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Mia Bolton: Thanks for joining me today. I am Mia Bolton, Head of Growth at Tenasol. I am excited to have Michael Lutz, Senior Consultant, and Eric Levine, Associate Principal at Avalere, and Teddy Gedamu, Founder and CEO of Tenasol, as we begin a three-part video series covering a very hot topic in healthcare, which is clinical data and its impact to not only healthcare, but how plans operate in an industry where patient and financial outcomes are increasingly data driven. Payers are at this intersection of using clinical data to drive decisions that improve care and lower cost. In today's session, we will explore how clinical data is not only reshaping data strategy for payers, but also how it can create a win-win for patients, providers, and health plans alike. So let's get started. For all three of you, what are you seeing impacting payers in the market in regards to clinical data? And Michael, we'll start with you. Michael Lutz: Thank you, Mia, and, thanks for having me today. I'll say two things, off the top. First, we're seeing the regulatory environment evolve around the use of data in the health plan space. We're talking to a lot of clients that see the value of having deep understanding of usable clinical data and what that brings to their organizations. But they're also really concerned about the changing regulatory landscape that's being driven by reactions to both consumer concerns and regulatory agency actions. Eric's going to talk a little bit about this in a minute as well. On one hand, there's a push for plans to use data to provide more efficient and more effective access to care. And on the other hand, there's a fear of running afoul of the rules, especially rules that keep morphing, and they don't know where they're going in the future. On the other side, I'll say on the internal operational side, of the health plans, we're seeing some challenges where having a lot of access to information can add to the burden of the operating teams within the health plan and actually impede their work rather than improvement. So we've been working with clients to help them know what information and what data is needed for each operational use case, how that data is delivered to the end user as actual information for actionable information, not just a bunch of data points, and how plans can start using this as a reliable tool that's additive to their workflow processes. Teddy, I don't know if you want to add or provide other insights. Teddy Gedamu: Yeah, sure. And, I guess I'll just double down first on your observation and what you all are seeing, within Avalere, we're seeing the same thing, particularly as it relates to clinical data. Within the health plans, historically, claims data is ubiquitous. It's leveraged across every program and used to drive value for a lot of the concerns and policy and regulatory requirements that you were just alluding to, Michael. Clinical data, on the other hand, is still very siloed. It's used very transactionally, so it's used for a specific purpose. And then from there, historically, what we see is that plans don't leverage that asset for benefit in an ongoing way. And we really see that as being sort of the primary opportunity when we think about how health plans could sort of transform their business and become more data driven in this way. It's not just focusing on interoperability, which is an important tool, but not the goal. I think a lot of plans that we've worked with in the past have run afoul of mistaking interoperability as the destination, when really this data is just getting more complex and there are more and more structures that this information could be represented in. And, as a technology company, we start to think a lot about, okay, how can we help solve some of those issues? So, we're really eager to tackle this important topic with you all. Mia Bolton: And, one aspect that, Michael, you touched on is a regulatory perspective. So, Eric, what is happening from a regulatory perspective that may indicate where the market is heading? Eric Levine: Yeah, we're seeing a flurry of activities, both at the federal and the state level. I think as governments work to catch up and modernize. Recently, from the Department of Health and Human Services, we have a proposed rule around, the Health and Human Services Acquisition regulation to align health IT procurement requirements. We've recently seen HHS release its federal health IT strategic plan and roadmap to align strategies across the different agencies. We've seen a reorganization, renaming the ONC to the Assistant Secretary for Technology Policy and Office of the National Coordinator for Health Information Technology. So, definitely a mouthful, but in that reorganization, they've also established roles for a Chief AI Officer and a Chief Data Officer. And finally, from ONC, there's been a number of rules around data exchange and APIs, and the most recent example being the health data technology and an interoperability proposed rule, or the HTI-2. At the congressional level, we're also seeing a lot of discussion and inquiries around the use of technologies such as AI and healthcare. So, in the Improving Seniors’ Timely Access to Care Act, it would require Medicare Advantage plans to annually submit the use of AI in UM decision support. And not just AI, but machine learning and other decision support technologies. And also there have been questions to the Congressional Budget Office around how it incorporates AI, machine learning, and other technologies into its modeling and projections. And then finally, at the state level, we're beginning to see states take action. So, California most recently enacted a bill that limits the use of AI in utilization management. And so it prohibits software from making denials. And then there are a number of states who are beginning to establish task forces to evaluate the role of AI in sectors that include healthcare. Mia Bolton: And Teddy, from your perspective, more on the kind of technical it side, what are you seeing from regulatory perspective? Teddy Gedamu: Yeah, on one hand, we're seeing the same thing that Eric just illustrated, which is just an acceleration of more and more policies that drive the need and use to access this type of data, as a part of just the standard way that these plans need to operate programs. We see it both on the technology policy, but we also see it within programs like NCQA, for example, who's kind of promoting this digital quality approach to transform how plans historically administer HEDIS ® programs, for example. The interesting thing that we see on the technology policy side is, if you've read into TEFCA ™, which is really a framework that's designed to sort of streamline the way disparate health information networks operate. And as you think about health plan use cases, we're really seeing that the permitted purposes that would allow payers to engage in these networks in some ways are being more narrowly or granularly defined, which is interesting because it means that while on one hand we're seeing that health plans are interested in sort of enterprise level, implementing enterprise level approaches and strategies, when you translate that to operations and how you access the data, things start to become a little more narrow and nuanced. So I think it's really important that as plans think about their data strategy, they're really understanding the different access channels that are available to them and how they need to position themselves to leverage them, not just for one narrow use case, but across multiple for maximum value. Mia Bolton: Right. So we're seeing a lot in the regulatory environment. What are other market dynamics impacting clinical data, or what you're seeing on the payer side? Michael. Michael Lutz: So, as Teddy was saying, that when you start to think about the operational use cases of this data, what we're finding is that a lot of vendors offer rate platforms. Some of them are quite dynamic in what they can do and the amount of information that they provide. But if plans, or sometimes even providers, that have access to some of this information, if they don't receive training, understand the specific use cases that are unique to each role within their organizations, then these tools aren't likely to be used, or at least not used to their potential, or in an effective manner, and that sort of renders the access to the data useless. The other key consideration is that these platforms, or the data that they provide, needs to fit seamlessly into existing operating procedures in order to provide information that is additive or useful to the process. Otherwise, it's just a distraction in an already complex system, or it's paralysis by volume of data that the end user just doesn't know how to utilize in their day-to-day activities. Mia Bolton: And Eric, on your point around regulatory, what are other kind of industry dynamics outside of what the government or the, federal side is doing, around HIPAA compliance, those types of market dynamics? Eric Levine: Yeah, a few things come to mind for me. Plans get a ton of data. They get it from different sources; they're using them for different activities. And I think because of that, oftentimes data governance can be siloed. You have departments bringing in, storing, and extracting data and from various different vendors. And I think there's a lot of opportunity to streamline both from a cost effectiveness perspective, but also to enhance and enrich the data across different plan functions. On the other hand, though, there's a number of compliance considerations. I know that plans really operate under when it comes to the use of PHI and PII that might impact their approach to data management. And on top of that, I think you also have rising risks of cybersecurity threats, and those come into play as well. Michael, I don't know if you have anything to add on that. Michael Lutz: Yeah, thank you. Eric. You talked a little bit about the data coming into the plan, but also there are a lot of impacts on how to use the data and the information once it's in the plan. And how do you fold that into the daily operations and without any sort of educational support, plans are left to their own devices to figure this out. A lot of vendors have data platforms, some of which are quite dynamic. But if the plans, and potentially providers that might be accessing the information as well, don't receive training or understand the specific use cases and how it fits into their operational procedures and how each role within the organization accesses or uses the information in a unique way, then that renders the data useless or at least less effective than it could be. The other key consideration is that the platforms and the resulting information needs to fit seamlessly into the existing operating procedures and provide information as additive or useful to that process. Otherwise, it's just one more distraction in an already complex system or already complex activities that plan staff are required to execute every day. The other thing that I want to talk about too, is, and we talked about it a few times here, is actionable information, not just data. Plans are under incredibly tight, pressures on margin and profitability. And if they have to hire analysts to be turning that data into useful information, that's money that comes out of the clinical purview, the clinical providing of services to their members, and having to focus on administrative tasks. So, we really need data, but, data in actionable format, data that provides information to each of the specific use cases within the health plan. Teddy, I don't know in the work that you're doing, if you're seeing the same issues with your clients Teddy Gedamu: 100%, I mean, one of the most compelling conversations, or stories, that we tell prospective and current clients is the opportunity to leverage technology to eliminate technical debt in this era that many government plans, of government program health plans, are kind of operating within that being able to show savings and efficiency, particularly with AI based solutions, is really, really important because it's not there across the board. Your point about making data actionable too, is, I think, really, really important. I think that it's important for plans. And we talk about this a lot with clients. Developing an enterprise strategy does not necessarily mean a one size fits all for every program, right? If you're managing data well at an enterprise level, then you could potentially deploy various solutions that leverage that data that are uniquely designed for those specific requirements or that specific program, or to meet the needs of that customer. That's where we've seen success stories, frankly, the clients that have been successful is they're sort of operating in that way where they're not trying to solve everybody's problems, they're just creating a shared service that others can tap into and that's really valuable. And so the last thing I'd say is this area is only accelerating. More data is becoming available. It's more and more complex. The volume is growing, and so the ability to generate efficiencies and not have all this data sort of in the hands of individuals that costs a lot of time and money, and leveraging AI for some processing automation, I think is a great opportunity for health plan as well. Mia Bolton: Thanks, Teddy. Well, thank you for joining me in this discussion. And check out our second video in this series, unlocking the power of AI in clinical data management and operations. Thank you all for joining.