it can also have an unstructured aspect to it, meaning clinical notes, you know other things that the doctor has said about the patient that provides context for why a service was provided.

07:10.43 Dave Jason Lepojarvi, M.D.: also got a number of other types of data sources from clinical our clinical partners, those can be called encounters. Brian Johnson, M.D.: Prior authorizations we do annual wellness visits all of that gives us a clinical Brian Johnson, Of the Member but they’ve also non clinical aspects as well, we have touch points with that Member, whether it be through our Member service Center the call Center through our website through through the Brian Johnson, M.D.: And then there’s what you might call background information so social determinants of health is a term, some people may know sdo h.

07:40.61 Dave And yeah that that provides sort of context on the member, and what challenges they may be having, whether it be you know food insecurity, financial insecurity, housing insecurity, all that data comes together and provides a holistic view of that member.

07:54.78 Dave And if we just treated it in silos, we really couldn’t manage that member’s well-being well because you’d have different teams within a company all with you know one slice, one view of that member. You wouldn’t have the full context for that.

08:10.42 Dave the the clinical or non-clinical aspects of that member. And so you you really are going to miss aspects of your well their well-being if you don’t unify data. But then maybe I’ll add to that and say, you know, all those data sources are reflecting, you know, the current state or they’re retroactive.

08:28.10 Dave We also want to sort of think ahead. you know We want to have a prediction of the future. Who is most at risk, whether that be, you going to the ah ER or developing a chronic condition, or even just being um you know dissatisfied with us as their as their healthcare plan.

08:44.74 Dave And so by bringing all the data together, you’re able to develop a much more sophisticated predictive model as well that allows us to take the right actions that will help that member, whether it be solving a care gap, connecting them with a provider, you know reaching out to them to address some experience that they’ve had that that wasn’t great and that we can hopefully make better for them.

09:06.99 Dave And so just to sum up, you know, again, you have to have a holistic and an accurate picture of what’s happening with each and every member. And that comes from so many different sources. And, you know, that affects the health outcomes.

09:17.82 Dave It affects the experience. And that of course, it affects ultimately, therefore, our financial performance as a company.

09:24.36 Ratnadeep Bhattacharjee boom Interesting. One of the important aspects you touched upon, Dave, is risk, right? You know, predicting risks.

09:31.16 Dave Yeah.

09:32.62 Ratnadeep Bhattacharjee You know, risk stratification is often understood to be the centerpiece of Medicare Advantage decision-making, right? Everything from reimbursement to care management depends on it, if I’m not wrong.

09:46.08 Ratnadeep Bhattacharjee could you Could you walk us through how unified data enables risk? you know, better risk stratification and what happens when organization, ah you know, let’s say lack that unified view.

10:00.48 Dave Yeah, absolutely. So as I was alluding to earlier, we we get clinical information about the members from a variety of different sources. You know, if if it’s a claim, that means the person has already gotten care in some way. That’s sort of ah a retroactive view. If it’s a prior authorization, that means a doctor saying, hey, we we plan to do some kind of procedure or or test or something on a member, yeah that that’s sort of a forward looking view.

10:29.84 Dave And then, as I mentioned, there are some sort of broader contextual things like the social determinants of health, where it isn’t immediately today um tied to some type of medical procedure or you know encounter with a physician, but it you know it may in the future if someone has food insecurity or housing insecurity or just general um you know insecurity financially, that’s that person is more likely, unfortunately, to wind up with negative health outcomes.

10:59.72 Dave So we really need to bring those things together and an understanding of, you know, what does that mean going forward for this member? And therefore, what are the right types of actions that we should take?

11:13.01 Dave you know, for some people, they might not be having a lot of claims today. you know it it might you know very superficially seem like they’re healthy, but we kind of know from everything what we have about that member that they have a lot of insecurities in their life, you know maybe they’re not in peak physical health, and they could wind up in the yeah ER.

11:30.33 Dave And that that obviously is very traumatic for the member. And of course, financially also, it’s it’s a very expensive outcome that we want to avert if it’s at all possible. There’s other types of members out there who maybe we know have a chronic condition. Maybe they have cancer, for example.

11:46.38 Dave And so that that’s already you know happening in their lives. But with the right type of engagement, the right type of treatment, we can hopefully help them you know on the path back to help health, keep them you know out of the ER.

12:00.97 Dave And You know, it’s it’s a different type of ah current state data that we have, but and therefore a different type of intervention that we need to make for that member. You know, it’s more about making sure that they see the doctor they already have, taking the medication that they’ve already been prescribed.

12:15.79 Dave And so, you know, I don’t think you can just say there’s one type of risk. You know, there is ah variety, a wide variety of different journeys that our members are on.

12:26.42 Dave and therefore, you know a variety of interventions or just sort of monitoring that we need to do to keep our members healthy and engaged with us, you know I should add that.

12:39.29 Dave the way that Medicare Advantage works is CMS, the government administrator, so looks at our membership and based on the the health conditions of the members and may compensate us more or less. If a person is is kind of chronically ill, then there’s you know a higher level of reimbursement to take into account the fact that they are you know, going to the doctor more often. And so just as a business, we need to make sure that we know what’s what’s happening with our ah members. And this is true of every Medicare Advantage plan.

13:11.91 Dave and And really, I would say maybe every insurance company altogether, you know, if you don’t have a full holistic view of what’s going on in your members lives, you’re probably not going to be able to manage them effectively.

13:24.62 Ratnadeep Bhattacharjee Hmm, interesting. Also, Dave, beyond, risk I know you touched upon a few use cases, but beyond risk adjustment, what are some high value case of unified data in Medicare Advantage, right?

13:31.45 Dave Thank you.

13:38.66 Ratnadeep Bhattacharjee For example, you you you touched upon you know ah reducing care gaps, right? So care gap closure, member engagement, even quality reporting, right?

13:50.41 Ratnadeep Bhattacharjee According to you, What stands out to you as an area where unifying data really creates impact besides risk?

14:01.92 Dave Sure, sure. Well, let me point to you know another a major thing we’re concerned about with our members, which is the experience that they’re having you know in their healthcare journey, which you know even for a healthy person who maybe isn’t going to the doctor frequently, you know we want them to have great experience, which isn’t something you often hear in the world of healthcare, care of course. And so when we think about member experience, and that can happen in a lot of different ways. you know It’s the experience they had when they went to their primary care provider.

14:33.81 Dave It’s the experience they had when they went to their pharmacy. It’s the experience that they had when they signed up for SCAN and you know became enrolled as a member of our health plan, or when they called up our call center or went to our website or um you know you used our app, for example.

14:51.83 Dave If all all that data is coming in in different channels and it’s reflecting different parts of that experience. And so ah where where that data lands is not at its start unified, you know the the pharmacy data and the you know that the website visitation, that that doesn’t start off in the same place. We have to bring that together and build that longitudinal perspective, that longitudinal view of the member journey, whether that’s direct engagement with us as their health plan or the various healthcare care providers out there, the pharmacy, the hospital, the primary care provider, the lab, etc.

15:27.09 Dave And so we we often have members who have a bad experience with their provider, maybe they can’t get an appointment, for example. And, you know, they, to some degree, you know, blame us. And they they they say, Oh, why you know, why can’t I get ah an appointment with the provider? Whether or not that truly is our fault doesn’t really matter. We we have to take action on their behalf because we you know we care about them. we want and them to make sure that they are able to see ah provider you know in in a timely fashion.

15:58.99 Dave And so by bringing all the data together, by having that longitudinal view, we can hopefully at least you know give them a better experience than what they have come to expect often in the world of ah healthcare. care And that’s going to lead them to you know want to stay with a plan and i also hopefully be more engaged in their own health care and just have a you know better journey you know in general.

16:28.62 Ratnadeep Bhattacharjee Right. ah So as you speak, ah Dave, I could see that, you know, you were touching upon most of the use cases wherein for a health plan like scan, right? 16:41.78 Ratnadeep Bhattacharjee it it a It really impacts the PMPM at the end of the day, right? And that is what the main goal is. at every health plan if I’m not wrong, especially on the Medicare Advantage side of things where, you know, with all these audits and, you know, CMS really making sure that, you know, everything is correct and everything is centered towards patient, you know, is these three these use cases are becoming more and more important as as as we speak nowadays, right?

17:13.53 Ratnadeep Bhattacharjee And to this exact same point, Dave, you are also helping lead scan health plan into the AI era. you know, when you think about, you know, AI in Medicare Advantage, how important it is to, you know, to first get the data house in order, if you know what I mean, right?

17:35.31 Ratnadeep Bhattacharjee So, you know, here I’m, I want to understand from your perspective, you know, since you are taking them into the AI era, What does it mean in terms of ai you know data readiness, even before becoming AI ready?

17:48.31 Ratnadeep Bhattacharjee What does it mean in terms of governance, you know creating a trusted longitudinal data? You’ve already touched upon those points, but I really want to get deep into the ah readiness aspect within ScanHealth specifically.

18:02.74 Dave Yeah, that’s a great question. And it’s a big undertaking for sure. So you know if you think about our overall data architecture, there’s a lot of systems that get involved. First, you have what you might call your operational systems.

18:18.16 Dave These are typically built for purpose platforms. These are the platforms that handle our claims, our enrollment, our call center, you know you name it these these Jason Schiffernitz, These typically vended products that, in some cases, are very legacy and, in some cases, they don’t.

18:37.13 Dave always have no great API connection so though gradually we’re we’re modernizing the platforms that we use then once all that data lands Andrew Tucci, into into scan into our ecosystem and these various transactional platforms, then you got to bring it all together into that unified view that we discussed earlier. Andrew Tucci, So that you can do analytics or use cases on top of the data and that’s where.

19:05.12 Dave one of the major projects that we’re doing right now is bringing that data from a typical on-premise legacy architecture you know into the cloud. And so we’re using Snowflake as our future state data warehouse. We also do some work on Databricks as well as for machine learning purposes and other AI use cases.

19:27.28 Dave And so by bringing the data into a modern data platform, it’s vastly more scalable, it’s vastly faster, and it enables us to do types of use cases that we couldn’t do in the past.

19:43.15 Dave And I should probably add one more aspect, which was, Traditionally, our data was structured data. So if your listeners aren’t familiar with that, you can think of it like a table. You’ve rows and columns.

19:53.71 Dave you know You pretty much have like well-defined structure to your data. A lot of the data in healthcare care is unstructured. It could be doctor’s notes. It could be the transcript of a phone call, for example. It could be an email. 20:04.91 Dave We still get a lot of faxes that come in, although you know we’re trying to move away from that. We’ve got paper letters as well. yeah How do you put all that into ah table? Well, in some ways, you can’t. But with a modern data platform, you can have a data lake type architecture, meaning you can bring all this structured, semi-structured, unstructured data together, and then you can build ah AI use cases or to analytics cases that that sit on top of that.

20:31.13 Dave Now, part of that is a technology move um to to get a modern data platform, but it’s more than just technology. There’s also ah data governance aspect to it as well.

20:42.90 Dave You have to make sure that all this data is clearly labeled and tagged and and organized in a way that your technology can find the data that it’s looking for and understand what it is that yeah it’s looking at.

20:56.74 Dave And then there’s also just a more broad cultural change that really has to happen. ah you know I think in the past, data could be seen as the job of ah of a technical team like ours.

21:12.16 Dave And people maybe, you know in a broad sense, abstract sense, they understood that they needed to provide some input now and again, but they didn’t really see it as core to their job to to really be a steward of their data.

21:24.64 Dave But as AI becomes more and more critical for, and think, ultimately everything that we want to do, No, it’s not really feasible that the data analytics team can ever be the true subject matter experts in every piece of data that comes into the company. and We need our business stakeholders to truly be the stewards and the owners of that data. And when I say owner, or I don’t mean it in the technical sense of you know owning the data warehouse, but they they should no you know what data comes in. you know What does it mean?

21:55.15 Dave What data other do we need to send out? And what data does that mean? yeah know yeah We need to have a culture where Everyone sees themselves as data-driven in what they do. 22:07.03 Dave out you know the The core analytics team, data analytics team, may come to support them and provide those technical expertise in terms of how you use that data, how you build a model, how you build a chatbot, whatever it is.

22:19.74 Dave But the true subject matter expertise really has to sit with the business. And so, you know, to wrap up my long answer here, that I would say that you got this to the technical perspective of having the right data platforms, the process, which is data governance, and then that broad sort of cultural people change aspect where the whole organization understands that if they’re not you know ready, willing, and able to provide that data stewardship, it’s not going to be possible to build the AI use cases, which they’re going to both want and need to be successful in their roles.

22:55.95 Ratnadeep Bhattacharjee Hmm, interesting. that’s ah That’s a great, you know, I think this is a masterclass for anyone listening in terms of how to really and not do stuff, not think about stuff rather, and then, you know, how to be ready with your data before, you know, getting into the bandwagon of all the AI use cases that people talk about nowadays.

23:19.79 Ratnadeep Bhattacharjee ah You know, Dave, ah one of the other things that I keep uh listening to whenever i you know talk to these health plans or you know people working there in the analytic space or data space or even non-technical people right they they talk about how stringent it has become from cms side of things right this radb audits and all those things happening very regularly So as as as someone who is at the helm of all the technical efforts within within a company like ScanHealth or for that matter, anyone at your position handling those sort of things, like how how does a data leader like you

24:01.69 Ratnadeep Bhattacharjee handle, ah i won’t say crisis like it, but audits, you know, all those regular unsolicited audits and, you know, ah something that may just come up without even a warning, right?

24:15.78 Ratnadeep Bhattacharjee How do you handle those things? How do you get yourself ready?

24:19.54 Dave yeah Yeah, this is a very smart question and it’s absolutely one of the biggest challenges that we have. Certainly, i and my business stakeholders want to be focused on you creating new value for our members and for us of the company.

24:37.82 Dave And then our regular regulators swoop in and they give us an audit. And, you know, we obviously we have to prioritize it. That’s that’s sort of non-negotiable, ah but it’s really not the thing we would most want to be doing.

24:53.05 Dave So, you know, how do we how do we handle this? We have a few people who are, largely focused on doing this type of work. So they’re very familiar with the types of questions that we get from our regulators and our um our third party stakeholders out there, our auditors, because often they’re asking for similar types of information. So it’s not always reinventing the wheel.

25:20.67 Dave And then we also have great partners in our compliance and audit departments at the company who do a number of mock audits throughout the year so that we can practice, if you will, for the types of questions that may come our way.

25:37.41 Dave And those those partners of ours can you know do do something that’s very similar to a real audit. We can get the data ready. And then when CMS or a state regulator comes in,

25:49.89 Dave we’re we’re already pretty well prepared based on these sort of mock audits and the fact that we have a few people who have the muscle memory of knowing where the data sits. And that’s how we’re able to turn these things around relatively quickly.

26:04.95 Dave You know, sometimes We do get out of the blue questions and we just, you know, ultimately it is a fire drill. You do your best to prepare. um But, you know, sometimes these things do, you know, do happen.

26:18.15 Dave I think it is really essential to at least have some people on the team. If you work at a company like ours who are tasked with these kinds of things so that they have done this before and and know how to be responsive. if If you just kind of assigned it to a random person on the team, I think they might flounder a little bit and they might not be able to do that do the data polls in the turnaround times that sometimes we’re subjected to.

26:49.18 Ratnadeep Bhattacharjee Okay. So, uh, Dave, if you, if you look, uh, know, three to five years down the road, right. How do you see data and AI transforming the Medicare advantage space?

27:02.31 Ratnadeep Bhattacharjee Uh, will we reach a point according to where, you know, ah data unification is not just, uh, you know, different, I mean, it, it, it should be a standard rather than a differentiator, right? Do you, do you see a future where that happens?

27:18.84 Dave Yeah, it absolutely will. I mean, things are changing so fast that, you know, it’s hard to predict three years into the future, let alone five years into the future. But we’re We’re already deploying some AI use cases, and we’ve got a number that we’re sort of gearing up to get started on.

27:36.56 Dave And they are going to provide us so much insight and so much leverage that really will accelerate our capabilities, our efficiency, our effectiveness.

27:50.68 Dave going for companies that aren’t already on this journey i think it’s important to catch up as quickly as you can because i think it’s really going to differentiate some players versus others. And Medicare Advantage is a fairly well-regulated space.

28:09.05 Dave So there isn’t always a lot of room for creativity in terms of what you can offer to your members, the types of benefits you can provide. For example, you know CMS provides a lot of guardrails. So it can appear in some ways almost like a commodity you know and so you maybe in the past you differentiated with some supplemental benefits or with a better experience or maybe you differentiated on price but you haven’t been that different from one another however i think in the future if you are able to use ai to really um predict your members clinical journeys in a way that you can intervene much earlier that’s that’s going to very different outcome if you can understand

28:52.33 Dave the types of networks you need to build so that you can build a high performing network of quality providers at ah at a good rates, that’s going to make you much more financially successful.

29:04.20 Dave If you can understand what types of benefits your members really value in terms of saving money or in terms of ah clinical outcomes, yeah that’s really going to create a differentiated product.

29:17.69 Dave So and and then finally, I should just add this in terms of operational efficiency, you know, that administrative costs are a big problem in in the world of health care. And there’s often a lot of manual steps, things that, you know, with traditional methods have been difficult to automate.

29:32.82 Dave And with AI, it’s going to be a little bit more complicated. little bit more feasible to to automate those steps. And so if you can bring down your administrative costs and you know funnel that savings into the member experience, into the into clinical outcomes, or even into lower premiums, you’re really to start be able to differentiate yourself in a market that was previously commoditized. and like i said earlier all that start all that starts with the data you you really don’t have an ai strategy if you don’t have a data strategy and if your data is not well governed if it’s sitting in many different systems that don’t talk to one another it’s going to be extremely hard to build effective ai use cases and so there is a

30:18.46 Dave layer or is a first step that’s maybe less exciting to the business of bringing all that data together into a unified platform. And maybe you don’t immediately see, you know, what’s the ROI of doing it, but all those downstream things that you want to be doing require that sort of technology enablement, that process enablement.

30:40.69 Dave And so, you know, it’s really critical to be i think already on that journey. 30:47.00 Ratnadeep Bhattacharjee Interesting. Yeah. ah Dave, this has honestly been a fantastic conversation. I already, you know, called it a masterclass.

30:58.44 Ratnadeep Bhattacharjee So before before we wrap up, what’s one piece of advice ah you would like to give to healthcare leaders ah who who are currently struggling with, you know, fragmented data?

31:12.10 Ratnadeep Bhattacharjee but but want to move you know towards smarter AI driven Medicare advantage decision making.

31:19.46 Dave Yeah, great great question. you know I earlier laid out to like this technology process, people slash culture framework, which you know I think all three of those steps are really important. And I would say that for anyone not already on that journey, ah you know it’s time to start. you know that that From a technology perspective, you really need to have cloud data platform. I think by now most people ah realize that.

31:47.68 Dave But maybe less obvious is the data governance, which i think is a combination of having a dedicated data governance team that really understands the data, that really is it going to be equipped to create that semantic context that AI needs to understand what your data truly means.

32:06.36 Dave If your data is not well organized and you don’t have that semantic layer, the AI is not going to make sense of something that a human couldn’t make sense of. And so the data governance team has to be there, but you’re never going to have a data governance team large enough to truly be subject matter experts in every piece of data in the company.

32:23.17 Dave And so you really have to bring your entire enterprise along. but That’s not an easy thing to do unless it comes from the top. You know, if if it’s just trying to be driven by the data and analytics team, people see it as a burden. They’re going to see it as, well, why do I have to do that? You know, why can’t you all do that?

32:40.61 Dave So he you really he really need executive level sponsorship to be saying to the business, We won’t be able to compete in the future if we’re not equipped with AI. are We’re not going to be equipped with AI if we don’t have a robust data platform, platform in the broadest sense of the term.

32:57.96 Dave And that is ah you know the responsibility not just of one little team, but of an entire enterprise. No, in the same way that I’d like to say that, you know, compliance doesn’t just belong to the compliance team. Compliance is the whole company’s responsibility.

33:13.33 Dave You know, the same thing is true with being data driven. You know, it’s it’s a whole company’s responsibility. And that’s that’s a big cultural shift for for many people. But it’s one that I think all enterprises need to embark on.

33:28.49 Ratnadeep Bhattacharjee Yeah. Thank you so much, Dave, for sharing your insights today. ah It’s clear that you know unifying data isn’t just a technical project. 33:34.19 Dave Absolutely. 33:38.23 Ratnadeep Bhattacharjee It’s a strategic you know imperative and even you know kind of management level ah ah know initiative, right for especially for Medicare Advantage organizations that want to deliver smarter care and make better decisions at the end of the day. 33:38.83 Dave Absolutely. 33:56.10 Dave absolutely 33:56.20 Ratnadeep Bhattacharjee and And you know thank you to our listeners for joining us. Don’t forget to subscribe to Leaders Perspective for more conversation with healthcare leaders like Dave, who are shaping the future of care delivery and technology. 34:09.52 Ratnadeep Bhattacharjee Thank you so much and keep listening to Leaders Perspective. 34:13.47 Dave Thanks for having me.