Steps to Improve Data Gathering on Rare Diseases

February 18, 2022


The authors of four separate studies on the economic burden of rare diseases recently collaborated on piece in Health Affairs calling for concrete steps to address gaps in data that make it difficult to track rare diseases in the healthcare system. Though the authors came to similar conclusions in their reports, they were also stymied by existing data constraints, such as a lack of codes for rare diseases, differing data structures of electronic health records, and missed opportunities to gather data through public health surveys. We spoke to Joni Rutter, acting director of the National Center for Advancing Translational Sciences; and Annie Kennedy, chief of policy and advocacy for the Everylife Foundation for Rare Diseases, about the economic burden of rare diseases, the data constraints that limit a complete understanding of the impact they have, and what steps can be taken to improve the availability of patient data.

Daniel Levine: Annie, Joni. Thanks for joining us.

Annie Kennedy: It’s our pleasure to be here. Thank you for having us.

Daniel Levine: we’re going to talk about a recent piece in Health Affairs. You both co-authored the series of studies about the economic burden of rare diseases that led to the piece and recommendations you have to improve our understanding of rare diseases and their impacts on people who have them and their loved ones. I’d like to start with the studies that you each were involved in that led to this. Annie, about a year ago you and I talked on this podcast about the EveryLife Foundation’s National Economic Burden of Rare Disease study. Listeners who are interested can go into our archive and look for episode 324. Annie, can you remind listeners what that study was seeking to do?

Annie Kennedy: Sure. About two years ago, the rare disease community really identified a gap in real data around what the economic impact of living with a rare disease is. And so as a community, we came together to really collect this data. Families who were living with rare diseases certainly understand the cost absorbed by families. And we see in our healthcare bills, what the costs to the healthcare system are, but we’d never really, in an organized way had evidence—real data around this. So we set out to collect what’s considered direct cost data—look at the data in the healthcare system, as well as non-medical and indirect data; look at the impact to caregivers, the productivity losses, what it costs to not be able to be at work or to have to manage your healthcare while at work; and also what the costs were to families who are having to make modifications to their homes or modifications to their cars, or pay for things that are prescribed by physicians that aren’t covered by their healthcare insurance. What that was. So, we conducted that study and what we found was that during calendar year 2019, when we looked at 379 rare diseases, and we can talk later about why that was the number that we looked at, and I’ll remind you that there are an estimated somewhere between 7,000 and 10,000 rare diseases. So, in this study we’re really just scratching the surface of the economic impact, but we found that in 2019, the economic impact, or the cost of living with rare diseases in the U.S. was close to a trillion dollars. And what’s most significant about that was that the majority of those costs were not the costs in the healthcare system—were not the costs that we’re seeing in emergency room visits and provider visits and prescription costs, but were the costs being absorbed directly by families. Those indirect costs are non-medical costs—the out-of-pocket costs with living with a rare disease. We were not the only ones, though, collecting data. We were really heartened to know that other partners were also looking at this really important need and really important question, including, the NIH.

Daniel Levine: Well, Joni, you were one of the authors of the IDeaS Initiative pilot study that was published in the Orphanet Journal of Rare Diseases. What did that study seek to do and what did it find?

Joni Rutter: Yeah, great question. And I’m so glad Annie went first to talk a little bit about her study, because it really does dovetail very well with that. You heard her say that there are over 7,000 rare diseases. Each year as we’re able to sequence more and more individuals, we’re finding new diseases every year, even on top of that. So individually there’s 7,000 rare diseases, but collectively they are really common with about 30 million people in the U.S. who have a rare disease. So, as you heard from Annie on the EveryLife Foundation study, the burden of rare disease is enormous at a societal cost around $1 trillion and that’s staggering, and we had been thinking along these same lines in terms of understanding that cost burden, but we didn’t really have data to point to until the EveryLife study. By that time, we were kind of underway in thinking about how to address it on our own. Because rare diseases are, as a whole, somewhat fragmented and it’s difficult to find rare disease patients within our healthcare system, they’re essentially silent in a way because they’re very hard to identify. So, for us, this was quite a tall order, but we set out to do three things. We wanted to understand the total prevalence of the rare disease population within the U.S. Can we identify how a given disease is caught by a unifying diagnosis or a set of characteristics, for example, for rare diseases. So that was one question. The second question we had was what are the key data that are needed to understand the natural history of rare diseases? How many people have enough data to characterize that natural history of those rare diseases? Can we identify trends, for example, if rare disease patients need to see a variety of physicians within the healthcare system, can that be something that we can count on to identify rare diseases within the population without having anything else to go on? Or can we go on tests that are ordered, for example? So, that natural history of disease was the second question we were interested in. And then the third question was very much along the lines of what Annie and the EveryLife study has done, and that is what’s the cost of care for rare disease patients? We wanted to understand that total cost of rare diseases in the U.S. both as an aggregate and also at an individual rare disease cost level. So, we selected about 14 different representative rare diseases within four different healthcare systems to analyze using these sorts of ways to identify rare disease patients within those groups. And we wanted to get a sense of that diagnostic odyssey, how long it takes for patients to get diagnosed with a rare disease, for example. So, if we found them in the healthcare system, we could use that date in time and go back five or 10 years to understand what their diagnostic journey really looked like, and we wanted to get a good sense of that. And we were able to use those data then to get a handle on those three main questions that we were seeking to ask.

Daniel Levine: And what were the findings?

Joni Rutter: Well, we took those rare disease patient records and compared them to matched control groups within the same systems. In this way, we’re able to quantify and evaluate the direct medical costs of those rare diseases across the health systems that we looked at. What we found was that when we compared those groups, rare diseases were three to five times higher in direct medical costs and that translated into about a $400 billion price tag for those direct costs in medical care per year. So, we took a completely different approach coming at this problem, almost directly opposite as how Annie and EveryLife did their study. But we came up with a number that was very similar in those direct medical care costs. We were not able to evaluate the indirect and other costs that EveryLife did, but as they indicated that total cost is about $1 trillion. What was striking to me is that this just signifies that it’s a very clear public health issue for this burden of cost for rare disease patients.

Daniel Levine: As both of you sought to undertake these studies, how hampered were you by the lack of available data? Were there things you were unable to do or found difficult getting greater clarity on because of data challenges?

Annie Kennedy: As I mentioned, our methodology included an analysis of direct cost data, but very importantly included a survey that we conducted to the broad rare disease community. And to develop that survey, we worked with our patient advocacy organization partners to identify what data elements we would include in that survey. We disseminated the survey through hundreds of patient advocacy organization partners to the broad community. And that’s how we collected the data around the non-medical and indirect costs. We then asked people when they took the survey to identify what rare disease they had been diagnosed with, so that when we did the data analysis, we correlated the name of that diagnosis with a corresponding what’s called ICD code or the International Classification of Disease. And the ICD code, for are those who are listening, is a code that I like to think of it like a hashtag that is assigned to medical devices and medical conditions. Then when you go to the doctor, you have codes for everything, a code for high blood pressure, a code for pregnancy. There are codes for COVID, and it follows you in your healthcare system. Whether you’re in registries or if you’re in different electronic health records, when you go to your primary doctor or the hospital that code can then follow you and connect your records to one another. So, we asked people, we correlated their rare disease with their direct medical data. One of the limitations, though, of our study and other studies like this is that we don’t have ICD codes for all of the rare diseases. So, as we’ve said, there are an estimated 7,000 to 10,000 rare diseases. We have ICD codes for about 500 of those rare diseases. That means that we can’t pull data within the electronic health records and registries and surveillance systems in the U.S. for more than those diseases, because we don’t have codes to pull them. Those data systems can’t talk to each other using that international classification system. That’s one of the really important limitations of this work, but what that really translates to is that if you have a rare disease that does not yet have its own distinct code, essentially within those systems and the way we query this data and we do these analyses, then you’re invisible, we can’t track you in this way. That was a really important limitation. And one of the policy items that we actually point to, in this Health Affairs piece is that we really need to do better as far as assigning codes to rare diseases in rare disease communities.

Daniel Levine: Joni, how about your experience? Were there challenges with the data that limited your ability to get access to what you would need?

Joni Rutter: Absolutely. There were unfortunately, and I will just echo everything that Annie has said about the ICD codes. I think that that’s just a big critical fact in our inability to analyze these data in a way that’s streamlined and fairly straightforward to do. But I’ll say too that there’s a widely varying percentage of rare diseases in different healthcare systems, which also makes it difficult to understand their true prevalence and even with ICD codes and if they don’t have ICD codes, that difference in prevalence across healthcare systems really just adds to the variability and the uncertainty of the data that you’re looking at. And perhaps a bigger issue is with the data itself and electronic account records and the data included in them. These data aren’t always in structured fields. ICD code is a structured field, and since data aren’t always in those structured fields, then we can’t get that consistency that’s needed for understanding and comparing the data across those fields. So even if they’re classified, and they may be classified under broader unspecified terms or other types of codes that could be used, it still makes finding rare disease patients very difficult, even in unstructured data like those within physician notes or describing a test that are not amenable for simple extraction from an electronic health record. Those unstructured data are very difficult to be able to compare, as well, across different studies and this limits the ability to identify those rare disease diagnoses. So, there’s a variety of things that really impact our ability to look at these data and what I think part of what we’re missing here is our ability to understand those timelines between the onset of those symptoms or diseases compared to the accurate diagnosis that needs to be obtained. Understanding that timeline between symptom onset and diagnosis might be highly variable and we’re just not able to capture that within the system. Again, these are just quite a few issues within the data that make it very difficult to pull these rare patients within the systems out to really understand very clearly the bigger picture that’s going on.

Daniel Levine: And Health Affairs. The two of you recently joined authors of other similar studies. How did that piece come together? What was the conversation?

Annie Kennedy: EveryLife reached out to the authors of these other studies, as we were learning about the studies that were in progress, and saw that the timelines for the release of the studies were actually well aligned. Economic cost studies are really important for a number of reasons. One is that cost estimates can be used to prioritize policy and we at EveryLife are a policy organization and wanted to ensure that this data that was being generated could be used by the broader rare disease community to help inform policy work by rare disease partners. It’s really important to us that the members of the rare disease community, the individual families that spent so much time contributing to our study informing the data that we were collecting and then sitting down and each family who participated in our survey spent close to an hour contributing their experiences, their financial reflecting, their financial experience into our survey. And that’s not for naught. That’s not just for a publication. That’s really to move the needle so that we can really ease the impact of living with a rare disease, ultimately increase the resources that are going into research and infrastructure and for rare disease in the U.S., and then really inform some of the policy work that’s happening. The other thing that’s really important as we look at these cost estimates is that it helps us to understand where the specific economic cost drivers are, so that as we look at those policy levers, we know where to push and pull on them. The first of the reports to come out was our EveryLife report. And then, I believe the GAO study and the NCATS study came out really close together. And then the study that Sheldon Garrison released, came out and I think right before those two did, and we were really gratified to see that we had all used very different methodology, that the numbers were really aligned and were the same. So, we were validating one another’s work and really showing that this was the experience of the rare disease community. There is a public health crisis, but there was also a really clear theme and Dr. Rutter just spoke to it. One of the things we saw in our study through the collection of the data from the community was the diagnostic odyssey in rare disease. And one of the things that families reported to us (we had worked with the Undiagnosed Diseases Network to incorporate some questions to understand what that diagnostic odyssey looks like in rare disease) and we found through our survey was that on average, the mean for respondents was 6.3 years between the time they first reported symptoms through a provider until they received a confirmed diagnosis of their rare disease, 6.3 years. And that diagnostic odyssey included visits to 17 clinical specialists. And those visits included ER visits, out of state visits, hospital admissions, and on and on and on. And so we can see a correlation directly to the direct costs that we saw in our study, and where there are cost drivers in rare disease that we can then really dig further and see where there are opportunities to reduce those costs because of the technology we already have to do better to advance diagnostic tools, to increase reimbursement for diagnostic testing and genetic counseling, and overall reduce the barriers to diagnostics and follow up care. So for all of these reasons, it was incredibly important to us to pull these studies together and start to point to some of the common threads so that we could really push some policy opportunities. We see some real low hanging fruit to really make vast improvements for our rare disease community.

Daniel Levine: I’d like the two of you to walk us through the recommendations in the Health Affairs article, but before you do that, Annie, you had spoken about ICD a moment ago. I’m wondering if one of you could demystify those for us a bit and explain how a rare disease gets an ICD code.

Annie Kennedy: There is a very formalized process for the establishment of an ICD code. ICD codes in the U.S. are done in coordination with the WHO, or the World Health Organization, but in the U.S. it’s through the CDC or the Division of Health Statistics. There is a committee that has another acronym—the ICDCM, and they have a very difficult job of overseeing all of the codes for all medical procedures and all diagnoses. It is actually a very technical process where all codes have to be alphabetized and indexed, and really married to one another and make a lot of sense. So, if you have a category of codes, and let’s use the muscular dystrophy as an example, you can have a broad category of codes and then sub codes within those. If you have a rare disease, rare diseases fall into broad categories and need to have more granular, more specific codes, and some disorders have no codes at all. So, you could use COVID as a perfect example. You do have diseases that are new to the population and need an entirely new code. And there are times when you have a rare disorder, that for a long time has been a part of an umbrella or a basket code and warrants a more specific or a refined code. And if you are looking to do that, oftentimes this is a process that’s led by, in the rare community by patient advocacy organizations that work to develop the evidence, to look at the data that’s available, oftentimes through patient registries, economic data, and to develop a nomination. And EveryLife led an effort about a year ago to develop a roadmap to an ICD code. We actually put together resources, templates for communities, nomination templates, so they could see what other communities had done previously. We gathered tools and guidance from all the federal agencies that work with us, and it’s all available on our website, so that if you are a patient, an organization, or any partner looking to nominate either a new or refined code, you have someplace to start because there really hadn’t been any guidance up until that point. And we just really looked to develop a resource for partners so they knew where to start.

Daniel Levine: What was the recommendation you were making about ICD codes and what would you like to see happen?

Annie Kennedy: What we set out to do was really create a resource for organizations that were on the path to try to create a code. And right now, we have a generous rare disease community. Organizations call an organization that’s already done it and learn through word of mouth and experiences for one another. We wanted to have something that was a little more formalized for people to start with. So that was the first thing we did. Along the way, though, we did learn of some good practices. I won’t call them best practices because we just learned what had worked for some folks, where the minefield had been, and then did work with some partners to develop some suggestions for how we could do better. One of the things to us that seems like a healthy start is we know that we have at least 7,000 rare diseases and about 500 codes. We would really like to see the federal agency partners come together, all of the federal agencies that work in this space and have rare expertise to come to some agreement on what codes should exist. We’re not saying there should be 7,000 codes, but we can do better than 500 and to update that listing so that we have a listing of codes that is more reflective of the current lived experience and current science in rare disease. And we actually led some appropriations language around this last year to really urge the federal agencies to come together so that we could reduce the rocks of the backpacks of patient groups, so that it’s not on the patient groups to have to do all this work themselves. And we could really update that listing to be more reflective of the number of diseases we know people are now currently experiencing.

Daniel Levine: You also call for enhancing the collection of rare disease patient data. What specifically would you like to see done there?

Joni Rutter: Thank you, Annie. I really enjoy how you talk about the ICD codes, because I think that these are tractable issues that I think that we can start to really tackle and codes are one thing, but in terms of collecting data and information on rare disease patients, that is another thing. There are a couple of things here that I wanted to point to. One, for example, in just larger cohort-based types of research that’s conducted across the country and things that we support. I think one of the areas that we can enhance our understanding of rare diseases is capturing additional information on rare diseases in those broader kinds of research-based cohorts, our understanding of rare diseases and their intersection with other health outcomes, for example, or environmental influences, is largely unexplored. This is one area that we can continue to make headway on. Another issue is around the natural history of rare diseases. And I’ve talked about this a little bit before, but understanding the clinical course of rare disease is critical for helping with earlier diagnosis and that diagnostic odyssey that we’ve been talking about. In this way you can start to understand, for example, for any given patient with a rare disease, their clinical features, their major medically relevant milestones, or their characteristics, or disease modifying therapies that might be available, how billing costs are mapped over those electronic health records to get a more honed understanding of that natural course of disease and how to spot it, how to treat it, and how to align those costs. And part of that issue then is to harmonize the rare disease coding in healthcare system. That’s such a big need. That’s really woefully inadequate. I think that many times we turn to the community to really think about those practical solutions. And one of the networks that we have that NCATS supports is the Rare Disease Clinical Research Network, or the RDCRN. And this is a network of 20 or so groups that are studying a variety of different rare diseases. And thinking about the rare disease patient data and how to collect it, and perhaps it will be a fantastic group to also think about how to prioritize tackle the coding issues as well.

Daniel Levine: Another recommendation has to do with expanding access to advanced diagnostic tools. Why does this matter in the context of rare disease data and understanding the landscape?

Joni Rutter: I’ll take this one and then Annie, I’ll turn it over to you. This is an interesting one in contrast to the current approach to diseases that are based on the clinical presentation. Rare diseases are so important to really understand, even going beyond that clinical presentation, because sometimes that is misleading. And so, the concept of things like looking at perhaps how these diseases manifest, can we get an understanding of even perhaps those that share molecular etiology that’s contributing to the disease focus. So, thinking about how we can use sequencing technologies to start to identify and diagnose particular rare diseases, that’s one thing that we’re trying to do in terms of the diagnostic side. I think the other key issue here is about identifying them within the healthcare system and using new tools and new resources for unifying within the electronic health records for physicians who are seeing rare disease patients. Are there ways in which we can enhance the electronic medical records so that there are triggers within the system that will alert physicians, whether or not a patient’s seen multiple doctors before seeing that particular doctor, or if there are particular terms in their medical record, those basket terms that Annie mentioned before are so critical for identifying issues where there might be a rare disease patient in front of the physician, but it’s not necessarily that obvious. And so, can we identify and use new tools that perhaps take advantage of artificial intelligence and machine learning to identify those types of rare disease patients faster and better, and get them to a diagnosis faster and better? I think those are some of those ways in which we’re thinking about advancing those diagnostic tools.

Daniel Levine: You also call for supportive registry, natural history studies, and other projects like that. How fundamental a role do these types of studies play in understanding the rare disease landscape?

Annie Kennedy: Dr. Rutter, I’m sure can talk about this all day. So I’ll give a short answer and maybe hand it off to her. I would say they’re critical and they’re foundational, not just in understanding rare diseases, but also in moving clinical trials forward and therapeutic development forward. So, it’s how as rare disease communities, we find one another and understand our diseases better. And we understand the progression of the diseases and understand subpopulations within our diseases, and the nuances within our communities are all understood within our registries and our natural history studies. Then, as we’re seeing improvements being made either through treatment interventions or products that are being developed, that’s where we begin to see that evolution and then understand how that’s benefiting our communities. So, it’s foundational to the community that we have these registries and these natural histories stood up, but it’s also in some communities, the existence of the natural history studies will be probably the only way we’re able to conduct the clinical trials and be able to really design trials that will make product development possible. It’s such a critical point and the clinical trials are certainly something we could talk a lot more about, but the other piece of it is that the more we understand about the natural history of the diseases and those natural history studies, they can also help us to find ways to prevent misdiagnosis of rare disease, which we know happens quite a bit. And for rare diseases that do get misdiagnosed, because we don’t have that natural history data or ways to classify them well in our systems, then that can create issues in terms of inappropriate care because of those misdiagnoses or a lack of targeted treatments that could modify the disease in a given window. But if that disease isn’t picked up when it needs to have modifying treatment, then that window could close and those treatments would no longer be effective. So, these are also other critical issues. I think that understanding the natural history of disease is so important for us to, map these, issues out much more clearly.

Daniel Levine: Finally, you call for the enhancement of electronic records structures to facilitate research. Has this been kind of a missed opportunity? Can you explain that?

Joni Rutter: Oh, I’ll start. I think it is a missed opportunity in a way, and it’s also a bigger problem than just in rare diseases. This is for all of healthcare and Annie brought up the issue of COVID 19 not having an ICD code. I think this is a great case in point for in the United States there is no way to standardize our electronic health records for research or to help us make informed clinical decisions. This was a need that NCATS had identified early in the COVID pandemic so we created a national COVID 19 cohort collaborative, something that we call N3C, but it’s working with the clinical and translational science award program and the ideal state clinical and translational research programs along a variety of others. And we’ve amassed now 11 million electronic health records from COVID positive and matched controls to study clinical outcomes of COVID 19. This was a huge undertaking because of the lack of standardization across the EHRs. For example, one hospital might collect height information, for example, in inches, and another hospital might collect it in centimeters, and you can see that it’s a problem if you don’t standardize those two. So you need to collect it in one metric. And this problem highlighted with certainly with the COVID pandemic because it didn’t have an ICD code in 2020, but now it does. But now you can imagine that 7,000 diseases, most of which don’t have an ICD code, those standards are critical to be able to have our health systems be able to talk to one another. So, there is this need for electronic health records systems and structures to be able to start to build up that infrastructure for doing more research within those types of data that can be very helpful for clinical research.

Daniel Levine: The recommendations seem reasonable, but what’s unclear to me is who you’re addressing them to. Who has the power to make these changes or order them?

Annie Kennedy: The intention behind these studies was multifaceted. The intention behind doing the blog was to make sure that policy makers, meaning people in Capitol Hill, appropriators, people in federal agencies are really understanding the core themes in these studies and that it wasn’t just one researcher, one study that found this data—that we’re really seeing some core themes. We really wanted to pull all these pieces together. So, I think each group will probably be doing individual things with these studies, but as a disease community we wanted to come together and make sure that policy makers see all of this pulled together. It is no coincidence that we’re moving into Rare Disease Week and we will have, probably close to a thousand advocates going to Capitol Hill, and the EveryLife Foundation and Rare Disease Legislative Advocates are helping to coordinate a lot of that. And these are issues that really hit at the core foundation of our rare disease communities’ experience. A lot of us in the rare disease community have found this data to be very validating. This really reflects the lived experience of members of our community. And while these numbers are staggering, when you think about them and you look at them, they’re not shocking to families who are living with rare diseases. What’s really important to us as we meet with members of Congress and as we set our policy agenda here in Congress, is that while the numbers are important, we’re able to look beyond the numbers and understand that these reports really shed critical light on the challenges and difficult choices that are faced by millions of families, and that as we’re having conversations about where our federal funding priority should be, that it’s not acceptable that a parent’s ability to care for their child should be dependent on their finances. So, what we’re really seeing here in the data is that time and again that happens here in the U.S. And so, what we really did was knit together some opportunities and some policies that could be implemented in 2022 that would help alleviate this really crushing financial impact being shouldered by families in the rare disease community.

Daniel Levine: And do these recommendations carry cost implications, and if so, how should they be funded?

Annie Kennedy: We are also doing appropriations work here at the EveryLife Foundation. We have not had scores placed on any of these. We don’t have a legislative proposal assigned to any of these. Many of these actually would probably streamline costs in many places. I think the short answer is there isn’t a score. But I do think if we look at some of these individual policy proposals, we would probably find that there would be a cost savings associated with reducing a diagnostic odyssey of six years and 17 specialists and applying some of the existing technologies to reduce that odyssey and ensure that the treatments that are available to patients were made available at the point of care when the first symptoms presented, rather than sending somebody on a heartbreaking and expensive diagnostic odyssey. So, I think we can start to see the solutions lining up and we can move beyond those back of the envelope calculations that we’ve been doing for so long.

Joni Rutter: Just going to add to that. I love Annie’s answer there too. I think that in terms of how should they be funded, one of the things that we’ve done at NCATS is we’ve thought about the diagnostic odyssey quite a bit and NCATS just made awards to provide funding for multidisciplinary work on artificial intelligence and machine learning approaches that incorporate genomics and clinical expertise. We’re really looking to strategies that can be applicable to a broad array of rare diseases and be able to be adopted or adapted to frontline healthcare providers. And so, we’re funding research now to be able to incorporate this type of thinking in the broader healthcare systems that we support. That is one area that we are actively supporting.

Daniel Levine: Well, what can members of the rare disease community do if they’ve read the article and agree with the recommendations? How can they add their voices to the call?

Annie Kennedy: I love this question. Members of rare disease community can find us on our EveryLife website and also join us through our Rare Disease Legislative Advocates. Most immediately we have Rare Disease Week. We have many events during Rare Disease Week. NIH is hosting a Rare Disease Day, which I’ll hand off in just a second so Dr. Rutter can talk about it, and it’s about the collective voice and priorities of the rare disease community and hundreds of patient advocacy organizations are also lifting their priorities during those events and during that week. And so we just invite all members of the rare disease community and your loved ones and friends and colleagues to join with us so that we make sure that people understand that rare disease isn’t somebody else’s concern or somebody else’s problem, but it is a public health issue that we all care about and all prioritize.

Joni Rutter: And I’ll just add too, as Annie mentioned, it is Rare Disease Day at the NIH on February 28th. It is an event that anyone can sign up to join or hear more about what’s out there and how to get involved. At this meeting, people from across the community come together to share their stories, to spotlight progress, and to talk about what more we need to do. I will also say that NCATS has a rare disease page: ncats.nih.gov/rare diseases. Here you can find information about findings, resources, clinical trials, funding opportunities, and staff to connect with for other questions. So, between EveryLife and NCATS, I think there are variety of resources for people to get connected with, and there are other resources out there as well.

Daniel Levine: Joni Rutter, acting director of the National Center for Advancing Translational Sciences, and Annie Kennedy, chief of policy and advocacy for the EveryLife Foundation for Rare Diseases. Joni, Annie, thank you by both.

Annie Kennedy and Joni Rutter: Thank you.

This transcript has been edited for clarity and readability.


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