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Leveraging Your NCDR Data & Accreditation to Addre ...
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Good afternoon, and welcome. Apologize for that. I'll tone it down just a little bit. Make sure everybody's awake after your lunch, and you're ready to go. We're excited about this afternoon's general session. It's going to be a very thought-provoking hour that we're going to spend. And it's a really important, I would say, foundational step of looking at different ways to utilize ACC and accreditation NCDR data sets. The session title is Leveraging Your NCDR Data and Accreditation to Address Inequities of Care. My name is John Jennings, and I serve as the vice president of clinical advisory services for HCA Healthcare, based out of Nashville, Tennessee. It is my pleasure to serve today as the moderator for this session. And joined with me this afternoon is a host of phenomenal leaders. We've had some great discussions, I'd say, prior to this session, and really in planning this. They have great passion for elevating awareness, discovery, and problem-solving approaches to addressing health disparities and inequities. The format for the next hour or so is going to be really threefold. We have a couple of formal presentations that will set the foundation, and again, hopefully spur some really mindful thoughts on the topic from you all. Following that, we'll have a panel discussion. And then lastly, question and answer. And this is where we really want to hear from you. This is, again, a very important topic. We heard from Dr. Massoudi this morning in his keynote, as well as Dr. Frey, about how the ACC's strategic pillars are addressing inequities of care, and the focus. The focus for NCDR, accreditation, et cetera, to begin to explore new ways of discovering the data, but most importantly, driving clinical improvement and improving the care of the patients that we all serve. And a lot was said this morning about this group in the room attending virtually, that you all are the ones that drive the improvement. You have the data. You know how to really leverage that information. Share it with your multidisciplinary clinical teams, the physicians, the leaders of your hospitals to make sure that we're, again, providing excellent care. So without further ado, I'd like to introduce our first speaker. Dr. Aaron Mock. Dr. Mock is the vice president of health care research for the advisory board. Dr. Mock is based out of Washington, DC. His focus work has been much in the cardiovascular space, leading the cardiovascular roundtable for a number of years. His 15 years health care research experience specializing in health care policy and market dynamics. And what I just said there was a very small snippet of his accomplishments and what he's been able to really lead. So without further ado, please join me in welcoming Dr. Mock. Thank you, John. Thank you for waking me up from my postprandial nap. Always the challenge with these things is the worst place to go is right before drinks. But this is the second worst place to go. But we'll try to keep you as entertained as we can through this process. I mean, it's obviously a remarkably challenging topic. And John alluded to the beginning of the process. And I think we truly are at the beginning of the process. There is a long road ahead of us. Lots of opportunity, but lots of challenges that we know exist in relation to this. Both utilization of data, but just understanding the scope of the problem. And I think I'm going to talk more about the scope of the problem here, because we have experts who are very deep in the data side who can talk a lot about some of the unique challenges that we're confronting. But I want to give you some sense of the lay of the land and just why it's so hard. Why has it been so hard to start to address issues of disparities when it comes to cardiovascular care? We're going to jump into some of the slides if we can. So this, hopefully, does not come as new information to you. But when we look at some of the trending data when it comes to CV comorbidities, but really things that are also associated directly with CV, we see skyrocketing rates of increase, really across everything. If you look at some of the data on the left of the slide here, you can see just how profound it's going to be going forward. This is sort of an overdetermined process. We know that this has been a challenge for some time. If we look at some of the drivers that we're likely to see going forward, it's only going to get worse. You look at the baby boom population, the top of the curve of the baby boom population just turned 75. We know what happens. We in this room know what happens when you turn 75. We've had a healthier over 65 population that we've ever seen before up until now. But as they evolve into later stages of their life, they're going to have pretty pronounced care needs and a lot of those are going to be cardiovascular in nature. We also have things like increasing patient complexity. Just more patients with the kinds of comorbidities, either things like ESRD or diabetes, are the things that make it very difficult to manage some of these patients in ways that can start to address some of those disparities. And obviously, there are things like social determinants factors that are playing a role. So all arrows point to a bigger problem. Unquestionably, with that, CV inequities are kind of adding to the burden rather than subtracting from it, right? And we know those big in the outside of the hospital. Everybody has seen data on this or read studies in relation to this, whether it's related to where you live or how you self-identify or your socioeconomic status or any of the other kinds of factors that we know are there. They manifest themselves outside the hospital, but they come into the hospital. We don't have a lot of control outside of the hospital right now. We do have control inside of the hospital space, or at least a degree of it, and that's really where we need to start putting our attention. And we know, from pretty robust data actually, over the course of 20, 25 years, that those disparities are perpetuated both in the research context, where certain populations are just left out of research and therefore left out of our understandings of some of the challenges that they confront, or in direct delivery of care, we see pretty significant disparities. And you can see just a few data points on the slide here in relation to this, whether it's around things like length of stay or referral likelihood or just the opportunity of being viewed by the right CV specialist at the right time. It's manifest. So it's a big problem outside in the population. It's a big problem in the hospital. And it's having pretty significant consequences on where we stand and how we perform from a cardiovascular service line perspective and from a care delivery perspective overall. So we've seen pretty robust data on this as well now. When you look at where CV leaders are seeing disparities manifest, it's in all the things you see on the left of the slide here, things like screening rates, which are highly variant, shockingly so, across different populations, to a degree that runs into huge challenges. Because how are we going to track data and get a good sense of what precisely we need to do to address this if we can't even capture who needs to be screened at the right time? Readmissions, length of stay, that's obviously manifest. You look at any of the major categories you'd want to look in relation to this, like heart failure, and you see that kind of manifesting itself. Complexity within certain communities, just going up and up and up without our effective means of addressing that. Making for a much more confused data environment in which to evaluate what works or what doesn't or how we're going to get them in and actually care for them. And things like referrals. And of course, if you talk to certain administrators or you talk to hospital CEOs, that's what they're worried about. They're worried about things like referrals because the cost associated with that is pretty profound. You see the sort of cost drivers over on the right of the slide there. Whether it becomes things like just overall aggregated CV cost or opportunity cost for not managing these patients directly, there is a cost. We should do this because it's the right thing to do. We should do this because we want to pursue quality and address disparities. But if all else fails, we should do this because it's going to keep the enterprise sustained if we're doing it appropriately. And in the long run, that is a necessary factor in relation. So we're seeing a lot of trends that are kind of pointing to the need for greater attention paid to disparities, certainly. And the opportunity is obviously there. But we're encountering challenges. Why has it been so hard to capture data? And why is it going to continue to be very challenging going forward to get good and smart with the data and manage patients more effectively to help to alleviate some of these disparities? There's a couple of reasons. One has to do just with the trends that we're seeing across service line growth and decline. It's easiest for us to capture data, understand patients, and try to manage their care needs when they're inpatient. That's the area where we have the greatest kind of control. Now, there are areas of pretty considerable growth on the inpatient side, mostly because patients are having greater complexity of care. A lot of these have more medical admissions, too. But obviously, in the EP space or in the cath space, there's inpatient growth simply by virtue of the fact that we have aging populations that have complex care needs that have to be effectively addressed in the hospital. So a lot of that comes from things like valve procedures. Also, we have things like advanced heart failure, bad implantation, the kinds of things we'd want to do there, transplant, or ECMO, which, of course, in the last several years has become really important simply because of COVID. So there is some growth on the inpatient side. But relatively, the growth is really on the outpatient side. And it's a much more complex care environment there from a data perspective. It's just much more ambiguous. Parts of the outpatient space are the Wild West. It just becomes very challenging to manage some of that stuff. And you can see the growth, of course, it's in things like EP or peripheral vascular procedures, a lot of that medical cardiology growing as well. Now, that's a pretty big growth factor, 25% in EP in five years, for instance, or 12% growth in vascular. Go to the 10-year timeline, it's even higher rates of growth across that. But things don't get captured when you just talk about outpatient as a whole. Outpatient encompasses many types of care sites. A lot of that is the hospital outpatient department, but a lot is other care sites as well. And this is what's going to make it very difficult going forward to effectively manage some of these challenges. We are seeing a lot of care moving outside of the hospital. Alternative care sites, where there isn't great data collection, where wrangling data becomes very challenging. But we need to know more about what's going on there if we're going to effectively address some of the challenges of those disparities we saw earlier. Whether it's things like the growth of ambulatory surgery centers, which in some states are growing like mushrooms, or if it's things like office-based diagnostics, or increasingly outside of the hospital as a whole, there's going to be a lot of data to collect that will be helpful and illuminate where disparities manifest themselves, the challenges associated with them, and how to actually start to address them. But it's also going to be a very, very complex data environment in which to capture this kind of data in ways that are going to be deliberate, and intelligent, and intelligible to us. So largely, when you talk to folks on the CVS service line, or administrators, or all of us, we think of this as, in some ways, a solution to some of the aspects of disparities that we see. It's, at the very least, potentially an access solution. Hopefully, we can see certain patients in places like the home that would not otherwise come into the care environment and be seen. That might mean earlier intervention. It might mean learning more about what those patients happen to need. But it's also chaos. And under those conditions of chaos, we're going to have a lot of trouble being very deliberate about that data unless we build out the mechanisms that are going to be necessary to address some of this. And you can see that with things like virtual and home based care. Virtual and home based care are seen or understood to be the next frontier when it comes to some CV services. Certainly, there are lots of drivers in this direction that are going to be relevant for you in the room as we start to understand how we're managing some of these complex CV conditions, not just in the procedural space where it's relatively, I wouldn't say it's easy. It's certainly not easy. But it's easier to understand quality, evaluate outcomes, see who's getting a procedure or not, because it's simple. But these kinds of spaces where if we're moving towards a cross-continuum approach, where we're trying to move upstream from a prevention point of view, not just a secondary prevention, but to maybe even a little primary prevention, but at the very least trying to manage these patients better, it's going to be tough. It's an ambiguous data environment. Patients love it. There are certainly CV innovations that are going into the home that are going to have relevant data for us to capture that will tell us a lot about who is getting the kind of care, follow-up, or pre-care that they need, and who isn't, whether it ends up being things like virtual rehab or, in particular, heart failure at home, kinds of management techniques which have been grown by leaps and bounds. We know that this is the way of the future, but it is going to constitute a huge challenge. And theoretically, this is great for addressing disparities. In practice, this might exacerbate disparities. You could see these being very congenial environments for managing certain kinds of patients in homes. But what if you don't have a home, for instance? Or the home is a risky environment, so you can't put in the kinds of technology you'd want to evaluate that patient at home, so they're shunted to hospitals or post-acute care settings and not given the kinds of care that they need. These could be good solutions to address this. They may not be. Regardless, they're going to create a complex environment for data capture if what our goal is is to better understand the root causes of disparities and how those disparities manifest themselves in terms of quality outcomes. We're going to have to get better at that, absolutely. The case in point is something like heart failure, both heart failure treatment and prevention. Now, this is an area where there's been probably more attention paid to certain kinds of disparities and outcomes than others, partially because we have things like a readmissions reduction program, which you get penalized for not managing that patient better or seeing what those outcomes are. But if you look at this, we have a robust traditional approach that doesn't focus very much on capturing the sources of disparity or trying to address those. Moving from that kind of traditional approach to a next-gen approach is a goal that we have. It's one we want to pursue, but it's going to constitute some interesting challenges going forward. Wish we could spend more time on talking about this, but I know we want to move on to the rest of the panel. So the fact is there's just no easy path to addressing CV inequities, either from a data capture point of view, and we know that data does not directly translate into better outcomes. We have a challenge there that constitutes a major one we'll have to address. But also just from the fact that there are just very complex, over-determined factors that are shaping what we can do and what we can't in CV services in a way that we're going to have to get around if we're going to move forward in relation to this. We're not good just in quality. We're better at quality than we've ever been. We have lots of challenges just on quality. These factors, inequities, constitute a whole array of new wrinkles that we're going to have to start addressing if we're going to be wise about our moves. So there's no easy path, but there's ways to start. Realistically, we live in a business environment. Whether we want to or not, that's the facts. We need to find ways to make the issue of inequities as much a business imperative as it is a quality imperative. And using data to help do this is going to be a kind of path forward for us. Now we see that happening already. CMS is slowly but surely making steps to involve inequities in its final rules in ways that hopefully will ultimately manifest in real change, real change when it comes to addressing inequities. Now that's another thing we could have a whole session on because there's a lot of policy challenges in relation to this, but they're moving down that direction. So are plans. For the first time in history, really, health plans are starting to try to integrate metrics related to equity and related to inequities into their scorecards in one form or another. There's lots of ambiguity there. We will touch on what that ambiguity is, but at least they're moving down that direction and thinking different ways. At some point, social determinants and things like that are going to be integrated into our existing value-based arrangements and other tools that are helping us, will help us, hopefully move the bar. But the fact of the matter is we're going to have to move it ourselves. We can't expect other people to move it for us. The only way this starts to get done is if we have panels like this going forward, we think very deliberately about the role we can play in contributing to broader efforts aimed to effectively address that. So I hope that's what we'll be able to discuss in the rest of the panel. I'll stop there and move on, but I want to thank you for listening and discussing this a little bit. Thanks. Thank you, Dr. Mopp, appreciate that. It's a great presentation. Our next presenter is Holly Dalton. Holly serves as a cardiovascular systems project manager for Baylor, Scott, and White based out of Dallas, Texas. And I learned a little bit about Holly's role a couple hours ago, and she's got a big job like a lot of you all as well. She oversees the data abstraction and all the quality improvement initiatives for her system. And we're talking about 16 cath labs, 14 EP labs, eight cardiac surgery programs. And I know there's a few structural heart programs thrown in there as well. So please join me in welcoming Holly. All right. Thank you, John, for that introduction. And thank you, Dr. Mock, for kind of telling us what our 60,000-foot view is of equity, disparities, and how to kind of take that. My job is going to help you all take that from that 60,000-foot view to your facility view. So we're going to do that through viewing and identifying some of the CV inequities through your registry data and also the accreditation that the ACC has to facilities. So to kind of talk about that, there's a couple of things I want to address and provide information for. And that's going to be, how do you understand really what these inequities are? There are some things at the national level and even state level. And there's a couple I wanted to highlight. And then, you know, we are here. We are all involved in the NCDR data. And so what is that going to look like for us as we have that data available to us? And what can we do with that data to help our facilities, our health systems, and our patients in the communities that we serve? And then kind of wrapping it up, want to come off of Dr. Mock's presentation to talk about those imperatives he kind of left us with. How does this all roll in together? And how do we as data managers, quality initiatives, and CV administrators come to the table, a larger table, when we start talking about those business imperatives? So to kind of get started, one needs to kind of understand the main topics, which are equity, disparity, and social determinants of health. It can be difficult to try to understand that as sometimes they are very much intertwined and then also interchanged when talking about this conversation. So one thing is to kind of look at the health equity is the ability for people across the way to achieve their best health. That may look different for every different person, but equity allows them to do so in a manner that works best for them. Now, when we talk about those disparities, so we are talking about a very kind of systematically obstacles that certain populations, and this can be broken down into many different areas as listed here in the graphic, from your education, from the neighborhood that you're in, your social economic status, all these different things that are somewhat out of the box of what sometimes we think of, which is age, race, and ethnicity. So those social determinants really come from all the very integral parts of everybody's everyday life. They're listed where they live, learn, work, play, worship. All of that plays into how they access their care, what they think about their care, and that all plays into those kind of disparities. So one of the tools I wanted to highlight is the ADI mapping that's available through the University of Wisconsin. This is a free tool where you can actually get very specific address and area at your fingertips. So the ADI was actually captured about 30 years ago. So those questions we have now, well, they're not exactly new. They've just come up to the forefront with the pandemic and other things socially and through the discussions of care. So the ADI was comprised of 17 very different kind of composites of social determinants of health, including that education, income, employment, and housing. So what they did then further is kind of grouped it together in what they call neighborhood blocks. So that's where we can get granular for the zip codes that you service. So when we're looking here at California, they do ADIs based on a method from 1 to 10. One, you do not really have any disparities, or you're able to access and receive your care without difficulty to 10, those with the most challenges to overcome in order to get that care. And so as we look at the map, the way that is determined is to look at the color coding in which blue is associated with a 1, and then it goes through the orange and yellow to get to red, which is a 10. So to understand kind of where your community is, where your state is, how am I going to compare what we have in our data set? The ADI index through the Neighborhood Atlas is a great tool to utilize. And of course now, tool number two, is it going to be the registries that we live in every day? So every registry for the NCDR does have a demographics portion. And every facility does kind of abstract data differently from somewhat automation to full chart review. And in that manner, we can have a demographic set that is consistent throughout a patient population and is comparable through those reports that we get on a quarterly basis. And when you get to those detail lines, you can actually see what things are looking like in a like hospital, which is determined on volume at this point. And then also, you know, what does the registry kind of look like? What are these patients across the nation? What comprises of them? Are there areas in which you can really identify there might be some lacking in your facility? And then you can take it a step farther. So what you can do is actually take the outcomes that you guys are all working in, working towards, and improving, and now you can add a little bit of social determinants of health by actually also pulling in this information through demographics available through the registry. So this actually allows you, as the data manager, to kind of add that extra layer to the data for actionable and quality improvement moving forward to address these very sometimes difficult topics. And now we have the ACC Accreditation Services. So kind of what I like to think about is, you know, NCDR, they're the registries. They gather the data. Now what accreditation services do is they are providing framework that has been certified and proven for facilities to gain a network of putting up what works best at their facility, and then also having all those tools the ACC has across communities and across the nation to allow facilities to learn best practices that maybe they would not have access to, facilities that are very common in their population, but maybe in a different state. And so you can really gain and make those connections, just like we do here for this conference annually, to understand some different out-of-the-box thinking, and also share your out-of-the-box thinking. So to kind of put it all together, again, bringing this as a kind of call to action in a way from Dr. Mock is we have imperatives one, and we have imperative kind of three. So what can we do with those? Those are ours, and how we can get the opportunities in our facilities, back it up with the quality and analytics that NCDR and the ACC accreditation services supply. And then also, we can then kind of come to the table for two and four. So many of our facilities, as Dr. Mock mentioned, this is a forefront of the business model that through CMS and other things, they are trying to address. And understanding of the CV population and what that brings, and having data as a kind of specialist in that data really provides them with that clinical side and data to develop those business cases and look at the population in a different way that that group may not be doing currently. And through that and through understanding the resources that you may have at your facility, or resources that are available through your connections made here and through the ACC accreditation services, you can come together and understand what community resources you have at your fingertips to reach out to those patients that maybe aren't. And also understand for those community organizations how you can meet your patients where they are and get them to the care to have them live a quality and equal opportunity to do so for them. So the one thing we talk about to identify is listed here, that kind of the sex, race, and ethnicity zip code, gender identity, sexual orientation are all topics that really come up when we start talking about disparities in social determinants of health and how people get their healthcare. Now NCDR does provide a good chunk of that information to you, that being of course sex, race, ethnicity, and even zip code. But what I'm looking forward to discussing with the panel is how you can somewhat supplement that in a way, getting to even more difficult conversations regarding gender identity and sexual orientation. As Dr. Mock brought up in his presentation, there are different obstacles for both of those communities and different strategies that are needed to reach out to them and get them into your care. I appreciate the time to talk and I am going to bring it over to the panel. Thank you, Holly. So we're gonna transition to a couple other introductions. We have two additional panelists that, for those of you that have been around the Quality Summit for some time, these two do not really need much of an introduction, but I know we have some new folks and so we're gonna introduce. So to my immediate left is Andrea Rocha, the Director of the Center for Research on Sexuality at the Center for Research on Sexuality. To my right is Andrea Price. Andrea serves as the System Director of Population Health for Indiana University Health, based out of Indianapolis, Indiana. I've known Andrea for a number of years as a friend and a colleague, and I will say she's one of the best leaders in this space that I've seen. She is excellent at the most difficult part, which is execution, determining the tactics and executing and measuring success. So thank you for joining us today. To Andrea's immediate left is Joan Michael. Joan has been also a friend and colleague for a number of years. Joan is the Director of ACC, again, based out of Washington, D.C. Joan oversees the STS ACC TVT Registry and Impact Registry as well. And I've always been fascinated with Joan's ability for the TVT Registry, because those of you that work in that, it's a very unique registry. It's a partnership between ACC and STS. And, you know, let's be real, surgeons and interventional cardiologists do not always get along. But Joan has bridged that gap. And it is, I've had the opportunity to be in some of the meetings at the national level with Joan and the team, and it's been phenomenal. So thank you, Joan, for joining today. So I'm gonna tee up the first question for our panel, and again, this is gonna be very conversational in nature. One of the common themes when we look at, again, the concept of diversity, equity, and inclusion, and many of your hospitals, if not all of your hospitals, are standing up committees, potentially departments, of folks that are leading those efforts. And I would say more often than not, those individuals have little to no awareness of the richness of the ACC registries. My question is, what are some ideas and approaches on how to best bring the data set forward as a new resource for identifying inequities of care? Whoever wants to jump in can jump in. Well, I'll start. Thank you, John, for that lovely introduction. I think this could be a whole two-day conference to talk about these topics. And I think it's always the awareness has to be, people have to wanna work on it, and they have to come to the table with a willing to learn and to be aware of what their internal culture and their internal, what's happening, what's inside the building. But then also to be willing to look at their area that surrounds their cohort of patients or their community. And one way to increase that awareness is certainly look at data. And I would think if I, I'm no longer in a hospital, but was for many years, as somebody said, I think we took that as we were older than dirt. Thank you for saying that. We've been around for a while. But I think showing, if I were in a hospital, I would wanna pull the data from the various registries and do a display of where folks are coming from, who those folks are, and then say, and then let's look at what our community looks like, and is there a match, and where is there some holes in areas of work and increase in. So I think that looking at the data that comes out of the registry would at least start the awareness. You have to be aware that there is an issue or an opportunity to improve first. And it's multifaceted to attack the problem, but almost like sort of a, let's do an inventory of who's inside the building and who's outside the building, and is there a match, and then where are those gaps. And to add on to Joan's thoughts, I think the NCDR, what we do really, really well at the national level, and actually the international level, is we have a really good procedure group, whether it's outpatient or inpatient. Your attribution is spot on. You guys in the audience, you know exactly who's doing those procedures because you're reviewing the charts and you're looking at them. These are gaps that I would arguably say that a lot of people that are coming into these new roles at the system level are struggling trying to find good data sources in order to really assess what is current state from our DE&I initiatives. And so what I would do is if I was supporting the registry work at my organization, I would try to find out what are they looking at. Are they looking at, they're probably looking at across multiple mother-baby, CV, ortho. They're looking across multiple service lines. But if you can figure out what aspects of that they're looking at, then look at your data set and go to your physician champion or your clinician champion and start to show, this is what our data is showing. This is how we're aligned to what the executives on the C-suite are trying in different spaces. Is there something that we need to look at from our referral patterns or the type of care that we're giving? And that's a way that you can have really good actionable data that then can be trusted and looked at as far as how you're moving forward to address some of your inequities. You need that aha moment. And I think the data gives you that aha moment because I think there are a lot of decision makers in hospitals thinking, we're doing okay. We're doing all right. It's a lot better than it was 10 years ago. We're doing okay. And I think that data, as Andrea's saying, could provide that aha moment to say, no, you're not. Or there's some opportunities to even do better. Yeah, great. Thank you so much. I'm curious, Erin, you spoke about the involvement with CMS, third-party payers. Within this realm, do you anticipate that they will be looking to the registries more, knowing that, historically, they've been very interested in the executive summary metrics. They may not know about the wealth of information that's below, but do you foresee a time in the near future where they may be looking to the ACC and other registries and this group to help provide that information? Yeah, you bet. The way that they're interested in doing this, I mean it's an evolution, right, as payers and CMS want to become more sophisticated from a data perspective. They've always been sophisticated at, you know, risk stratification for, you know, reimbursement and things like that, but want to be attuned to address these things at a root cause because they're thinking about patients differently, starting to think about them in a longer-term way for private pay, and for CMS of course they're thinking about the just the cost curve, they have to address this. They are gonna go everywhere they can to do this, and they're gonna probably want to partner much more closely with bodies like you to be able to just understand your data functionality, understand what's actually available to them to actually start to develop these tools, and it's a slow process, especially at the federal level for doing this. Frankly, I think in some ways the private payers are moving faster at the moment, strangely enough, just because some of the dynamics that are going on, but they will get there and they will want to partner. So on your side, it's valuable to think about how those partnership opportunities can start to be cultivated and develop so that you can kind of provide the case back to them for what they need to be looking at and what, how they need to be thinking about reimbursement to incentivize this at the provider level. Yeah. Very good. So Holly, you referenced a lot about the accreditation process. I mean, I'm not as up to speed on sort of how that can be tied into this. Are there, are you aware, are there certain measures that the participants can can align to, assign, that help achieve and maintain certification in the various accreditations? I am myself also not a hundred percent, but I'm looking at all the things as we as a system look towards accreditation, is they provide a lot of tools, a lot of the standardized guidelines and best practices, and I look forward to seeing those kind of come up and change to address this. What are facilities out there taking those steps? How are they doing it? And is there a way to kind of be able to also focus that on your facility and your physicians, even now coming with somebody else who's done it similar to say, well this has been proven. And a lot of them are kind of knowing that this is happening through, you know, a lot of the articles and as mentioned before, clinical trials are focusing on how to bridge some of these gaps as well. I want to touch on something that you had mentioned, Joan, earlier regarding some early findings on the TAVR AVR space in terms of... Let's make this a TAVR talk. No, we talked earlier and this is a subset of all of our registry data, but we don't think it's different in the other registries either, but it's a point of discussion and a hot topic every time. As most of you know, with TVT we do annual slide sets so people could say what's our trends, how are we doing collectively, not only at your site and national level. And it was a pause to look at the demographic data within the TAVR world that we did that is their most recent slide set showing that there's been no budge on that needle. It's been a steady 4%, you know, African-American, 3% other. That means that's Asian, Hispanic and everything else. And then the 90% has been a high 90% with white patients seeking care and we talk about that a lot. The first time we ever showed our physicians those slides, somebody said this is really bad, you know, this will be on the front page of the New York Times or something that we're not providing care. First of all, we then later found out that level is not any different in the surgical population and it sort of opened our eyes a little bit to this is a problem in all subspecialties and especially within cardiology. We've seen that, so we look at that a lot and there's a lot of efforts going on. Antoine Keller in Louisiana, Wayne Batchelor in Inova, there's a lot of physicians around the country that are doing work on disparity, inequities in our little spot of the world and nobody knows how to fix that yet. There's a lot of ideas but there's a clear difference between aortic and mitral and why should we be looking at something else? We do know that patients seek care or they feel more comfortable coming in for care. If somebody on the team, somebody on the heart team looks like the patient, they don't have to be the physician but somebody caring for that patient and that aids with being accepting of the procedure, trusting the physician, compliant with their follow-up care. So we know that but this now is a little bit of a curveball. We're seeing an uptake in one procedure, the other procedure is stopped. It's just a, you know, flat line. So we look at that and we're trying to figure out again, how can we improve that or where can it be improved? How much can it be improved? And I think you mentioned earlier about, well, the age of that population. If our median age is 82, do some of these patients not make it till 82? So they're not even, you know, in the denominator. It's not an easy two-minute fix but it's, we're in this, within my small piece of the world, we're in that sort of awareness phase and doing an inventory and assessment of what can we do to help improve this. We don't know by how much but can we improve it at all? Any other thoughts from the panel on that? Yeah, I think, you know, you to point it to something very important, right? Which is, if we're looking at certain kinds of well-defined procedural categories that are later in life, we're already kind of missing the boat in the sense that, you know, a lot of these inequities, they manifest there but we're almost at the end stage of a process that manifests itself much earlier that has to be addressed. And the point we were kind of just making around the incentive structure for CMS or private pay, it's just not there. If we're going to start to move the needle here, it's going to involve certainly using our existing data sources to kind of illuminate it, make the business case to leaders across the hospital or CV service line that this needs to be done. But it also requires a wholesale transformation in some ways of the model of care and the model of reimbursement so we can get further upstream in this process. That's how we're really going to start to address some of these inequities. It's fine with procedures, it's very important for addressing procedural inequities but it's, we need to think of this very holistically and it's just hard for us to do that right now. So it's going to be a long process but hopefully we can move the bar. And I'll add, I think I'm off, you know in fixing this, it's not one size fits all, right? So that's by age group, that's by disease, that's by ethnicity or how folks identify themselves gender-wise and sexuality-wise. I mean it's not one size fits all. So it's like where do folks in different, with different needs and different age groups and different cohorts, where do they go for their care? And so I see this as sort of this metastasizing kind of you know astrocytoma with fingers all over. It can't be just one thing that fixes it and this is what we're going to do. Hospitals need to really kind of clean the slate, start over again and follow the patient and you know chip away at it. You know sort of a follow-up to that and I wonder as hospitals, as physician practices, ambulatory surgery centers, as growth continues, do the leaders of those growth initiatives, do they think about diversity, inclusion or is that, is it still putting these brick-and-mortar type facilities in areas of a higher affluency? Maybe where population is growing or is there a shift occurring to say you know what we need to be more mindful of the broader picture here, I don't know. Yeah it's interesting, it seems to be so contingent on the health system and the populations that they serve. There are some health systems out there that absolutely think about this in terms of where am I going to create a new revenue stream. It's an access solution to new revenue right and that's that's the basic means that they're going to do. So they're thinking very deliberately about service placement or the side of care shift along those lines right or how can I challenge a competitor by you know building a new site. There are some by virtue of necessity and sometimes by virtue who are thinking very deliberately about service placement to address inequities in care. You know where they're effectively care deserts in much the same way as you'd imagine for food deserts and saying hey you know we really need to have an office here or an urgent care center here or an ambulatory surgery center and and we're going to do CV procedural work out in this community because they won't come to us. But it's really remarkable to see diversity, the extent of the diversity in terms of people's strategies and responses. I think it's mostly historically been driven by necessity but increasingly the errors are pointing the right direction for everybody thinking about much more deliberately about some considerations on care equity in service placement. Very encouraging to hear that. Barb do we have any Q&A from the group? We do have a couple here. Let me see the question is can you please cite specific registry data that speaks to health equity? And so for those of you that are working with the data you know Andrea, Holly, John, what do you look at specific to NCDR registry data that might kind of help you with that health equity question? I'd like to get into the details. So like there's a couple different ways that I think that you can look at this depending upon what registries you participate at. One way that I've thought about how you can look at it is from a gender perspective. We know that a lot of times cardiac symptoms may not be quite the same in women as what they are in men and sometimes some of their symptoms are unrecognized either in an elective setting or in an acute setting. So if you participate in chest pain MI I think looking at your split between gender male and female of people that are coming in as AMIs and then take a look at your elective PCIs. See your gender split there as well. If you are looking at like 75% male elective PCIs but on the flip side your AMI rate is pretty high for your females there may be an opportunity to better bring females into an elective PCI setting as opposed to waiting until they actually are having an AMI. So that would be one way that you might want to go back and look at your data see if it says anything there. Additionally you know looking at your data from there's we have lots of procedures that are very much focused on shared decision-making with the patient. So if you're looking at your ICD registry which you know have all of the ICDs in there also required very comprehensive shared decision-making and you may happen to see that like 85 to 90 percent of your patients are white males. It could be a good conversation with your physician and seeing how they are having those shared decision-making conversations with females that may be referred in or with persons of color to see what type you know of wishes that they truly have whenever it comes to treating potentially a sudden cardiac death prevention which which you see with ICDs. So those are a couple of tangible ways that hopefully can get you kind of thinking about how data might be able to be used that you're already tracking to see if there's some opportunity to really advocate for some of your patients back at your hospitals. So there's a couple questions here's with themes around you know when you when we have you know various ethnic groups in our community and see disparities of care in the communities you know with language barriers or socio-economic structure you know what can the health care community do to kind of create these partnerships with social services to help match people with available resources are there toolkits out there available. I think what what I'm getting from these questions is how do we how do we help start solving this problem around these things that we see in our communities. Yeah I can I can speak a little bit. There are plenty of toolkits because this of course has been a problem for a very long time. And it's it there's lots of tools that have been made available to say frontline staff if you're working in an ED or you're working in other kinds of environments. They have those there haven't been as many directly related CV. Certainly this is an area that's kind of been like off the radar for for quite some time. Those are useful. Those are very much a first step. We're starting to see a lot of systems much more deliberately think about their partnership arrangements which were largely ad hoc up until now. If you needed to create a partnership and you had to go to community partner you'd find them and work with them. That was great when you could do it. Understanding that the burden of for instance unreimbursed care is growing for instance or that people go to the hospitals when they have nowhere else to go and need other kinds of services. Many systems are starting to become much more deliberate. We've seen several examples of health systems work with mayors work with the city government to create new and much more comprehensive approaches. Understanding that going forward it's very likely that hospitals are going to serve not just as a health care safety net right. But but really as a social safety net. And they do that right now in an unfunded way. Ideally going forward we're going to see new levers and hopefully incentives to kind of facilitate that both across CV and other services to ensure that we're really working together and our role as community anchor is understood and appropriately reimbursed so we can keep doing that. I think one thing to add on as well is looking at the resources that the ACC has invested in over the last few years at our organization. Anytime you get patient education it's always in English. So trying to have it translated into a different language actually costs extra money typically isn't budgeted and is externally contracted out. The ACC CardioSmart.org has done a really nice job to create patient facing education on various disease states that are in multiple languages that are free to download and to use. So I would start there if you know that you have a certain population that you're trying to address as far as a communication perspective. You know the one thing I would add is this is a great question and really it's the purpose of today right. So this is sort of grassroots and we hope that from today's meeting when we come back this time next year rooms going to be full double the number of people on the call. That we have posters that address this. We have additional sessions that address you know tactics strategies discovery that folks have put into place but we're early on really cardiovascular front here. But fantastic question. That's basically it. Although there was one question you know is NCD are planning on including social determinants health elements within the registries. And I would say I think that is something that we are exploring like what are those how do we do that in a meaningful way. We don't have that mapped out yet but it is on the discussion. So I think that's incredibly important. I'm glad that question was asked. I'm glad you address that because the weight and credibility that the ACC and CDR has I know in all your institutions is huge. And so that is a sort of level set. This is a priority and it allows you all to get a little bit further into the weeds into some of this I would say as well. So it's great to hear that. OK. Well it sounds like that's what we have from Q&A. Again I want to thank the panelists the presenters and all of you. Thank you so much. And we look forward to hearing the great stories about this topic next year. Have a great rest of your summit.
Video Summary
The video content discusses the importance of utilizing ACC and accreditation NCDR data sets to address inequities of care in the healthcare system. The speakers highlight the need for awareness and understanding of health equity, disparities, and social determinants of health. The data from the registries and accreditation services can provide valuable insights into identifying and addressing inequities in care. Specific examples are given, such as analyzing gender disparities in elective procedures and referral patterns, and using data to assess and improve health equity efforts. The panelists discuss the need for a holistic and multifaceted approach to addressing inequities, involving partnerships with social services, language barriers, and socioeconomic factors. The video emphasizes the importance of using data to drive quality improvement initiatives and make a business case for addressing health equity. The panelists also mention the potential for CMS and private payers to partner with organizations like ACC to further address inequities in care. The video concludes by highlighting the ongoing efforts and the potential for future collaborations and innovations in addressing health equity. No credits were mentioned in the video.
Keywords
ACC
accreditation
NCDR data sets
inequities of care
health equity
disparities
social determinants of health
gender disparities
quality improvement initiatives
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