Alright. Welcome, everyone. My name is Bert Burnett. I am director of market engagement and growth at NCQA. I'm excited to have you all with us, and I'm excited for our guest today. We've got a a handful of guests that are gonna be talking about Medicare Advantage versus traditional Medicare quality outcomes, and I'm excited to introduce first Christy Tiglin. Thank you, Burke. Hello, everyone, and thank you all for joining. We are really excited to be talking about some work we have been doing jointly with NCQA and AHIP, as well as our partners at the Blue Cross Blue Shield Association. We've been doing work for several years in the Medicare space. I am the Vice President of Research Science at Inovalon. I've been working in quality measurement for more than fifteen years, way longer than I want to share with you all today. And we're gonna be looking at some pretty exciting research today, I think so. Let's let's let's do it, Burke. That sounds great. Alright. Next up, I'm gonna introduce, Siegel. Hi there. My name is Sari Siegel. I'm the senior vice president of research at AHIP where I lead research and analytic efforts across Medicare Advantage, Medicaid, commercial coverage, employer coverage, as well as broader health policy issues. I'm very excited to be here today to talk with you all about some really important research connecting quality outcomes and value within MA versus fee for service. Thank you. I'll hand over to Fred. Hi. I am Fred Blavin. I am the associate vice president of research and policy development at the Blue Cross Blue Shield Association. Thank you all for joining us here today, and thank you for Burke, and everyone else at NCQA and for Chrissy and Sarah for help organize this webinar. I joined the association just a few months back. Previously, I was a senior fellow and health economist at the Urban Institute in Washington DC where I've, had, you know, worked for nearly fifteen years as a health economist and policy analyst working on related issues to coverage, access, and affordability. I'm excited to speak a little bit more today about MA versus fee for services differences. Excellent. Alright. Well, thank you all and we will go ahead and get started. So, Christy, I'm gonna start with you and just kinda kick off the q and a session. Can you just summarize for us how this research is different from previous research comparing MA and fee for service? Absolutely. There were a few innovations in the work that we did together and I think the first and most important was that we were able to use real world data. And not only just Medicare data, but we used three years of pre enrollment data from either the commercial insurance plan or the Medicaid plan that the Medicare enrollee before they turned age 65, what their insurance coverage was. So this is really important because this meant that what we were doing was then using characteristics from before they enrolled to make sure that they weren't influenced by some of the things you hear like there are differences in coding of chronic conditions between Medicare Advantage and fee for service. We took their chronic conditions, their baseline characteristics from before they enrolled in Medicare. So that was one of the big innovations. We then looked at whether they went to Medicare Advantage or went to Medicare fee for service and we looked at two years of post enrollment data. So how did they do after they enrolled in either Medicare Advantage or Medicare Fee for Service. A second important thing that we did that is often not considered in quality measures was that we linked in social drivers of health data. We linked it to each member at a very near neighborhood level using the nine digit zip code, which really is a very small neighborhood of about 10 to 20 households. So this is highly predictive, much more predictive of the health behaviors, the likely outcomes of the people who are living in that very small neighborhood versus bigger geographic areas that may contain disparate populations. So we use that to really compare people on you know their income, their education, their ability to speak English or understand English. Did they have access to a car, transportation? Did they live alone? Those kinds of really important factors that impact outcomes. And then finally, and I think also really important to this analysis is that we use exact matching on some characteristics like age and sex, but then we use propensity matching for matching on chronic conditions, on social risk factors so that we're really doing an apples to apples comparison. So we're taking a person who enrolled in Medicare Advantage, we're taking a person who enrolled in fee for service, and we're making sure their characteristics are the same. What that means then is that when we're looking at outcomes, they're driven purely by the program they enrolled in and not by who enrolls, who decides to enroll in each of those programs. So we get rid of that confounding really by doing this matching. So we're comparing apples to apples populations. So those were the real innovations, Burke, I think in this research. That's awesome, Christy. Thank you. So so Fred and Sarah, I'm gonna ask you both. You know, Christy talked a little bit about the advancements in the approach, but, you know, I'm gonna ask both of you how you know, share more about why those advancements in the approach to comparing those quality measure outcomes were so important and how they resulted in such dramatically different findings than reported by prior research. Yeah. Thank you so much for the question. So let's go ahead and advance to the next slide. And this is a very important element in thinking about the entire picture that we're looking at here. One of the reasons we're very excited about this research is that comparisons between Medicare Advantage and traditional Medicare are increasingly shaping Medicare policy. And those comparisons really heavily depend on the data and the methods that are used. What you see in this slide, some of our high level findings, is that we are examining in this research diagnoses recorded during the three years before people entered into Medicare, while they still were covered by commercial or Medicaid coverage. And it found that people who enrolled in Medicare Advantage had more recorded chronic illness than those entering traditional Medicare. And you can see on this slide, on the table on the right, even in the first row when you're comparing having at least one chronic condition, that more than forty four percent of those entering MA had at least one of the most common chronic conditions that the researchers here examined, compared to thirty seven percent of those entering traditional Medicare. But the key difference here is in the lower rows that we found differences related to multiple chronic conditions. While only about nine percent of those entering traditional Medicare had three or more conditions, fourteen percent of those going into MA did. That really matters when we are comparing quality outcomes. It stands to reason that those who are more ill coming into a program may have a greater likelihood of hospitalization and readmission. If we don't account for that, it becomes really hard to tell the differences in the populations versus the differences in how well their care is managed. So using health histories recorded before Medicare enrollment really gives us an important baseline. And we use that in this research, along with other characteristics to create these propensity matched groups that were really able to hone in on the characteristics and make sure that this was really a truly matched cohort before examining outcomes. Yeah, thank you, Sarah. I think Fred, I think the next slide was going to also cover a few more of those just how the advancements in the approach really you know, resulted in some of those dramatic findings. So I will kick this next question to you. Great. Thank you. Yeah. I think this, Inovalon study really further illustrates how the the populations in MA and fee for service are are far more different than I think some previous analyses may have, acknowledged. And that potentially, you know, moving forward, you know, things like the the risk adjustment model, could potentially, underway underway certain key factors, particularly related to social vulnerability of of these populations, which are not accounted for within that model. So as, Siri's previous slide indicated, you know, fee for MA enrollees, have more chronic conditions and are in worth house worse health status than MA enrollees prior to, enrolling in Medicare. What this illustrates, on this slide is that they are far substantially more socially vulnerable as well. So forty two percent of MA enrollees within this sample came from Medicaid before the age of 65 compared to twenty one percent who enrolled within fee for service as shown by the the estimate in the bottom, right hand side of the, table in this slide. MA enrollees are also 1.6 times more likely to live in a lower income neighborhood than fee for service enrollees. They are less likely to live alone, less likely to own a home or a vehicle, and are less likely to be, English proficient. And here's why this matters from a methodological standpoint a point in in, you know, thinking about, like, the HCC risk adjustment model. You know, it's it's widely being used to compare two different programs, but it doesn't account for these differences in social risk. You know, it's capturing clinical complexity reasonably well, but it doesn't account for these risks that could be further driving utilization and health care quality differences between the two populations. And this is important because social risk factors can drive health care utilization and costs in ways that are not necessarily observed in a lot of studies or within various models and can have direct implications for beneficiary health outcomes. They could, lead to more, you know, social risk and lead to more preventable hospitalizations, more readmissions, and greater and greater risk of being in poor health is documented by, you know, several studies, in this area related to the social determinants of health. So in all, I think it's just important and what the a big contribution of this study is is that it's able to account for some of these differences between MA and and fee for service population that are not accounted for in a lot of comparisons between these two groups. Awesome. Alright. Well, thank you both. And then, Christy, I will kick this next one back to you. So we've talked a lot about the advancements in the approach. Can you start can you share just a few of the key findings of the study with us? Absolutely. Let's go to the next slide and we're gonna look at some of the quality measures that we evaluated in this study once we had these two matched populations. But we also looked at the actual populations. So the first one we're gonna look at is a measure you all are very familiar with, the thirty day all cause readmissions measure, which is a really good measure of quality because readmissions have lots of repercussions and impact for both the members, the beneficiaries, and as well as costs. On the left of the graph, you see the unmatched results. So that represents what the rates would be if you just compared the actual who enrolls in those two populations. And you see that the Medicare Advantage rate of readmissions is lower even if you don't do all those apples to apples comparisons of similar people, right? The rate in MA was 10.8% compared to a rate of 18.7% in fee for service. So Medicare Advantage is doing better even before we account for these population differences. On the right of the graph, we see the rates when we're comparing similar members. The only difference being one enrolled in Medicare Advantage, the other enrolled in fee for service. And now we see that the Medicare Advantage rate actually decreases from 10.8% to 9.1% while the fee for service rate actually goes up, meaning they're doing worse than we expect with people who look like this, right? Their rate goes up to 20.6%. So you really see quality gap is much wider than we see it being before we do this matching. And you can imagine scenarios where if those rates are closer you might get the reverse signal, right, and might not be finding these two disparities in care. And so you know, really we see that, you know, preventing readmissions, even in these members with complex clinical and social risks, really have to be addressed. Let's go to another one. The next slide, slide eight. We actually see a similar story when we look at another measure, and this is preventable or potentially avoidable hospitalizations. This is another hospitalization measure, but really captures those that proceed really to be avoidable, to be preventable. And here we see that the Medicare Advantage rate is lower, but not by as much, right? It's 14.4% versus fee for service rate of 17.1% in the actual populations. But again, we see that quality gap is really growing significantly from 1.2 times higher potentially avoidable readmissions to like 1.7 times higher in the fee for service population when you're comparing similar members with similar characteristics. So Medicare Advantage rate goes down very slightly to 9.6% and the fee for service rate is pretty similar to what it is before. And I think if you go to the next slide, we have a couple of other examples. And here we're seeing some a little bit of mixed results. In these other examples, We see, for example, that Medicare fee for service has lower rates, so worse rates of colorectal cancer screening, both before and after matching. But again, we see that gap widening to 54% lower rates in MA when we compare the similar beneficiaries. Fee for service actually does better with their beneficiaries getting their flu shot. But again, we do the matching, that quality gap is not very large, right? Fee for service also does better with diabetes care related to an eye exam. But again, the difference is smaller after we control for differences in the two populations. So if you go to the next slide, please. Just to summarize what we're seeing here is that we see that true differences in quality can really be masked when there are significant differences in the populations you're comparing in their demographic characteristics, their clinical characteristics, and their social risk characteristics. And we all know and NCQA has taught us that the goal of quality measurement is to isolate true differences in quality outcomes so that plans and providers can focus on the most vulnerable patients who are not having the best outcomes. And most of these measures are not adjusted for all of these differences in member characteristics. And that's that's okay. And there's been a lot of debate. I I co chaired the in the National Quality Forum Scientific Methods Panel for a lot of years, and there's a lot of debate about adjusting quality measures for these characteristics. But what you can do and should do is really another approach to identify these disparities is to stratify the measures by certain characteristics. You should stratify your measures by age group, by sex, by number of chronic conditions, or some measure of severity like the Charlson Comorbidity Index. You should stratify them by STOH factors if you can. Low income, low education, low language proficiency. Understanding true differences in quality is really essential if we're gonna reduce costs, prevent avoidable outcomes, poor outcomes. And so I think, you know, this this work that we did really brings that home very clearly, I think, Bert. Yeah, it's all very interesting. Thank you very much. And then, Sari, from your perspective, what are the differences in these outcomes? What does that mean for health plans? I think Christy touched on it a bit but I'd love to hear from you. What do you think that means for health plans? Yeah, I think in short, it means that managed care is really bringing significant value to the Medicare program. We see here that even with a sicker and more socially challenged population, we see that these structural characteristics that managed care and brings to the Medicare program through Medicare Advantage, these characteristics that are simply not built into fee for service in the same way that these really bring tremendous value. For example, the emphasis on preventive and primary care, the incentivized care coordination, supplemental benefits, these characteristics of managed care that are unique to managed care really hold tremendous promise for this population, not only in the area of cost control and addressing costs, which is important, but for the purposes of our conversation today, as we're looking at these key quality metrics, we really see this tremendous value that it brings to the patients. I would encourage plans to look at these findings less as a scorecard and more as a prompt to help inform the plans as well as other healthcare stakeholders to ask more precise questions about quality improvement and how to proceed along that quality improvement journey. So one take home message to me that I'm hoping plans and others will take from this research is that it's really critical to ask key questions about the methodology behind the analyses that are driving a lot of quality improvement and determinations of performance, quality performance in managed care and in MA versus fee for service. Namely to ask the questions about which populations are in the numerator and in the denominator. How similar are the populations that are being compared? What do the measure specifications account for? And what do they leave out? I think those kinds of questions will really help all stakeholders pinpoint specific challenges, understand where there's opportunities for improvement, and help to target innovations. I also think that there's relatedly the ability to look at these patterns that have been emerging that this research identifies to hone in on the very narrow questions where there is opportunity to continue this this quality improvement journey. Accounting for for who is enrolled and and when they are, what conditions they have walking into Medicare, whether it's fee for service or MA. I think it's so critical to help us understand and ask those questions, those nuanced questions that will really help us drive quality improvement going forward. Thank you very much. All right, Fred, I'm going to ask you this next one. Can you talk a little bit please, about the program differences between Medicare Advantage and fee for service and and, you know, what you've if you which of those differences you believe are really driving the differences in outcomes? Yeah. Happy to elaborate. And I think before diving into it, think it's important to emphasize as well that the findings in this study are actually largely very consistent with what is observed in the literature as a whole, that that of studies that compared MA versus fee for service. So there was a, you know, literature in health affairs conducted by and others a few years back that compared the data sis systematic review of of studies that focused on managed care versus fee for service differences. And they, you know, conclude that MA you know, across these studies, MA consistently was associated with more preventive care visits, fewer hospital admissions, fewer readmissions, lower spending, and shorter lengths of stay. And I think in studies that looked at quality outcomes, you know, MA generally outperformed fee for service as well in terms of looking at other quality measures. And I think this falls in line with what we what what Inovalon found here as well as a a previous Inovalon study that was done in conjunction with, some har researchers at Harvard that found consistent findings in terms of decreases in, relative decreases in, MA, hospitalizations and and utilization, using kind of a a more kind of quasi experimental, design approach. And, ultimately, what I think it comes down to in terms of what these mechanisms are here is that, you know, MA plans bear the financial risk of a hospital readmission, and fever service providers don't necessarily do so or potentially profit for it. And I think everything flows from there in terms of looking at the design differences between MA and fever service and how those could be driving differences in the outcomes analyzed in this study. So, Seri alluded to and mentioned a few of them, in her response to the previous question, but I think, these mechanisms are are that could potentially be driving these differences. So first and foremost, the emphasis of care coordination and chronic disease management within Medicare Advantage relative to fee for service. So MA plans are required to coordinate care across settings and have a strong financial incentives to do so through, you know, capitation and quality bonuses, which ultimately prevent can lead to the prevention of unnecessary hospitalizations and reduce readmissions and manage chronic conditions proactively as observed within the the results of the study. This is, you know, particularly important with populations that have, you know, high rates of diabetes, COPD, heart failure, and other complex, conditions that require ongoing monitoring. And the evidence in this study really brings that point home. You see it in the numbers where in within the matched analyses, the fee for service had a 126% higher thirty day readmission rate and a seventy one percent higher preventable hospitalization rate. And so this is you know, these are not small differences here that we're observing that are observed across the populations. I think a second key component is the supplemental benefits that MA plans provide that can really directly address some of the social determinants of health and the differences between the the the higher prevalence of these were social outcomes that are observed within the MA population. So, you know, MA plans can offer dental, vision, hearing, transportation, meals, other social supports that directly address some of the social vulnerability that their members have, which are documented within the MA study. And I think this is, you know, very important for, particularly, the the the the previously the previous population that had Medicaid that came into Medicare Advantage, where these individuals are able plans are able to connect these individuals with the social supports that they need that could ultimately lead ultimately lead to reductions in high more costly utilization down the line. So, for example, transportation to a primary care visit, or or other support, specialist appointments can potentially prevent, you know, ED visits down the line. Similarly, providing, meal support to someone who's in congestive heart failure, can, potentially lead to, fewer, fewer events down the line in terms of, hospitalizations. I think a third tool would just be the the care management, tools that MA has, at their disposal to keep people out of the hospital in the first place. So within this study, the InnovaOne study did show that MA enrollees use 20% more unique, prescription drugs and have a a generally higher rate, supply of prescription medications compared to the match fee for service enrollees. And this just reflects the the the the fact that MA plans tend to invest more heavily in pharmaceutical management for chronic conditions to prevent acute care outcomes among their populations. So you can think that, you know, keeping a diabetic on their medications, managing a COPD patient's inhaler regimen, or titrating heart failure patients' diuretics can really potentially down the road lead to reduced hospitalizations and readmissions. Finally, I think there's also a a component of greater accountability for outcomes in MA compared to fee for service through, more value based payment arrangements. So MA plans, are increasingly operating under value based contracts and alternate payment models, that align incentives, with providers and physicians. So these, types of payment arrangements can create additional financial incentives beyond just the capitation payments to manage care more efficiently and more effectively among patient populations and potentially, that are directed towards quality improvement. Thank you very much. Alright. Thanks, Fred. And then, Christy, what are the implications of all you know, you've got all these insights that you that you all gained from this research. What are the implications for policymakers and for health plans? Yes, Sari and Fred have articulated the differences in these two programs and I think research like this can really inform strategies for Medicare program design as we move forward. There's a lot of discussion on the hill about which program is better, which program is cheaper, which program provides better quality results. Is it fee for service Medicare or Medicare Advantage? And this kind of research using real world data, using real world Medicare Advantage encounter data which has not really been available so much today. CMS hasn't had Medicare Advantage data. They've had fee for service data and researchers have had fee for service data for decades, right? But not Medicare Advantage data. And even MedPAC sort of looks at fee for service switchers and projects based on fee for service switchers. We actually had a huge population of Medicare Advantage plan members across you know, plans of all sizes across the nation, and we're able to use that real data. So it's really important to if you're gonna understand the differences in the two programs to have actual data from both of those programs. But I think these results, these quality results really can help us understand where Medicare is doing a good job and those areas where Medicare can improve outcomes. We saw some areas where fee for service is doing better. There were actually more in our study. I wanted to show you some of the really the impact of doing these apples to apples comparisons where we can really better understand what the true performance is and really identify those disparities of care that might be related to the program design and some of the things that Fred and Sari have just talked about. So I mentioned earlier this research points to a need to just break down your populations, your population level quality measures, because your average rate could look like you're doing okay. And and because sometimes these things average out. You're doing really well with the healthier, wealthier, you know, members in your in your plan or or that you you you know, and your providers are are taken care of. But when you look at specific subsets, maybe by race and ethnicity, maybe by sex, maybe by some of the social drivers of health, that's when you're gonna see where the disparities might be. People who have high income versus people who have low income, women versus men. I just attended the Clinton Global Initiative. I was fortunate to attend yesterday And I did not know, and I've been doing healthcare research for decades, that women were not included in clinical trials until 1993 when Bill Clinton signed a law. I did not know that. And to me that is flabbergasting, right? That women were not even considered. So doing your quality measures stratifying by sex is really important because we still have a long ways to go in terms of making fair access and equal outcomes. I think, you know, beyond that, addressing all of the all of the patient characteristics that are impacting their access to care and treatment and good outcomes will ultimately lead to lower health care costs. Because we're gonna reduce these preventable outcomes, these preventable hospitalizations, the worsening of diseases like COPD, diabetes, congestive heart failure and others. I finally just want to point out that we're talking about Medicare here today, but the message, the underlying message here really holds true for any quality comparisons that use large populations, whether it's provider populations, health system populations, you know, comparing different different commercial populations or Medicaid populations. You really need to account for differences in the populations to find those true quality gaps that might be buried in an average rate somewhere. So this is this is not just applicable to to Medicare, Burke. This message should go beyond that. Absolutely, thank you very much. Very interesting. And then Sari, sort of a similar question to you. I'm going to ask you know what do you hope that this research accomplishes regarding potential changes to the Medicare programs or policies? Yeah, it is a similar question but it's a little bit different. Let me say that my hope is that this research improves both the evidence we use to evaluate Medicare and the decisions that we make about how it serves beneficiaries. So first of all, I hope that it raises the standard for comparing MA and traditional Medicare. Not only does this study include information about people's health before they entered Medicare, it also includes actual experience in both coverage options. And critically, it includes people who enroll directly into MA at age 65. I hope it prompts policymakers to seek out MA versus fee for service comparison research that similarly accounts for the meaningful clinical and social differences that we saw in this study before it draws conclusions about outcomes and performance. I also am encouraged by this research and hope that it helps to make quality outcomes a more central piece of the Medicare policy discussions. We see here that MA enrollees experience lower readmission and potentially preventable hospitalization rates, which are obviously very meaningful important outcomes for beneficiaries. And this really means examining how clinical and social circumstances affect comparisons. These have not historically been a central piece of the fee for service versus MA comparison research, body of research. And it's such a critical piece we found in this research that my hope is that this is widely acknowledged and that those that do those comparisons, the researchers that do those comparisons take into account these characteristics. Ultimately, hope for this research is that it really strengthens the connection between Medicare policy and the care that beneficiaries actually experience. I think we should take these findings very seriously. We should build on them, and we should continue to ask these nuanced questions so that we, all of us, all healthcare policy stakeholders can work to continuously improve quality of care. Thanks so much. Okay, Sabin, the last question for you Fred before we go to audience questions. How do you think that these proposed there are some proposed cuts to Medicaid and potentially lower Medicare payments might impact benefits provided by those MA plans that may be driving these better outcomes and the lower costs? That's a a great question, Burke. And I think it really gets at something fundamental that this study shows that, you know, forty two percent of the MA population in the sample previously, arrived in MA from having continuously enrolled in Medicaid coverage, and that rate was, twice as high as the rate, in terms of Medicaid patients going into fee for service. You can imagine that that that number is even higher if look at people who are kinda churning in and out of Medicaid coverage at a higher rate than, you know, what happens in commercial insurance. Those people aren't even necessarily included within the sample because of the the sample requirements. So, you know, know, these are individuals who are coming into MA at a lower baseline level of health in terms of having more chronic health conditions and and also having greater social vulnerability. So I think when you have, cuts coming or underway for in the Medicaid program as well as reduced Medicare payments, I think those are kinda compound risk to MA plans and the beneficiaries, that they serve, particularly some of the more vulnerable populations within Medicare Advantage. So on the on the Medicaid side, you know, the the one big beautiful bill act or, you know, the working families, tax cuts, are projected by CBO to reduce Medicaid and CHIP spending by over around $990,000,000,000 over the next ten years as well as resulting in millions of, individuals losing their health insurance coverage. So you can imagine if if states respond, to these Medicaid cuts through, you know, funding reductions, by, you know, tightening eligibility or reducing, benefits, you could see more people arriving into Medicare at age 65 with gaps in their health insurance coverage being previously uninsured, having worse access to care leading up to age 65, not necessarily receiving the preventative care services that they might need, as, if they lose their Medicaid coverage, and potentially leading to worse health outcomes before these populations even enter, within both the Medicare fee for service, but as well as, Medicare Advantage, which they disproportionately, based on this study, end up going into. I think on the Medicaid side, you know, MA plans are under, I think, you know, sustained pressure pressure on multiple fronts to, reduce spending, whether it's through lower benchmark, payment rates, through tightening of risk adjustment, or through pressures to reduce, you know, you know, overpayments in in Medicare Advantage kinda based on what MEDDPAC and some others have highlighted in terms of, you know, estimates that they have have put out there in terms of, you know, more intensity encoding and and potentially higher payments within med within Medicare Advantage. I think that, you know, with additional cuts with Medicaid as well as potential Medicare cuts, I think that is going to increase the complexity, and the vulnerability of the population that Medicare Advantage serve serves. And, ultimately, the the plans that are providing these services will have to absorb those cuts through changes in their benefit design. I think this is really where you'll see beneficiaries hurt, in response to potential payment cuts. I think, first of all, if you have reductions in, you know, Medicare, MA benchmark payment rates, that could ultimately be passed on to beneficiaries through higher payment, premiums or more cost sharing and potentially reductions in supplemental benefits themselves. And this is, really, will will will affect the most vulnerable populations where the supplemental benefits really come into play and really are able to prevent them, and really able to target their social needs. There's been previous research by, Michael Chernew and others that have highlighted that benchmark payment cuts to Medicare have, led to modest reductions in supplemental payments. But the authors themselves know and caution that, you know, these were gradual cuts to the Medicare benchmark payments and that larger cuts or a combination of cuts that occur more quickly can potentially have larger impacts on the provisions of, supplemental benefits to beneficiaries, particularly those who, you know, are more at risk and more benefit from these types of programs. I think another way where these cuts can adversely affect beneficiaries is through plans potentially exiting the market in response to to payments. So if you you can imagine that payment pressures can, put pressure on plans to exit, you know, unprofitable counties or market segments entirely, which are particularly within, like, low income or rural areas, especially in areas where there's been kind of more, growth in MA over recent years, but where margins might potentially be tight. If this were to occur, and a plan is to exit, the beneficiary won't lose coverage in and of itself. They would enroll into a fee for service plan, or they can enroll into a different MA plan. But their continuity of care is disrupted, and their care coordination will, be disrupted as well. They might have severed relationships with the providers that they've seen in the care management, benefits that they had with their previous MA plan. And I think those are the populations that will be, hurt the most, you know, is if you see these types of larger dynamic changes occurring within the MA market. And I think that that's also backed by some of the empirical evidence that has shown that when MA plans exit the market, in response, there's been a large increase in hospital utilization following. Alright. Well, thank you. Thank you very much to all three of you for a really great discussion thus far. Let's continue it by I'm gonna navigate over to the q and a and look at some questions from audience. I think, some of the earlier ones, I think you all touched on, but I'm gonna ask them anyway, because I think it it may be worth sort of expanding on. So, one of the first ones I see is do the, excuse me, do the readmissions diagnoses differ from between fee for service and MA? Readmission diagnoses differing between the two. Yeah, I can take that. If you remember the first data that Sari sort of looked at which was we're looking at who, when people enroll. We did see that in fact people who enroll in Medicare Advantage have more higher prevalence of chronic conditions. So they have more diabetes with chronic complications. They have more COPD. They have more depressive symptoms and more obesity, more vascular disease. So they have more chronic conditions to begin with. We didn't exactly look at what they were readmitted for in this study. We were just calculating the NCQA readmissions rate. But looking at the populations because MA has, they had a higher prevalence of chronic disease, you would expect them to have higher rates of readmissions based on that. So I think the underlying story is there, but certainly something we could look at but we didn't look exactly at why they were readmitted or for either the preventable hospitalizations or readmissions. Awesome. Alright. Thank you, Christy. Okay. Next up and let's see. This question is kind of a two parter. Did the study incorporate analysis of pharmaceuticals used? That could be significant, especially for those with chronic conditions, says the the individual asking the question. And they're they had a follow-up, but it's related, so I'll tack it on here. Did the study incorporate analysis of pharmaceuticals used and which drug coverage plan they had? Yes. So the answer is yes. The short answer is yes. We required for everybody who was in the study, we required them to have both medical coverage. So for fee for service parts a and b coverage as well as pharmacy coverage as far as drug coverage, so part d plan. And then for the Medicare Advantage plans, we only included MAPD plans so that, you know, they had both medical and pharmacy coverage. So other than being, you know, part d or or an MAPD, we didn't look at the specific plans obviously, but but we did require that for the entire five year period that we were tracking these members. And in fact, we looked at some of the drug quality measures like medication adherence for diabetes, medication adherence for cholesterol. Those are three that we looked at specifically in the study. Excellent. Alright, thank you very much. Next up next question is, do we know the impact of pre auth and denied claims on the differences between fee for service and MA? Sarah or Fred, do you want to speak to that? You may be able to speak to that better than I. I'll give you a chance to answer. And I'll just restate it again. Do we know the impact of pre auth and denied claims on the differences between fee for service and MA? I mean in short, it was not part of what we considered in this analysis. It was outside of the scope. So the short answer is no. An interesting question but it is not something that we considered. Yeah. I think there's been some other work in this space that that has been done. I yeah. I I I can't remember what exactly it said. Interesting question for sure, and always always more research to dig into. Thank you all. And then the next one is what were the sample sizes? I I think think we alluded to this but maybe we can double click. What were the sample sizes? Yeah, they were in the 300,000 or so range. Usually we get millions of patients when we do Medicare but because we were requiring three years enrolled in the same plan before they turned age 65 and then enrolled in Medicare, so three continuous years of enrollment with medical and pharmacy benefits and their commercial and Medicaid plan. And then another two years of enrollment in their same Medicare Advantage plan or in fee for service. They had to stay in the plan they enrolled in. So that really, you know, that reduced our population size quite a bit because we had that very long, you know, enrollment requirement. So yeah, I don't remember the exact numbers. We we can certainly make the study available to you. I believe it's your website and there's link and and it's on the Inovalon website. If you can't find it, out to us. There's lots more information in this in the full study. Today we're focusing on quality because qualities. Thanks so Just a quick answer, I just pulled it out of the report. It was 45,000 beneficiaries, 45,530 to be exact. And in MA it was about a little over 10,000 and in traditional Medicare fee for service we looked at a little over 35,000. I'm thinking of a different study. Yeah, I know the numbers were smaller because of that long enrollment. Yeah. That's right. The propensity matching caused us to have a smaller number. Also, that's true. Still, you know, thousands and thousands of patients. So we had lots of Lots of. We had sufficient power for the study. Yeah. It just also just kinda shows the trade off when you have being able to do as much of an apples to apples comparison, but then being like, well, how generalizable are these findings to the rest of the population? I think a lot of these studies, you know, like, the the switcher analyses has a small sample and a very narrow sample. This is, I think, a more generalizable sample, but, you know, I think that the the the data quality matching is is very high. But even studies that looked at larger samples, you know, did find findings that are consistent with, you know, these these quality magnitudes of quality change. Yeah. I think I think the Harvard work had had this numbers in around the 300 thousands, and we did sort of the same, you know, analysis type of analysis. But yeah, you know, the clinical advisors that we had, the medical directors, they really wanted to look back three years because diagnoses aren't always coded well, right, every single year and they want to make sure we're capturing all of the diagnosis. So that's why the long look back period, which is which is very unusual for a study like this. We usually have a a twelve month baseline. That's our standard in our research that we do at Inovalon. So this was a long long look back just to make sure we're capturing everything. Alright. Well, to to help us end on time, I'm gonna land the plane with one final question, and I'm going to read it exactly as it's written. How do we get more fee for service beneficiaries to enroll in MA? What is the recommendation? I'll let you guys take that one. Well, I would open by saying I think we need to get research like this out there. I think that is really the most important strategy is to educate consumers about the higher quality of care that they are able to access and the additional benefits that they are able to leverage through MA versus fee for service. I think it's not there hasn't been a tremendous amount of research that is translated down to consumers. And this is a big part of, frankly, our mission. And I know of Fred's mission as well to really help consumers understand the value that managed care brings to the healthcare ecosystem. And it's really through education and these kinds of webinars. This is the beginning of the answer, but I think having this kind of work out there is is critical, a critical step to enabling that education. Yeah. I would I would just add. I mean, you know, health insurance choices are complicated. They're they're they're not simple. And I think you getting plans to effectively show that value and and being able to use research like this, really trying to point out, like, where the benefits are, particularly for people who are, you know, managing multiple chronic conditions and have various complexities as a as their agents of the Medicare program. I think using having the right set of tools for consumers, being able to convey this information of value is important. And I think that's the trend that you've seen. If you look at enrollment in Medicare Advantage as a as a share of total, it's all, you know, increased significantly over time to the point where it's, you know, over over half of the population. So I think that's what the general trend is, but, know, you it just takes time. You're not gonna see drastic natural changes from one year to the next, like, where you'll have, you know, 52% of Medicare Advantage up to, like, 75 or 85%. I mean, there's gonna be natural naturally, some people just don't want to there's, like, a a stickiness to switching your health insurance plan. So there could be people who are in fee for service, they just stick with it and don't wanna change. And I think being able to show the value of the program and how it does better job of managing managing care for those enrollees, I think is important over time. I'll just mention that we also saw in this study that the people who were enrolled in managed care either in commercial managed care plan or Medicaid managed care plan were much more likely to enroll in Medicare Advantage than they were to go to fee for service Medicare. That's interesting. Alright. Yeah. Well, thank you all again. This was very, very enlightening. I I think folks really enjoyed it. There was a lot of a lot of praise in the comment section and in the in the q and a. So well done, you all. The for the handful of questions that we didn't get to, apologies there, but Christy's email is up. I'll I'll kinda put you on on first there, Christy. But please reach out to myself or to Christy or to any of the other speakers, and and I just wanna thank you all again for a very engaging and enlightening conversation. Thank you. Thank you. Alright. And thank you all for tuning in. We will see you all next time. Thank you.