Hi, everybody. Thank you so much for joining us today. I'm Helen Burstyn, the CEO of the Council of Medical Specialty Societies, and we're delighted to share with you this webinar today that's part of our webinar series on registry science and research. This webinar was intended to be our first one of the series on defining and creating the registries of the future. We did think so much of the registries of the future required a deep understanding of what's happening in the standard space that we had two prequel webinars, one on the U.S. CDI, U.S. CDI Plus, and then one on FHIR, which are available on our website. Today you'll hear some really interesting ways of thinking about the future of registries, how they can be used in sort of a certainly a wider way than some of our societies have primarily focused on MIPS. So this is really an opportunity to think more broadly about ways that registries can be used, particularly, I think, on the registry science and research side. So with that, I have the pleasure of turning the podium over, virtual podium, over to Kathleen Hewitt from the American Society of Hematology. Kathleen, over to you. Thank you, Helen. It's good to see you guys. I just took a quick scroll through all of the attendees, and it's nice to see so many familiar names. As Helen mentioned, I'm Kathleen Hewitt. I'm Senior Director for the ASH Research Collaborative. We have a data hub, not called a registry, but essentially it's the same thing. And also our learning community programs. And I want to thank Helen and also CMSS for taking time to put together a registry and research initiative, which the output of that is this webinar series. And this is the third one. So if you've missed any of the other two, if you go to the CMSS website, you can actually get information about the original two. So let me just go to the next slide here. And I'm going to be honest with you, this slide, it is intended to make you feel nervous, to make things feel a little bit chaotic, confusing, because that is pretty much what we're experiencing. And it's not really different, to be honest, from years ago. But what is a registry? What is it not? It's continued to change through the years. And this is just like a quick Google today and different definitions that you can get. And yes, HRQ and many of you all probably participated in creating some of the manuals about registries. And there's a very clear definition in there. But again, it's there's multiple ways in which you can look at our registry programs. Next slide. So the truth is, is that with everything, everything evolves. And thinking about cell phones, and today we have these great devices that serve as our own little mini computing tools that we stick in our pocket, and it tells us how many steps we've had and when we need to make a phone call, and we can take pictures with it. I don't know about you, but I actually had that very first phone far over on the left hand side. And I don't think it was that long ago. So the evolution of phones, the evolution of automobiles, you can think about airplanes, you can think about fashion, you can think about food, the way we eat, everything has changed drastically. And the speed at which it changes is, is only increasing too. As it relates to healthcare, there's some things that we've watched change that have an impact in some good ways and some not so good. But we don't see in general, as decreased significantly, how people are hospitalized and when. What used to be hospitalization for one to two weeks is now an outpatient procedure. We also as a society are trying to focus more on health and wellness, and not as much as the negative of everything as your negative outcome, even though we monitor those. And having mobile devices in which we can get to data, where we can get a better sense of social determinants of health. And new generations, I actually put this here. It's not so much new generations of devices, because that is as a case of new generations of drugs and biologics, gene editing, but also people, new generations, Gen Z population. I have a son who's 24. He's at the top of the, he's like the first round of Gen Zers. And even millennials, the way they look at using technology and using information to drive their health, to drive how they work. We need to be thinking and be innovative so that we can make adjustments so that none of us become irrelevant. Next slide. So taking a step back, and these are sort of the questions that should be rattling around in your head if they're not already. And there's many, many more, but knowing exactly what is the purpose of your registry program. Because 10, 15, 20 years ago, it was difficult to get your hand on healthcare data. You had to go out of your way, which is why many registries that were created back then became into existence. But today, data is everywhere. We have electronic health record systems that thanks to, unfortunately, Hurricane Maria, there was a lot of federal dollars that went into making sure that all health systems had electronic health record data. And then again, with mobile devices and laboratory data, I mean, it's everywhere. And this health information technology and how do you connect all of that? There are many standards, and the first two sessions that we had with these webinars talked about some of those new standards. And how do we embrace and utilize those standards, but also not compromise the quality of data that we need to have to be meaningful and to be able to conduct good research and to support quality improvement? And last but not least, should we invest in what we're doing now? Should we be doing operationalizing our registries differently than we are today? And if so, where should we invest? Should it be on more technology? Should it be on more services to those that are submitting data to your programs? Should it be in bringing in different stakeholders? The answer is probably a little bit of yes across the board. Next slide. So thinking about why we're here today, the whole point is to be innovative and think about the next generation and recognizing that there are new federal standards that are being released, have been, and continue to be, and how do we leverage them? And again, taking advantage of getting access to, if you don't already, to patient-reported outcomes and patient-generated data and making it simple for our patients to be able to contribute that information. It used to be that many of our programs, not all, you had committees and a governance structure where it was all of your members making very important decisions, and many of them have been successful, especially if you have been able to accomplish a lot with your program. But that is not a process that's going to work going forward. With implementation science, and we've learned so much, having multiple stakeholders with many different viewpoints be involved to advise and to help to determine what the strategy and the next steps and the priorities are for your program is going to be a critical element. Data quality goes without saying. Data is data, but if it's not high quality and you can't say that it's representing your patient population, then essentially it's useless. And last but not least is sustainability, and I don't know about you, but there have been lots of sessions that have talked about sustainability for registries, and the reality is that the recipe for sustainability is as unique as your organization, and it changes as the value drivers for why you would want to have a registry and why others need you to be in the position that you are in providing data to create information. Next slide. So it's time to stop and reassess. Who are you? What are you trying to accomplish? And what is your next step going to be for your clinical registry programs? So next slide. This is why I have the honor of sharing today's session with you, with these expert leaders, my co-moderator, Dr. Danica Marinak-DeBeek. She will be sharing a scenario called a coordinated registry network. Some of you are well aware of it because you've been actively involved with coordinated registry networks and perhaps even one that the FDA has been involved with, but it's not only unique and specific to the FDA. Dr. Bill Wood will then follow, and he will present how a new registry program, not even called a registry, called a data hub, is designing itself in light of all of the current technologies and access to data that exists today and didn't exist 10, 15, 20 years ago. And then Dr. Philip Goodney, he will share about his program, which is the Vascular Quality Initiative Vision Coordinated Registry Network. And his program has been around and is quite seasoned, and he can share how the work that they've done has evolved and how it's supporting their program, and most importantly, how it's helping their patients. And last, and certainly not least, joining us for our panel discussion will be Dr. Art Sudrekian, and he comes from Cornell, but Art has also led a lot of the coordinated registry network projects and works with almost all national registries and thinking about how they can be designed so that you can have a whole ecosystem of different data sources coming together and making that data available to support regulated research, investigator-led research, and other purposes as well. So with that, it's my pleasure to turn it over to Dr. Marinak Dabik to share with us about the work that she's been overseeing with Coordinated Registry Networks. Thank you. Thank you, Kathleen, and thank you, CMSS, for putting together this wonderful series. So I would like to bring you today the concept of Coordinated Registry Networks. Before I dive deeper into the definition of CRN and, you know, the way how we as an ecosystem part of this, I'd like you to think about CRN not as a particular entity, but rather as a concept, rather as a framework to consider all different types of health data aggregates and provide models that may help those enterprises expand their utility. And primarily, I would like to focus discussion on the registries as a part of the CRN data sources, but CRNs include not only registries, data networks, networks of registries, data hubs, some of the platforms that are evolving into platform trials, and many other types of aggregation of the interoperable data sources. Next slide. So why is it FDA was interested in the concept of the CRN? Because we all need curated, fit-for-purpose, interoperable, real-world, longitudinal data, in particular in the device space, let's say implantables. We really care deeply about how the patients and how devices actually perform in the long-term setting. For regulatory decision-making, for public health, we need that type of data. But for us at the FDA to travel to a journey from one-off FDA-mandated studies to a concept that strategically align variety of real-world data sources, and to be even thinking about registry-embedded studies, obviously it took years and I would say more than a decade to do so. Next slide. I mean, next click. So a couple of clicks. This is sort of a summary of my talk today, a couple of more clicks. So there had been a decade of really very active role of Centers for Devices and Radiological Health in exploring how registries can be elevated to regulatory grades of evidence that you can make decision-making. And obviously from that idea back in early 2010 to now in the space where we are seeing the learning community of CRNs blossoming in 13 clinical areas to recently develop maturity model framework, which is about to be published. It's accepted for publication in British Medical Journal. To actually providing an example of the most mature CRN that we have in our national scene today called VISION. We are going to hear today from Phil Goodney. But I just wanted sort of to establish this before we actually take a deeper dive in the definition of CRN. Next slide. So not going to walk through the entire slide, but year 2015 was particularly important because this is the year where the National Expert Working Group called National Medical Device Registry Task Force was convened to explore the role of registries in the ecosystem. And what can be done in particular from an angle of looking into interventional care, medical technologies, devices, and an ability to actually be contributing to evolving national evaluation system. The landmark report was issued in 2015. Next slide. And which coined the concept of coordinated registry networks. As part of this expert working group, there were folks like Rob Brindis, you know, a thought leader in the cardiac space. Many folks that you know in the area of, you know, orthopedics such as Lise Paxton, leads of other registries. So it was really not, there was only one member from FDA. So it really was ecosystem driven effort from professional societies, from industry, patients, representatives, and many other sector members from the ecosystem. So again, as I mentioned, the key concepts of CRNs were that it's embedded in routine practice. This was not to be afterthought and let's analyze the data that are collected. It was something that we want to be really building on efforts of you as registry leaders to actually leverage. Then we brought this concept of strategic coordination. Again, trying to think about interoperability, how we can link data sources with each other. And then talking about the networks. We coined this word around the registries, but again, other efforts such as data hubs and other networks can be actually included because not for every single question we have registries established. So in today's technology space, we can actually create those virtual registries around the questions that needed to be addressed and actually being able to keep that knowledge in the ecosystem portfolio. And then obviously thinking about national and international opportunities. Next slide. So I will offer a definition. That doesn't mean it's a final and it's not subject for change, but it's a really about real world data sources encompassing strategically partnering electronic health information systems that serve one or more clinical areas, orthopedics, vascular, cardiac, you name it. So it is really about building on the national, regional, or even international registries, strategically harmonizing data and creating the core minimum data sets that will serve a particular clinical space. And to be able to link them to complementary comparable data across the systems, including EHR, including administrative claims data, including patient generated health data. Some of the complementary clinical conditions can be harmonized into the family of CRNs and women's health CRN is a good example of that. And also even completely diverse set of clinical settings can actually join the learning community of CRNs. This is something that we actually piloted in the device space, but we don't own it. We don't run it. We don't really want to claim that this is created for FDA. This was ecosystem driven. Next slide. I will skip that. This is just for your reference, the copy of the national medical device recommendations for the NAST from that particular expert group of registries, experts, and accompanied JAMA viewpoint that boils down why registries were so promising for the foundational work in the national system for health technology. Next slide. So at the same time, I'd like to say that there have been a lot of international efforts in the standard space and the regulatory space to come up with a new definition of the registry, which was viewed as being an organized system, again, with the primary aim to increase the knowledge on medical devices contributed to improve the quality of patient's care and that continuously collect relevant data, evaluate meaningful outcomes and comprehensively covers the population defined by the exposure to this particular device at a reasonable generalizable scale. So if you sort of erase from here medical devices, the high points here are organized system, improving the quality of patient care, collecting relevant data, evaluating meaningful outcomes, comprehensively cover population. So all these things really go way beyond the device space. Next slide. So what the FDA had done with that recommendation from this expert national group about the value of registries, we've then partnered with the Office of Secretary, Assistant Secretary for Planning and Evaluation, who actually funded these two major grants to try building the CRNs across multiple clinical areas. And you see these two major grants here, and I'm going to present some of the findings and some of the deliverables just to get us discussing and other panelists will actually pick up on those as well because there have been a lot of collaborations across the system. So next slide. So what we've done first as part of this grant, we convened the multi-stakeholder group of experts and built in a formal Delphi process with over 35 organizations. Many of your organizations and your registries participated in the Delphi survey. And these are the seven maturity domains for the CRNs that we felt are important. And those are for registries and CRM. So let's not start with UDI because I don't want to turn your enthusiasm off just by focusing on devices. Let's talk about data collection efficiency. What this actually means, structured data capture, mobile apps, automation with interoperability solution. That was the vision that we had for the registries of the future. Number two is data quality, which has subdomains of coverage, completeness of enrollment and records, both at baseline and follow-up. And also periodic audits. This is what we sort of insisted on the FDA side that this is really important if we're gonna be making decisions in regulatory setting based on the data coming from these registries. Then what about total product life cycle? This was really meant to highlight that there is no boundary between pre-market and post-market. It's continuum of evidence. And we wanted to make sure that the registries are equipped with the tools to study performance of technologies and other performances, obviously including the clinical performances across the entirety of the evidence generation cycle. Then Kathleen mentioned governance and sustainability. The engagement of major stakeholders, societies, payers, various states working together. It's something that we felt it was really important to be one of the key domains. Healthcare improvement. Again, it's about really continuing an evaluation, feedback, benchmarking, outlier assessments and such. Engagement of patients. We insisted on patients actually joining the boards of those CRNs and being part of the steering committees. And finally, the precise identification of medical devices and their attributes. So that's something that we wanted to have regardless if we are in the device space or if you are a clinician, you want to know which technology performs better than others and that will drive your choices for moving forward with your practices. So we wanted to make sure that that's also embedded and we developed this non-punitive, really very collaborative, camaraderie way of assessing the quality of these registries. And have these levels of early learners through a making progress, defining path to success, well-managed registries, optimized registries, which gives you a little bit of a flavor of how we wanted to actually evaluate them. We then went and have worked with registries to self-evaluate them according to this and put together as a team sort of recommending how the registries can move in the level of maturity. And there are many registries that are still at the level one and there are some registries that are level four and five. So next slide. So this is sort of the concept of that maturity of the registries. And as you can see in the level one, let's say if we use just data collection efficiency domain. In level one, we have a situation that it's a heavy burden with ad hoc data elements and a project basis without really development of the clinically relevant, meaningful core data elements, all the way to the optimized level, level five, when technologies are in place for structured data capture, extraction from EHR, core minimum data elements, full adoption of interoperability standards and all that. Next slide. So I'm not gonna spend too much time, but I like to brag about the successes of vision in vascular space. And I just wanted to give you the snapshot of what is the difference between the registry as a registry versus the CRN as this ecosystem driven encompassing multiple data sources. So here you'll see VQI, that here is gonna talk about SVS registries, is a registry that had been established and had these already successes in many ways. But what the CRN effort brought to this is link the registry data to claims data with 15 years of follow-up achieved from 2002 to 2019 on close to half a million patients in the registry with 14,000 patients captured in the current validation efforts. So nothing is done really, let's, you know, in a space, let's link those without validation. We actually, when I say we, this is Phil, Rodney, and the team, and Art Sadrachian really working together on these efforts. So Phil is gonna talk more about this, but linking to SPARKS, New York, Oshkosh, California, some of the PCORI CRNs, mobile apps, complete linkage to Medicare data, and then also to some clinical trials data. That brings you that fabric of registry being in the core, but then everything else is really filling into the places and make the complete picture. Next slide. So again, this is the group, this is the learning community, which gathered together to learn from each other with the cross-pollination areas of clinical efforts, data science, epidemiology, statistics, sort of working together and develop together 16 tools that are shared and applied in harmonizing the efforts, validation, return on investment analysis, mobile apps. So again, these are very disparate data sources, but it's not surprising, for example, that Ben Perlos, who leads the abdominal hernia registry, pops in the field goodness steering committee meeting for the vision to see what's happening in the vascular space so they can learn and apply in the abdominal hernia. So next slide. Can we go next slide? They just lost everybody. I think Danica's connection might've just... Can you hear me now? Yes, we can hear you. Yes, and in the interest of time, I'm going to just conclude and Art will have a chance to actually talk about a lot of points from his presentation, but in the sort of moderated discussion later. Oops, I'm on mute. So I wanted to say that there are pragmatic advantages and efficiencies to be gained by thinking about the registries in the context of these coordinated efforts. These existing systems really minimize the re-engineering, meaning cost of implementation and leverage, established clinical core minimum data sets, established governance and sustainability. And also they are very strategic in terms of the flexibility in the design, accommodated emerging electronic system, as Kathleen was talking about, customizable across devices and looking into different aspects of diversity of the healthcare and access and equity and all of that. So, and as far as also building architecture that's consistent with the structure of data sets and also ability to use artificial intelligence and machine learning and all the other knowledge technologies. Next slide. And this is going to be my concluding slide that was designed to show that we are far beyond dreaming about this. These CRMs are already producing the regulatory grade evidence, and which is, as you know, very high in this country. There have been FDA published 90 examples in which real-world evidence was used in medical clinical trials. And most of them are coming from registries, so nobody's surprised. We've done a series of return on investment studies in which we've demonstrated, two of those are listed on a slide, that if industry uses the registries, your registries, for the regulatory decision-making and embed their studies, they can actually achieve up to 550% of return on investment in some instance. And this is a very, very high level of return on investment in some instances, and then obviously in other areas will be a little bit different. But the point being is that there is a hope that these business models can be actually centered around this value proposition for these coordinated efforts that bring beyond what registries currently collect. And this is just some examples. Again, we don't own the CRMs. CRMs are not designed for FDA. CRMs are to be viewed as a value and a jewel and the treasure of the entire ecosystem. And today's discussion, I hope, with Art joining the panel, we'll be able actually also to provide some specific examples about how that can potentially be done moving forward. Back to Kathleen. That's great. Yeah, thank you, Danica. That was an excellent overview. And I think now we're gonna go to Dr. Bill Wood, so you can advance slides to Dr. Woods. Thank you. So Dr. Bill Wood is my partner in crime here at the ASH Research Collaborative. He is, during the day, he pretends that he's a hematology oncologist. He's actually on service, so we appreciate you making time out of your day to be here with us. And he also is chair of the ASH Research Collaborative Data Hub Oversight Group. And I'll mention that he's a bone marrow transplant specialist. One of the benefits of having registries that are run through organizations like ours is we really get to work with the finest experts across the country and certainly across the globe. Something that would be very difficult to afford if you're not working with a member volunteer. So with that, I'll hand it over to you, Dr. Wood. Thanks, Dr. Hewitt, for your kind introduction. And thank you for your opening comments and Dr. Marinak-Dubik. I really appreciate that. And what I took in listening to what both of you said at the beginning was about how the healthcare data ecosystem is evolving rapidly, how registries, as we traditionally thought about them, are becoming something much different as part of that evolution and how the CRN framework can help provide one way to think about what the registries of the future may well look like. And so what I'd like to talk about today is the ASH, American Society of Hematology Research Collaborative Data Hub, as one such example to illustrate these points that were brought up. It's interesting, Dr. Hewitt alluded to this at the beginning that we don't call ourselves a registry, actually. In fact, we did for a period of time, a brief period of time, and then ourselves adopted this term data hub in large part because we were recognizing that we were moving towards this model of a registry of the future. I also just wanted to highlight briefly that in Dr. Marinak-Dubik's comments, I think that we saw this wonderful ecosystem of a number of largely device-based groups that have developed their own CRNs underneath this overall framework. And we are coming to this group now through the ASH Research Collaborative. We are not primarily a device-based group. We work in different hematologic conditions. And I hope that we can provide an example of how a professional society can move towards a registry of the future, aligned with these wonderful examples of CRNs as Dr. Marinak-Dubik had just described. So again, my role is as a senior medical advisor to the ASH Research Collaborative and as a chair of the ASHRC Data Hub Oversight Group. And I'm pleased to share with you a few thoughts about what we're doing now to illustrate a couple of these key points. Next slide, please. The purpose of our data hub is to capture real-world data to generate real-world evidence for hematology. And the way in which we do that is that we actually focus on specific hematologic diseases. We've started our work in sickle cell disease and multiple myeloma. And within each disease area, we gather together networks of sites that participate by sending patient-level data to help to inform both research and collaborative clinical practice improvement within these disease areas. And as we do that, we again develop a community of stakeholders, as was described within the CRN framework. We have a few main sources of data that we're working with right now. One of those sources of data, as I'll talk with you more about in a minute, comes from direct electronic health record data feeds, structured and in some cases unstructured data, depending on the level of consent that's been provided by participants. We also obtain information from directly filled out electronic case report forms that we essentially verify or curate at the site level with the benefit of pre-populated data from electronic health records. We also have the ability to map local curated registry data that sites might have. We work with some of the largest academic medical centers, seeing patients with hematologic conditions in the country, many of whom already have had some existing efforts that we can actually map into our overall data hub structure and then fill in the gaps that we need to complete our data model as needed. On top of that, we actually engage with our patients quite a bit. We have community advisory boards. We have the ability to develop prospective nested sub-studies which include the collection of patient-reported outcomes and patient-generated health data. And then within this broader multi-stakeholder environment, we're able to purpose this data hub in several different ways. Again, under the overall headings of research and collaborative clinical practice improvement, we can develop certain structures like a learning community that Dr. Hewitt earlier alluded to in which we can bring different sites together and patients and families and other stakeholders across the policy regulatory and scientific landscape to work together towards shared common goals and different hematologic conditions. And in doing that, we can develop data that are fit for purpose for regulatory and other uses. Next slide, please. I'd like to say just a few words about how we bring in our EHR data. I referenced the local curated registry data that we can map to our existing structure, which we do by flat file export. We also have the ability to bring in EHR data through direct feeds. We have been utilizing either OMOP common data models or FHIR-based data transmission. As you all know well, and again, registries of the future under the CRN framework and other frameworks are looking to leverage the newest technology data transmission standards as enabled by the 21st Century Cures Act, including now the ability to use EHR FHIR APIs. We actually have a number of sites that are choosing that pathway, and we anticipate that more and more sites will be using that pathway as we go forward. As data come into our data hub, we are able to develop pre-populated electronic case report forms, and we do that through the development of digital phenotypes, which I'll say more about in just a moment. Ultimately, those case report forms, where needed, can become the source of truth, and they are verified or amended at the site level as needed, and then essentially finalized for inclusion within the data hub. Next slide, please. So again, in this broader context of registries of the future, we intend to remain closely aligned with all of the important stakeholders throughout the health data landscape, including our colleagues and friends at the FDA. As we're thinking about what we're calling our data quality program, we're very intentionally closely aligned with the emerging data quality standards that FDA has described in several guidance documents, as well as in ongoing programs to provide structure for real-world data transmission from sponsors and technology groups. And these are some of the headings under our data quality program that we're extremely focused on that we use to structure our own data quality framework, including accuracy, completeness, conformance, plausibility, reproducibility, and provenance. And thankfully, these are terms that many on this call are familiar with. FDA guidance documents provide a lot of additional detail to help explain what these mean in the regulatory context today. Next slide, please. When we're able to develop our data quality program in that way, we feel that we are developing a data hub that's fit for use for FDA-regulated research. And what does that mean? Here are some of the use cases that we anticipate that we'll be working with our investigators and sponsors with and coming to the FDA in the future for as well, including the ability to enhance and facilitate clinical trials through the development of external control arms, development of observational studies to support efficacy, information that can help us to understand safety and toxicity data over time, including the use of fulfillment of post-marketing requirements and commitments years into the future. Next slide, please. A word about digital phenotyping or what we call e-phenotyping. There are lots of terms that refer to this concept that are out in the literature. But in short, our intent is that we're able to actually leverage both structured and unstructured EHR data. We're doing that now. And we can use that information in either rule-based or model-based ways where the intent is to model an underlying health concept. We develop an operational definition based on our best first approximation of that health concept. We're able to test it. Like any clinical test, we have test characteristics associated with that, sensitivity, specificity, positive predictive value, and so forth. We have thresholds that we use to determine whether or not a provisional operational definition can pass that test and or whether it needs additional site-level adjudication and verification to meet the threshold that we feel is needed for an accurate and high-quality data element. E-phenotyping is an iterative process. We know that our first attempt out of the box for a various type of clinical concept may or may not hit the mark. We go back, we develop a new operational definition, we test again, and we keep going until we get to the limits of the ability that we're able to abstract from structured and, in some cases, unstructured data. Moving forward, we'll have the ability with the data that we collect to apply the newest machine learning and artificial intelligence techniques to make our test characteristics even stronger. Next slide, please. As these data come in, we're able to then repurpose them in various ways. And a critical component of our data hub is the ability to return value directly back to stakeholders, including our site clinicians and investigators and others who can actually look at data in real time through dashboards that we've constructed to help them monitor their patient populations for a variety of different reasons. Could be for operational purposes, could be for, again, collaborative clinical practice improvement. It could be for hypothesis generation to inform the development of research studies. This is an example here within our sickle cell disease program. And as you can see, if we're interested, for example, as we are in our learning community, to increase a reliable use of disease-modifying therapies for individuals affected by sickle cell disease, then we need to see what disease-modifying therapy use looks like at the site level and across sites, and this is what these figures represent here. And we have a variety of different figures that we've developed for all of the different metrics that we curate and include within our dashboards that are disease-specific, available to sites, and in some cases, available to stakeholders through custom-built dashboards as well. Next slide, please. We also then will roll up these data into summary metrics that are available, and this allows us an opportunity to look at change over time in a tabular format, and this also feeds into our ability to provide real-time data quality reports back to sites so they can understand data characteristics of their patient population. Next slide, please. We have similar dashboards that we've developed for our multiple myeloma program, and here I think, again, is an illustration that our data hub leverages different types of data from different sources to, again, best represent underlying health concepts. Structured data alone are very challenging to use to model important outcomes relevant to multiple myeloma practice and research. This is an instance in which some of our electronic case report form data can be used as a gold standard while we're working to develop ever more complex underlying digital phenotypes. And then we, again, use those data, bring them back to the dashboard at the site level and stakeholder portal level as well. Next slide, please. I'd reference that these data are basically rolled up and compiled into data quality reports. This is an easy kind of at-a-glance way for, again, sites to ensure that their data transmission is going as they think it is. And then underneath, we have a more sophisticated and fully developed data quality program that is constantly testing the data that we're obtaining from different sites to ensure it's accurate and fit for purpose. Next slide, please. Just a brief word about one of the potential applications of this work. I referenced earlier that underneath the umbrella of clinical practice improvement is the ability to actually develop certain programs. We've been fortunate to be supported by Office of Minority Health and the Department of Health and Human Services to develop a nationwide sickle cell disease learning community. That learning community so far has been built at the pilot level. With over 10 participating sites, we actually have an in-person meeting for our learning community participating sites coming up just next week. And this is powered by the Data Hub. And that's really the key point here. This is a Data Hub that can directly influence our ability to improve practice at scale. In this case, the reliable use of disease-modifying therapies in sickle cell disease and the reliable use of co-developed pain management plans. Next slide, please. I mentioned our collaboration with the HHS Office of Minority Health. We also have ongoing work that we're doing with NHLBI and FDA. Again, this is consistent with the principles that Dr. Marinak-Dubik mentioned for coordinated registry networks. We're working with stakeholders across the entire data collection ecosystem and regulatory landscape so that the insights that we can generate from this broad network can be brought to bear to improve policy, research, and clinical practice. Next slide, please. I'll wrap up here towards the end with a nod to a real-world evidence initiative that we have led with our colleagues and friends from the Innovative Genomics Institute with participation from the FDA. We've been so pleased to have Dr. Marinak-Dubik, Dr. Sedraki, and others who are on this call contribute their expertise and insights to this project as well. Essentially, we have been looking at the overall use case of genome editing therapies in sickle cell disease to think about how we can actually use our sickle cell disease program to move towards that registry in the future, specifically looking at not only recommendations for genome editing therapy data elements that are fit for purpose, but also how our overall data collection strategy can become more and more closely aligned with a coordinated registry network concept. Next slide, please. More specifically around our coordinated registry network concept, we had a working group with multiple collaborators. We had over 100 participants at one point, again, across the landscape of policymakers, scientists, clinicians, representatives from other groups, patients, families, and many others. Our recommendations for our CRN workgroup came down to four main topic areas, data fit for use, data access and use, data sources, including patient experience data, PROs, BGHD, and otherwise, and a sustainability value proposition. Again, very consistent with overall CRN principles. Next slide, please. In fact, those recommendations have recently been made available for public comment. We're looking forward to getting feedback within the next couple of weeks. We welcome thoughts, feedback, and comment from those who are interested in this particular project. This may be a real-life example of how a society registry is moving towards a registry of the future in the CRN framework, and we look forward to your ongoing participation in our effort. Next slide, please. So I'm going to stop here. I want to thank you for your time and attention, and I look forward to the opportunity to answer some questions as far as the panel. That's fantastic. Thank you, Dr. Wood. We appreciate your overview, and it's interesting to see how a newer program is coming out of the gate and trying to address all the elements and consideration as being part of a clinical registry network, a coordinated registry network. Okay, so now let's transition to another program, and this being with the Vascular Quality Initiative, their vision-coordinated registry network. And Dr. Phil Goodney has joined us. He's a vascular surgeon. He's a health services researcher and also is chair of the Vascular Quality Initiative and the Vision CRN. And we look forward to hearing the work that you guys have done as you've had many years under your belt and I think are featured in many papers with the work that you've done as well as how it has helped to move forward several FDA decisions. So, Dr. Goodney, thank you. Thank you very much for the invitation and the chance to be here today. I'll be speaking as well as my research director, Kayla Moore, who's been a critical contributor to much of our efforts over the years. And I want to make sure I acknowledge the support that Dr. Marinak-Dabic and MDF-UNIT have provided us over time, both in terms of helping us build our infrastructure as well as guidance and advice about how to try to have impact and sustainability over time. So thank you very much for the invitation to be here today. I'll be a little expeditious. I very much enjoyed Dr. Wood's presentation and enjoyed hearing about their infrastructure and I'll show you ours. It'll be a little slightly different and I hope some complementary ways. So next slide, please. We've been fortunate to have support from FDA and NHLBI and PCORI and the American Heart Association and projects related to this. One of the nice things about hybridized data sources is they have a lot of applicability. And fortunately, we've had some success in grant funding to try to sustain these efforts as we've created these data sources over time and tried to apply their use in a myriad of ways. And I'll highlight one of the recent ways that we've tried to use this data for impacting regulatory decision making. Next slide, please. This is also just a slide to show that I'm presenting this information on behalf of our steering committee. We, you know, Art Cedrakian encouraged me many years ago to form a steering committee so that our decisions would have traction within our professional society and would extend their impact beyond just one individual's research group. And that was SAGE advice. And as our work has grown and blossomed over time, having a steering committee to look at our data from a lot of different perspectives and similarly provide recommendations from several different lenses has been a key component I think that we've contributed. There are many people listed here on our steering committee. It has not just academic surgeons or cardiologists or interventional radiologists, but also stakeholders from industry and regulatory areas as well. Next slide, please. Our goals for the next few minutes, just very briefly, I'll outline what the VQI Vision Coordinated Registry Network is and then share some key findings that we've contributed in recent years. And Kayla will go over some of our key infrastructure about how we collect and analyze our data. And then finally just describe what's next on our to-do list, if you will. So next slide, please. Sorry, next slide after this one. So what the Vascular Implant Surveillance and Interventional Outcomes Network, or the VQI Vision, is a coordinated registry network. And this is a publication that we had in the Journal of Vascular Surgery back in 2020 where it essentially just described the infrastructure and the pieces that are involved in the generation of this particular type of evidence and what the particular type of evidence might be good for. We wanted to summarize that as the evidence began to be democratized, if you will, as we made it available within those interested in our specialty to try to answer clinical questions and also even try to apply to regulatory decision making. Next slide, please. How our data is generated, it's pretty simple. It starts with registry that's collected from the Vascular Quality Initiative, or the VQI. That's our professional society in vascular surgery and the quality improvement initiative that goes along with it. In the VQI, we collect a myriad of clinical details about the procedures we do. So how old the patient was, why they needed the operation, how we did the operation, the technical details that surgeons love to talk about at conferences and things like that, and the clinical factors that make it likely or less likely that the patient may or may not have success or durability after the procedure. We then take that sort of rich clinical detail and then marry that clinical detail to the patient's Medicare claims records. And what's nice about Medicare claims is, of course, it tends to follow the patient usually for the rest of their life. And fortunately, in our specialty, most patients that have vascular procedures tend to be over the age of 65, so they qualify for Medicare. And then after they have their operation, it's always tough to keep track of patients because, you know, you might have your operation with me at Dartmouth-Hitchcock Medical Center in New Hampshire, but then you might go to Florida for the summer or you might decide to move to Arizona. And if your device that I put in you has trouble over time, I might never hear about it. But if the bills that are involved in fixing and maintaining and surveilling that device over time, if those bills all go to a central payer, then now all of a sudden we have a mechanism where we can establish not exactly every clinical detail, but we can measure with some validity four very important outcomes. How long the person lived after the procedure, whether or not the procedure prevented whatever it was supposed to prevent from happening. So, for example, if we implanted an endovascular aortic aneurysm prosthesis, do we keep the aneurysm from rupturing? Was there a long-term device failure or the need for a revision? So if another operation gets done again, whether it's by my team at Dartmouth or by somebody else's team somewhere else, the bills all flow to the same place and that allows us to centrally monitor what's happening with that patient's device. And then finally, since this is a payment mechanism, we can even study costs that are associated with both the procedure itself, as well as the surveillance that goes on over time as well. Next slide, please. We started doing this work in 2012 and have had some success in the ability to accurately measure long-term post-operative surgical outcomes, and namely the things that seem to have the most traction are long-term survival, the need for revisional surgery or re-interventions, and the need for further procedures that might be related to the problem that we've been treating. So really the durability and the effectiveness of our operations, it turns out, are important outcomes that we've been able to measure somewhat uniquely with our hybridized data sources. Next slide, please. We've been fortunate to publish those procedures in journals like the New England Journal of Medicine, Circulation, and Annals of Surgery, and they largely have focused on the long-term, you can see the survival curve shown in the figure in the panel on the right, in the long-term durability of the way that we treat patients with vascular disease, especially as it's related to the durability of their devices. Next slide, please. Those particular devices are studied within the context of our national quality initiative, and this is a website for the SVS, VQI, or the Vascular Quality Initiative. In partnership with many in industry, we are asked to consider how differential performance might affect different devices. Next slide, please. Sorry, this is our website if anybody's interested in downloading those papers that we just talked about. Next slide, please. And a key issue that's arisen with one of the endovascular treatments that we tend to study is what happens in terms of the need for late reinterventions after endovascular aortic aneurysm repair, or EVAR, because it turned out these devices that were supposed to last for the rest of the patient's life and keep the patient free from aneurysm rupture, it seemed like in real-world practice that wasn't necessarily the case. Next slide, please. And what came to light was that one type of device seemed to be failing more commonly than others, but those failures were happening well after the window that had been reported in the FDA studies that were submitted and approved to allow the device to be used in practice. So now we had evidence from real-world registries linked to claims that seemed to provide a unique window into when device performance may or may not be optimal. We were asked to provide some of this evidence during a FDA review panel that was held in November of 2021, held by the Circulatory Systems Devices Panel, to really talk about what the real-world surveillance of abdominal aortic endovascular stent grafts looks like, and we are pleased to share some of the data that I'll show next. Next slide, please. What this data showed was that certain typical devices, and this is work that's currently in press at the British Medical Journal, was there were certain devices that tended to have higher rates of failure. On the x-axis here is time, and on the y-axis is the failure rate of the device and the need for reintervention. And you can see that line shown in brown was one device that many clinically had had inklings, you know, needed to be fixed more often than the other devices, and it turned out that in real-world practice that signal persisted well after four or five years, which had been reported in some of the early studies, but the gap widened as it went out to six, seven, or eight years, to the point that this prompted reconsideration and revision of some of the decision-making around the use of that particular device. So really, this highlighted where a unique resource, this real-world evidence, could contribute towards regulatory decision-making for this individual device. Next slide, please. We modeled how many years it would take for our system, if you will, our electronic watchtower, to detect when the device may or may not have failed if we had started following it from the beginning. And that signal detection tended to happen earlier in using our electronic data sources because of the sample size involved as compared to when it was reported in 2017. You can see here the arrow shows that by 2014, we had began to see in our electronic system, using lab-linked claims data, we began to see evidence of failure. The FDA didn't see it with their data collection mechanisms that are basically physician reporting of individual events. That wasn't reported until late 2017. And that could prompt secondary data element collection, like further collection of imaging and chart review, to better understand why these devices may not perform as expected. Next slide, please. How are we going to curate this evidence? This obviously involves data from Medicare, data from individual registries, data from companies. And making sure we collate that information carefully and with attention to appropriate data use agreements is how we spend a considerable amount of time. And I'll ask Mrs. Moore to comment, because she leads many of these efforts for us, about how we assimilate this evidence and what steps we take to try to make sure we do it in an appropriate manner. So, Kayla? Thanks, Dr. Goodney. Next slide. So over time, we've worked very hard to balance what we think of as two opposing forces. Obviously, there's the expectation in our community that this data is a community resource. And on the other hand, there's also the expectation of data security when it comes to PHI and PII. So I'm going to take just a few minutes to talk briefly about that. Next slide, please. So VISION is very much a community resource. Our community is dedicated to the principles of transparency. And like VQI, we believe the data sets should be made widely available. And the evidence that we generate should be made available for purposes of research and quality improvement and vascular care. All of our participating sites that put data into the registry have an expectation that they can get that aggregate de-identified data back for their own research purposes. There is a process in place at the VQI for approving projects, ensuring scientific merit. Those projects are reviewed by a research advisory council prior to dissemination of the blinded data sets. On the other hand, because VISION links the VQI data to Medicare claims, we can't actually release just a regular blinded data set. We have to abide by the rules governing the use of CMS data. Those rules require that the data may be maintained on a secure HIPAA and BISMA compliant server, and it restricts access to only those individuals named on the DUA. So as you can imagine, with over 600 participating sites, we can't make that data available to all centers or all participants. So I'm gonna talk briefly about the way we balance those two things. Next slide, please. We have a process in place for use of the VQI VISION data. It goes first through the regular VQI RAC approval process where the projects are reviewed by the research advisory committee. Once that takes place, then we have a secondary screening by the VISION priorities committee, which ensures there's clarability and feasibility of the research questions so that the data that we have is appropriate to answer the question, that there's a clear need for the Medicare data specifically for long-term outcomes, that the research question can't just be answered using the short-term outcomes in the regular VQI data alone. And lastly, we have to ensure that the project falls within the scope of the DUA. CMS DUAs are project specific, and so they do have to fit within a well-defined scope. Once a project has passed those, has met those criteria, we will reach out to the investigator to invite them to submit a detailed research memo, and we'll go over that with them to refine their analytic plan. And then our analytic team works behind the firewall to conduct the analyses on their behalf, and we'll share aggregate tables and figures for dissemination in papers and reports. And as Bill mentioned, we do have a website where folks can learn more about this process, and also read key publications, including some important validation papers, and explain how the linkages are done using both direct and probabilistic matching methods. And I'll turn it back over to Dr. Goodney. Thanks. Great. Thank you, Ms. Moore. So what Kayla described is essentially democratization of our resource here. One of the key things that we think has helped us be successful is buy-in in our community, and trying to broaden access to the data as best we can. And so that's why we built that infrastructure. In terms of what's next, how we hope to continue to leverage these resources is, instead of trying to do post-hoc evaluations of how well the devices are working, we want to do this in a prospective manner, and create what we call the LEAF, or Long-Term Endovascular Aneurysm Surveillance and Follow-Up Systems, which essentially will be device dashboards that we can supply both to industry and to regulatory partners. And we think these can serve as a near real-time signal detection systems for problems that might arise with these graphs. And we have other examples outside of aneurysm repair, which we could apply a similar methodology. There would be a key advantage here, that these similar outcomes would be measured and reported similarly across devices, which would ease comparison, interpretation, and benchmarking. And a multi-stakeholder steering committee would help to look over the output from these analyses and decide what steps might be prompted next. Next paragraph, or next slide, please. This is sort of a chart that shows our processes that are in place for trying to develop these. We've worked with stakeholders in industry and CMS, and in our professional society, to try to put this collaborative together over this last year-long process. And we're hopeful that by the end of the year, this real-time sort of signal detection system should be up and running. And I want to express my appreciation to Danica and many others at FDA for helping us to push this process along. Next slide, please. These, of course, does not happen in isolation. Our initiative in our professional society, as well as other large national payers like Kaiser, as well as our industry teams, have all had collective efforts in pulling on the oars here to try to move these projects along in terms of defining the outcomes, harmonizing data elements, drafting our reports, and sharing data gathering and data governance planning mechanisms, as you can see in the slide here. Next slide, please. Our reports, we had something to model them on. We already provide feedback reports to our individual sites, much like the feedback reports that Dr. Wood showed. So instead of just providing feedback to our participating sites, we now provide feedback to our partners in industry who manufacture the devices. Next slide, please. So in closing, and I appreciate the opportunity to share some of our work, it's been a pleasure, of course, to be a part of a longstanding effort here to learn about long-term device performance using our linked registry datasets. And it's been my pleasure also to share some of our key findings about trying to find when devices might not perform well using real-world evidence, and linkages to registries are a key contributor to that ability. And finally, what's next for us is we hope that it will be industry partnerships and reporting for sustainability and impact. And with that, I'll close, and thank you for your attention, and thank you, FDA and others, for supporting our effort. Thank you. Thank you to all the speakers. Excellent presentations. We are going to be now moving to the moderated discussion, and hopefully we're leaving some of the time also for the folks that asked the questions via question-and-answer chat box to actually be participating with their questions as well. So I would like to start asking question of Dr. Sudrakan since he did not have a chance to actually give his presentation. I wanted to ask him about how you see the value that CRM concept provides for registries, for clinicians, for other stakeholders, sort of speak about the experience generated over the past decade or so. And then we're going to go with one question to each of the panelists, and then we're going to try to actually cover a lot of territory in the remainder of the 25 minutes or so. Sure. Thank you. Again, I apologize for joining late. Some emergencies that I couldn't avoid today. I'm happy to join late and comment and share some thoughts related to CRM benefits for registries. As Dr. Goodney highlighted, the Vision Coordinated Registry Network showcased the major strength of CRM model in terms of data linkages. For us to leverage all real-world data and the ability to bring that together and create that infrastructure that can host that information and enable partnerships, enable working with external collaborators, with regulators, is a huge, huge achievement. And I think that's something that most registries should consider. Most registries are at the stage of maturity that allows them to bring additional data in, because, of course, there's resource requirements, there's data quality requirements. There are many considerations before this can be initiated. So I think that is number one and really major way CRM can strengthen the registry. The second issue I just wanted to highlight, and Greg Pappas asked this question, whether everything can be interoperable. It depends on the context. So a difference between Bill Wood's presentation and Phil Goodney's presentation is essentially in an interventional care versus non-interventional care context. When we have medications or products that can be injected but do not require a surgery or an implantation, I think interoperability becomes way more important because a lot can be achieved by leveraging data sources and creating the data hub in a way that Bill presented. But when we have to deal with the context like Dr. Goodney's presenting, there's surgical details. A lot is happening in operating room that is just impossible to make interoperable with anything. We need to work with the folks who are implanting these products and have simple and friendly solutions for them to be participants in a registry and CRM. We can't avoid having those friendly mobile apps and ability for patients later on to interact with physicians. These are key issues that I think are related to the way registries are set up, but also the way we think CRM can be helpful is bring some tools that help innovate in that space. And I think, Danica, you might have talked about Hive in that context. I want to sort of be mindful of time, Arthur. Let's move to Bill. I'm going to be a bad cop because we want to make sure that everybody has a chance to, and then we'll go back to you as well. So now one question to Dr. Wood. When you're thinking about the next five years and how you would like to position your registry program, what are sort of the characteristics of what you have of your data hub program that best position you for that sort of near-term future in advancing it and harmonizing it with the novel tools and novel capabilities that exist in the entire ecosystem? Thanks for the question. I would highlight, I think, three key areas I think are going to help us grow and continue to achieve our overall objectives. I had just begun to illustrate earlier during the brief presentation. So one of those is that we have the ability to work with, and we're very focused on some of the largest tertiary and quaternary care centers around the country that are providing sophisticated care for patients with hematologic conditions, whether those are hematologic malignancies or classical hematologic conditions. And that is not whatsoever to discount the importance and prevalence of disease burden across communities around the country. But I think that in working with sites, we have the ability now to scale across not just these first two diseases that we've discussed, but the ability to get farther and farther across the landscape of different hematologic conditions. And I think that the issue of crossing into the community is something that we're addressing in a separate way. So I think that's kind of one key thing is that we're working with the same sites to provide lots of care to other patients who are affected. A second key issue is that, we take interaction with and engagement with the patient and family community very, very seriously. I think that our community advisory boards has been something that we've been very proud of within the ASH Research Collaborative. We anticipate doing work like this throughout our different patient communities. And I think that as we're thinking about PROs, patient-generated health data, even how one thinks about consenting where that's appropriate to particular activities within a registry, patient-family engagement is very important. So I think that that foundational work will hopefully set us up for success. And then I think the third area is really around this very tricky issue that Dr. Satrakian was just alluding to, which is that I wish it were as easy as having interoperability solve all of our problems too, but we have some issues in that regard as well. And I'm hopeful that because, and this is I think where professional societies really have an advantage, you know, we are trusted conveners. And I think that as we're working with our clinician communities, we can work on things like documentation, you know, standards or aspirations that will hopefully help with the curation process for data that are not so readily structured and interoperable. So anyway, a few thoughts off the top, but again, thanks for the question and the opportunity to answer. Oops, there you go. Thank you. One question for Dr. Godny. And again, we've heard a lot about accomplishments from the vision, how would you describe, what differentiates you from other data sources? Let's say you've been through this journey about addressing the particular question, whether that be from regulatory or other setting, what makes the difference between the regulatory or other setting? What makes the society's registry and portfolio of registries, including the CRN sort of addition to it, different from more of a traditional data sources? Well, I think, you know, we've been fortunate, and thanks for the question. We've been fortunate that the patients and the diseases that we wanted to study kind of presented a kind of fertile soil, if you will. You know, our patients all tended to be elderly, which made them a good candidate for Medicare linkages to our professional society. So that kind of was a, that eased a burden, if you will. If, you know, if half of our patients were under the age of 65, the question wouldn't be as applicable. But fortunately the patient population was appropriate. And second, it was really a key evidence gap. You know, people, it's hard to follow these devices over the longterm. They're quite expensive. You know, as Dr. Wood is alluding to, they're not just sort of treated in centers of excellence. They're used broadly across the United States at tremendous cost. So it was an important question that nobody could really get a handle on. And especially in terms of how these devices perform in a real world practice, well after the pivotal studies that inform their regulatory decisions initially have been performed. So we had sort of a sweet spot that had been created. And then the only real homework we had to do was just figure out how to make all the data sources talk to each other and make everybody get along in the sandbox, if you will. And we've been fortunate that with our partnership with MD EpiNet, with FDA, that really brought a lot of people to the table within our specialty to support the effort. You know, our professional society has been tremendously supportive of this effort because they saw the value, not just in, you know, some academic publications and things, but the opportunity to really have a voice in long-term regulatory decision-making and really contribute towards taking better care of patients with vascular disease by giving better evidence, you know, at lower cost, all those things. Okay, so now one question for each of you, and then we'll leave some time for Kathleen to go through any other remaining questions from the audience. And this has to do with how the future state looks like from your perspective. Again, that question, you can cover a lot of territory, including some of the novel technologies and all the other relationships and governance and participation. So how do you see the future going back to arts first? Yeah, I think 21st century registry and CRNs need to think really about value, additional value they bring to collaborators. Physicians are very busy people, and there's only so much we can do with the interoperability and ability to download a lot of data from IT systems. I really think we need to provide something more. And some examples are already in place, the technologies that help them manage patients, practice management, decision aids, technologies that help them even enable them to certain operations like image guided surgery. I think those are the technologies that should be helpful and should be part of our vision for data partners. The organizations that are helping us to maintain registries, hopefully will be the organizations also who could provide these kinds of solutions to keep our communities more engaged. That's one comment I have about a future registry. And second, really also a critical issue is working with federal partners to make data access easier for real world data sources is critical. This is number one challenge we're having. Medicare data alone takes a lot of time and resources. And yet there's a lot of other data sources that we can bring into these networks. And it's not easy for manpower issues, we have funding issues. I think the future definitely in partnership, in fact, with the community that is participating today is to lobby the government and make sure we have this better access to data sources. Okay, Dr. Woods, the same question. Sure, absolutely. Absolutely, there's tremendous opportunity in this area. I'm glad we're having this panel and this discussion. Registries are the future, it will look a lot different, I think, than what we've been used to over the last few decades. And I think just a couple of quick areas that I'm very interested in personally. Again, one is this issue of leveraging new technologies to actually see how we can positively influence the way in which at point of care, we're doing documentation. I think I look at projects like MCODE and oncology, there's related projects like that, cardiology and elsewhere. Hematology is a ripe area too. So, and we do that, I think, when we have trusted interests and demonstrate value in that. But I think that makes the data collection a lot more reliable down the road. Second, again, is this issue of really leveraging data science and having truly structured kind of, this digital phenotyping effort is a massive one. And many have been doing this work for quite some time, but it's a testable effort. And so I think that we can find out how far we can push the limits of really getting what we can at a structured and unstructured data and then saying, this is, you know, for certain concepts, this is about as far as we can get. And for other concepts, you know, we're gonna need some additional manually curated help. And I think really understanding that and exposing that is gonna be important. And then the third area I would say just briefly is, again, Dr. Satrakian's points around community value. And I think that we really have to engage patients and families as individuals and clinicians as individuals too. So much of the time, clinicians don't really see these efforts can become very abstract. They're just not very available at point of care. And I think as we look at kind of, you know, breaking down traditional silos across institutions and elsewhere to become part of a collaborative community focused on using these data to produce accelerated research and practice change, easier said than done, but I think engaging clinicians as individuals is a huge opportunity. I know Kathleen is eager to jump on the questions. Anything, Phil, that you'd like to add or you'd like Kathleen to go with her questions? I agree with what Art said. I think, you know, emphasizing data access, easing data and speeding the data access, I think is another key step moving forward. So, but I'm anxious to hear the Q&A, so. Okay, all right. Thank you all for that panel discussion. Let's transition now, everyone who's on the line. We have a few questions in here, we'll start. If you have any other ones, please don't be afraid. Ask even the simplest of questions, because I guarantee you're thinking it, somebody probably else is. So one question we have here is for the VISION program. Has VISION looked at the systems for semi-automated curation? There are a couple methods, including what is being used by ASHRC and by I-SPY, which is one source. Dr. Goodney, you want to respond to that one? Always, you know, I think Dr. Wood pointed out nicely, you know, in a perfect world, I would do my operation with my own vascular team. They would barcode the implant. It would directly upload through my hospital's EMR, which would then distribute all the electronic data to both my own professional size registry, which would then populate it into VISION, you know, through our kind of direct access mechanisms. And I'd be done at 2.45 in the afternoon, and there'd be like a warm muffin waiting in my office. And that's the ideal scenario. But the reality is that, you know, I operate in three different hospitals. And sometimes when I ask for a device, you know, the people working with me say, well, what are you talking about? I don't even know what that is. Especially, you know, in COVID, when our teams have been devastated. So simplicity, unfortunately, is going to have to be a bit of the order of the day. So while I think we should, you know, emphasize our newer, you know, e-phenotyping, I very much enjoy hearing about, that's a great idea, trying to simplify and leverage electronic resources. I do think that we have to, you know, make sure to not lose sight of making sure that we can also collect data from some of the places that might be the, you know, less well-equipped and be working harder to provide high-quality healthcare. So I've been, you know, we speak on both sides of that issue in terms of trying to leverage new technology, but also trying to make sure we don't just study the places that have the sharpest edge on the knife, but we also study places where things might be a little harder to work every day. Yeah, that's excellent, thank you. And I see Dr. Pappas, he also added, one source is saying that they're saving a third of the time in data curation. Again, data curation, meaning that you're reviewing and validating, making sure that the data are reliable. Okay, let's move on to another question here. One is, what are the top three things I need to consider for my registry to be part of a coordinated registry network? And I would be happy to maybe take a stab and then I'll ask the other colleagues on the panel here to respond if you have something to add. You know, if I were to drill it all down, because so much of what we had talked with at times can feel very technical, very scientific, but what does it mean at the end of the day if you're just trying to figure out what is your staffing structure? How are you organized? What contracts do you have in place? Do you have enough money in it to support everything? So the top three areas I would suggest would be, one is what you heard today, and I'll just drill it down to the basic. Do you want your registry data, which is real-world data, to be used to support FDA-regulated research, to be used to support some other type of research? Because remember, coordinated registry networks is not unique and specific to the FDA. It's just that the FDA has a lot of very good case studies in how FDA is using real-world data to make regulatory decisions. So that first question being, does real-world data being used to help somebody make decisions, does that align with the mission of your registry program? If the answer is yes, I think number two, I would give some thought to, do you have the competencies to participate in those discussions? Do you have the right scientific and technical leaders to participate? And I would emphasize that I don't think we all have to have the world-class experts in thinking about predictive modeling and how to take your data and create precision medicine tools. But we do have to have people who appreciate that and are willing to roll up their sleeves and work with groups to think about how to use your data to get to the point of some of the great uses that Dr. Goodney was referencing. And also the technical leadership, thinking about how do you bring in different data sources and how do you deal with data use agreements and how do you deal with matching patients if you don't have direct identifiers? So number two would, in summary, would be to think about your technical and your scientific resources. And then the last would be to give some thought about your business model, because all of the work that goes into the things that you've heard described today, it costs a lot of time and a lot of money. And how is that gonna be funded? And some of the work, there is a paper, as a matter of fact, I just copied, and I'll push here, I'll go ahead and push, send now to everyone. And I think there might be another more current paper. So if so, if we can find it before our session is up in two seconds. And this is determining the value of coordinated registry networks. It's a return on investment paper and talks about how much money was saved for the ecosystem. But you have to think about running your program. And is there a way in which your data is being used across a coordinated registry network where it's perhaps there is your driving income that is supporting all of the work that you need to do? So I would encourage you to reach out to other organizations who are actively involved with coordinated registry networks and ask them how their business model internally might be working. I would like to add a couple of things here. One minute, but I would like to make sure that the folks don't leave this meeting with thinking that joining the coordinated registry network is only for the most sophisticated ones. In fact, to the contrary, the ones that can benefit the most from the learning community are the ones who need the most help, because there is a lot of help pro bono that is happening in this community. And so I would encourage you to do that. And then, according to everything that you presented, it's really about learning how to leverage work in clinical space, informatics, technical, all of the things that Kathleen had mentioned are standing, and I agree with them. But for the ones that can benefit the most from it are the ones who can actually join it for those benefits. Yeah, no, I agree. Dinesha, that's an excellent point. Thank you so much. That was an incredible webinar. I learned so much from all of you. I wish we had more time. We clearly could have gone on for a lot longer, and apologies to Dr. Pappas. We could not get to all of his questions, but the good news is I believe he's on our next upcoming webinar on October 31st, which will focus on a lot of the issues you've all raised today as well, which is focused on sustainability and member engagement. So we will continue these discussions with our friends at FDA and really think about how we could work collectively across all of our registries and continue to take their learnings and understand how we can get people engaged in that work going forward. And with that, I'm gonna thank you all for your time. Thanks to Heidi for organizing all of this and Kathleen and Dinesha for pulling this all together. And thanks to all of our speakers. Bye, everybody. Have a good day. Thank you. Have a good one.

medical registries

CMSS

registry science

Coordinated Registry Networks

CRNs

electronic health records

EHR

ASH Research Collaborative

FHIR

Vascular Quality Initiative

real-world evidence

healthcare improvement