electronic health records
A Rare Public Health Challenge
Posted on by Joni Rutter, Ph.D., National Center for Advancing Translational Sciences
Most public health challenges may seem obvious. The COVID-19 pandemic, for example, swept the globe and in some way touched the lives of everyone. But not all public health challenges are as readily apparent.
Rare diseases are a case in point. While individually each disease is rare, collectively rare diseases are common: More than 10,000 rare diseases affect nearly 400 million people worldwide. In the United States, the prevalence of rare diseases (over 30 million people) rivals or exceeds that of common diseases such as diabetes (37.3 million people), Alzheimer’s disease (6.5 million people), and heart failure (6.2 million people).
Shouldering the Burden of Rare Diseases
As with common diseases, the personal and economic burdens of rare diseases are immense. People who live with rare diseases often struggle for years before they receive an accurate diagnosis, with some remaining undiagnosed for a decade or longer. The diagnostic odyssey includes countless doctor visits, unnecessary tests and procedures, and wrong diagnoses. For people in rural and low-income communities, lack of access to care is an additional barrier to an accurate diagnosis. And a diagnosis often doesn’t lead to better health—only about 5 percent of rare diseases have U.S. Food and Drug Administration–approved treatments.
Collectively, the personal burdens of those with rare diseases impose a significant economic cost on the nation. When quantifying the health care expenses for people with rare diseases, we found that they have three to five times greater costs than those without rare diseases [1]. In the United States, the total direct medical costs for those with rare diseases is approximately $400 billion annually, a figure validated independently by the EveryLife Foundation for Rare Diseases. The EveryLife study also included indirect and non-medical costs, resulting in a higher total economic burden of nearly $1 trillion annually [2].
What’s even starker is that the true scope and impact of rare diseases actually may be greater because rare diseases aren’t easily visible in our health care system. Many of the diseases are too rare to have a code that identifies them in the electronic health record (EHR).
Speeding Up the Search for Solutions
Each and every day, NIH’s National Center for Advancing Translational Sciences (NCATS) works with patients, advocates, clinicians, and researchers to meet the public health challenge of rare diseases. Driving those conversations are three overarching goals to help people living with rare diseases get the high-quality care they need, faster:
1. Shorten the duration of the diagnostic odyssey by more than half. The diagnostic odyssey for someone with a rare disease takes on average seven years, and there are several ways we can speed the journey. For example, we are designing computational tools to detect rare genetic disorders from EHR data. This work is part of a broader research effort focused on using genetic analysis and machine learning to make it easier for health care providers to diagnose people with rare diseases correctly. Also, connecting patients more quickly with each other and the research community can hasten the search for answers. Check out the resources below to learn about rare diseases, find patient support organizations, and get involved in research efforts.
2. Develop treatments for more than one rare disease at a time. A key strategy is leveraging what rare diseases have in common. Some of our efforts build upon the fact that 80–85 percent of rare diseases are genetic. We can use this knowledge to develop genetic and molecular interventions for groups of rare diseases. Two programs—the Platform Vector Gene Therapy pilot project and the Bespoke Gene Therapy Consortium, which is part of the public-private Accelerating Medicines Partnership®—are streamlining the gene therapy development process. Their ultimate goal is to make gene therapies more accessible to many people with rare diseases. We also have joined in to advance the clinical application of genome editing for rare genetic diseases.
The NCATS-led Rare Diseases Clinical Research Network, which is supported across NIH, brings scientists together with rare disease organizations and patient advocacy groups to better understand common characteristics, which also might speed clinical research. With this in mind, we are adapting a clinical trial strategy used in cancer research to test a single therapy on multiple rare diseases.
3. Make it easier and more efficient for scientists to discover and develop treatments for rare diseases. NCATS develops ways for new treatments to reach people more quickly. Repurposing drugs, for example, is revealing already-approved drugs that may work for rare diseases. Programs such as Therapeutics for Rare and Neglected Diseases and Bridging Interventional Development Gaps move basic research discoveries in the lab closer to becoming new drugs. Ambitious initiatives, such as the Biomedical Data Translator, unite data from biomedical research, clinical trials, and EHRs to find treatments for rare diseases faster.
The COVID-19 pandemic showed us the power of working together to solve public health challenges. Let’s now come together to address the public health challenge of rare diseases. If you want to get involved, please join us at Rare Disease Day at NIH 2023 on February 28. You’ll hear personal stories, learn about the latest research, and discover helpful resources. I hope to see you there!
References:
[1] The IDeaS initiative: pilot study to assess the impact of rare diseases on patients and healthcare systems. Tisdale A, Cutillo CM, Nathan R, Russo P, Laraway B, Haendel M, Nowak D, Hasche C, Chan CH, Griese E, Dawkins H, Shukla O, Pearce DA, Rutter JL, Pariser AR. Orphanet Journal of Rare Diseases. 2021 Oct 22; ;16(1):429.
[2] The national economic burden of rare disease in the United States in 2019. Yang G, Cintina I, Pariser A, Oehrlein E, Sullivan J, Kennedy A. Orphanet Journal of Rare Diseases. 2022 Apr 12;17(1):163.
Links:
Rare Disease Day at NIH 2023 (National Center for Advancing Translational Sciences/NIH)
Genetic and Rare Diseases Information Center (NCATS)
Toolkit for Patient-Focused Therapy Development (NCATS)
Rare Diseases Registry Program (NCATS)
Rare Diseases Research and Resources (NCATS)
Note: Dr. Lawrence Tabak, who performs the duties of the NIH Director, has asked the heads of NIH’s Institutes and Centers (ICs) to contribute occasional guest posts to the blog to highlight some of the interesting science that they support and conduct. This is the 23rd in the series of NIH IC guest posts that will run until a new permanent NIH director is in place.
Study Shows Benefits of COVID-19 Vaccines and Boosters
Posted on by Lawrence Tabak, D.D.S., Ph.D.
As colder temperatures settle in and people spend more time gathered indoors, cases of COVID-19 and other respiratory illnesses almost certainly will rise. That’s why, along with scheduling your annual flu shot, it’s now recommended that those age 5 and up should get an updated COVID-19 booster shot [1,2]. Not only will these new boosters guard against the original strain of the coronavirus that started the pandemic, they will heighten your immunity to the Omicron variant and several of the subvariants that continue to circulate in the U.S. with devastating effects.
At last count, about 14.8 million people in the U.S.—including me—have rolled up their sleeves to receive an updated booster shot [3]. It’s a good start, but it also means that most Americans aren’t fully up to date on their COVID-19 vaccines. If you or your loved ones are among them, a new study may provide some needed encouragement to make an appointment at a nearby pharmacy or clinic to get boosted [4].
A team of NIH-supported researchers found a remarkably low incidence of severe COVID-19 illness last fall, winter, and spring among more than 1.6 million veterans who’d been vaccinated and boosted. Severe illness was also quite low in individuals without immune-compromising conditions.
These latest findings, published in the journal JAMA, come from a research group led by Dan Kelly, University of California, San Francisco. He and his team conducted their study drawing on existing health data from the Veterans Health Administration (VA) within a time window of July 2021 and May 2022.
They identified 1.6 million people who’d had a primary-care visit within the last two years and were fully vaccinated for COVID-19, which included receiving a booster shot. Almost three-quarters of those identified were 65 and older. Nearly all were male, and more than 70 percent had another pre-existing health condition that put them at greater risk of becoming seriously ill from a COVID-19 infection.
Over a 24-week follow-up period for each fully vaccinated individual, 125 per 10,000 people had a breakthrough infection. That’s about 1 percent. Just 8.9 in 10,000 fully vaccinated people—less than 0.1 percent—died or were hospitalized from COVID-19 pneumonia. Drilling down deeper into the data:
• Individuals with an immune-compromising condition had a very low rate of hospitalization or death. In this group, 39.6 per 10,000 people had a serious breakthrough infection. That translates to 0.3 percent.
• For people with other preexisting health conditions, including diabetes and heart disease, hospitalization or death totaled 0.07 percent, or 6.7 per 10,000 people.
• For otherwise healthy adults aged 65 and older, the incidence of hospitalization or death was 1.9 per 10,000 people, or 0.02 percent.
• For boosted participants 65 or younger with no high-risk conditions, hospitalization or death came to less than 1 per 10,000 people. That comes to less than 0.01 percent.
It’s worth noting that these results reflect a period when the Delta and Omicron variants were circulating, and available boosters still were based solely on the original variant. Heading into this winter, the hope is that the updated “bivalent” boosters from Pfizer and Moderna will offer even broader protection as this terrible virus continues to evolve.
The Centers for Disease Control and Prevention continues to recommend that everyone stay up to date with their COVID-19 vaccines. That means all adults and kids 5 and older are encouraged to get boosted if it has been at least two months since their last COVID-19 vaccine dose. For older people and those with other health conditions, it’s even more important given their elevated risk for severe illness.
What if you’ve had a COVID-19 infection recently? Getting vaccinated or boosted a few months after you’ve had a COVID-19 infection will offer you even better protection in the future.
So, if you are among the millions of Americans who’ve been vaccinated for COVID-19 but are now due for a booster, don’t delay. Get yourself boosted to protect your own health and the health of your loved ones as the holidays approach.
References:
[1] CDC recommends the first updated COVID-19 booster. Centers for Disease Control and Prevention. September 1, 2022.
[2] CDC expands updated COVID-19 vaccines to include children ages 5 through 11. Centers for Disease Control and Prevention, October 12, 2022.
[3] COVID-19 vaccinations in the United States. Centers for Disease Control and Prevention.
[4] Incidence of severe COVID-19 illness following vaccination and booster with BNT162b2, mRNA-1273, and Ad26.COV2.S vaccines. Kelly JD, Leonard S, Hoggatt KJ, Boscardin WJ, Lum EN, Moss-Vazquez TA, Andino R, Wong JK, Byers A, Bravata DM, Tien PC, Keyhani S. JAMA. 2022 Oct 11;328(14):1427-1437.
Links:
COVID-19 Research (NIH)
Dan Kelly (University of California, San Francisco)
NIH Support: National Institute of Allergy and Infectious Diseases
Understanding Long-Term COVID-19 Symptoms and Enhancing Recovery
Posted on by Walter J. Koroshetz, M.D., National Institute of Neurological Disorders and Stroke
We are in the third year of the COVID-19 pandemic, and across the world, most restrictions have lifted, and society is trying to get back to “normal.” But for many people—potentially millions globally—there is no getting back to normal just yet.
They are still living with the long-term effects of a COVID-19 infection, known as the post-acute sequelae of SARS-CoV-2 infection (PASC), including Long COVID. These people continue to experience debilitating fatigue, shortness of breath, pain, difficulty sleeping, racing heart rate, exercise intolerance, gastrointestinal and other symptoms, as well as cognitive problems that make it difficult to perform at work or school.
This is a public health issue that is in desperate need of answers. Research is essential to address the many puzzling aspects of Long COVID and guide us to effective responses that protect the nation’s long-term health.
For the past two years, NIH’s National Heart, Lung, and Blood Institute (NHLBI), the National Institute of Allergy and Infectious Diseases (NIAID), and my National Institute of Neurological Disorders and Stroke (NINDS) along with several other NIH institutes and the office of the NIH Director, have been leading NIH’s Researching COVID to Enhance Recovery (RECOVER) initiative, a national research program to understand PASC.
The initiative studies core questions such as why COVID-19 infections can have lingering effects, why new symptoms may develop, and what is the impact of SARS-CoV-2, the virus that causes COVID-19, on other diseases and conditions? Answering these fundamental questions will help to determine the underlying biologic basis of Long COVID. The answers will also help to tell us who is at risk for Long COVID and identify therapies to prevent or treat the condition.
The RECOVER initiative’s wide scope of research is also unprecedented. It is needed because Long COVID is so complex, and history indicates that similar post infectious conditions have defied definitive explanation or effective treatment. Indeed, those experiencing Long COVID report varying symptoms, making it highly unlikely that a single therapy will work for everyone, underscoring the need to pursue multiple therapeutic strategies.
To understand Long COVID fully, hundreds of RECOVER investigators are recruiting more than 17,000 adults (including pregnant people) and more than 18,000 children to take part in cohort studies. Hundreds of enrolling sites have been set up across the country. An autopsy research cohort will also provide further insight into how COVID-19 affects the body’s organs and tissues.
In addition, researchers will analyze electronic health records from millions of people to understand how Long COVID and its symptoms change over time. The RECOVER initiative is also utilizing consistent research protocols across all the study sites. The protocols have been carefully developed with input from patients and advocates, and they are designed to allow for consistent data collection, improve data sharing, and help to accelerate the pace of research.
From the very beginning, people suffering from Long COVID have been our partners in RECOVER. Patients and advocates have contributed important perspectives and provided valuable input into the master protocols and research plans.
Now, with RECOVER underway, individuals with Long COVID, their caregivers, and community members continue to serve a critical role in the Initiative. The National Community Engagement Group (NCEG) has been established to make certain that RECOVER meets the needs of all people affected by Long COVID. The RECOVER Patient and Community Engagement Strategy outlines all the approaches that RECOVER is using to engage with and gather input from individuals impacted by Long COVID.
The NIH recently made more than 40 awards to improve understanding of the underlying biology and pathology of Long COVID. There have already been several important findings published by RECOVER scientists.
For example, in a recent study published in the journal Lancet Digital Health, RECOVER investigators used machine learning to comb through electronic health records to look for signals that may predict whether someone has Long COVID [1]. As new findings, tools, and technologies continue to emerge that help advance our knowledge of the condition, the RECOVER Research Review (R3) Seminar Series will provide a forum for researchers and our partners with up-to-date information about Long COVID research.
It is important to note that post-viral conditions are not a new concept. Many, but not all, of the symptoms reported in Long COVID, including fatigue, post-exertional malaise, chronic musculoskeletal pain, sleep disorders, postural orthostatic tachycardia (POTS), and cognitive issues, overlap with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS).
ME/CFS is a serious disease that can occur following infection and make people profoundly sick for decades. Like Long COVID, ME/CFS is a heterogenous condition that does not affect everybody in the same way, and the knowledge gained through research on Long COVID may also positively impact the understanding, treatment, and prevention of POTS, ME/CFS, and other chronic diseases.
Unlike other post-viral conditions, people who experience Long COVID were all infected by the same virus—albeit different variants—at a similar point in time. This creates a unique opportunity for RECOVER researchers to study post-viral conditions in real-time.
The opportunity enables scientists to study many people simultaneously while they are still infected to monitor their progress and recovery, and to try to understand why some individuals develop ongoing symptoms. A better understanding of the transition from acute to chronic disease may offer an opportunity to intervene, identify who is at risk of the transition, and develop therapies for people who experience symptoms long after the acute infection has resolved.
The RECOVER initiative will soon announce clinical trials, leveraging data from clinicians and patients in which symptom clusters were identified and can be targeted by various interventions. These trials will investigate therapies that are indicated for other non-COVID conditions and novel treatments for Long COVID.
Through extensive collaboration across the multiple NIH institutes and offices that contribute to the RECOVER effort, our hope is critical answers will emerge soon. These answers will help us to recognize the full range of outcomes and needs resulting from PASC and, most important, enable many people to make a full recovery from COVID-19. We are indebted to the over 10,000 subjects who have already enrolled in RECOVER. Their contributions and the hard work of the RECOVER investigators offer hope for the future to the millions still suffering from the pandemic.
Reference:
[1] Identifying who has long COVID in the USA: a machine learning approach using N3C data. Pfaff ER, Girvin AT, Bennett TD, Bhatia A, Brooks IM, Deer RR, Dekermanjian JP, Jolley SE, Kahn MG, Kostka K, McMurry JA, Moffitt R, Walden A, Chute CG, Haendel MA; N3C Consortium. Lancet Digit Health. 2022 Jul;4(7):e532-e541.
Links:
COVID-19 Research (NIH)
Long COVID (NIH)
RECOVER: Researching COVID to Enhance Recovery (NIH)
“NIH builds large nationwide study population of tens of thousands to support research on long-term effects of COVID-19,” NIH News Release, September 15, 2021.
Director’s Messages (National Institute of Neurological Disorders and Stroke/NIH)
Note: Dr. Lawrence Tabak, who performs the duties of the NIH Director, has asked the heads of NIH’s Institutes and Centers (ICs) to contribute occasional guest posts to the blog to highlight some of the interesting science that they support and conduct. This is the 18th in the series of NIH IC guest posts that will run until a new permanent NIH director is in place.
Using AI to Advance Understanding of Long COVID Syndrome
Posted on by Lawrence Tabak, D.D.S., Ph.D.
The COVID-19 pandemic continues to present considerable public health challenges in the United States and around the globe. One of the most puzzling is why many people who get over an initial and often relatively mild COVID illness later develop new and potentially debilitating symptoms. These symptoms run the gamut including fatigue, shortness of breath, brain fog, anxiety, and gastrointestinal trouble.
People understandably want answers to help them manage this complex condition referred to as Long COVID syndrome. But because Long COVID is so variable from person to person, it’s extremely difficult to work backwards and determine what these people had in common that might have made them susceptible to Long COVID. The variability also makes it difficult to identify all those who have Long COVID, whether they realize it or not. But a recent study, published in the journal Lancet Digital Health, shows that a well-trained computer and its artificial intelligence can help.
Researchers found that computers, after scanning thousands of electronic health records (EHRs) from people with Long COVID, could reliably make the call. The results, though still preliminary and in need of further validation, point the way to developing a fast, easy-to-use computer algorithm to help determine whether a person with a positive COVID test is likely to battle Long COVID.
In this groundbreaking study, NIH-supported researchers led by Emily Pfaff, University of North Carolina, Chapel Hill, and Melissa Haendel, the University of Colorado Anschutz Medical Campus, Aurora, relied on machine learning. In machine learning, a computer sifts through vast amounts of data to look for patterns. One reason machine learning is so powerful is that it doesn’t require humans to tell the computer which features it should look for. As such, machine learning can pick up on subtle patterns that people would otherwise miss.
In this case, Pfaff, Haendel, and team decided to “train” their computer on EHRs from people who had reported a COVID-19 infection. (The records are de-identified to protect patient privacy.) The researchers found just what they needed in the National COVID Cohort Collaborative (N3C), a national, publicly available data resource sponsored by NIH’s National Center for Advancing Translational Sciences. It is part of NIH’s Researching COVID to Enhance Recovery (RECOVER) initiative, which aims to improve understanding of Long COVID.
The researchers defined a group of more than 1.5 million adults in N3C who either had been diagnosed with COVID-19 or had a record of a positive COVID-19 test at least 90 days prior. Next, they examined common features, including any doctor visits, diagnoses, or medications, from the group’s roughly 100,000 adults.
They fed that EHR data into a computer, along with health information from almost 600 patients who’d been seen at a Long COVID clinic. They developed three machine learning models: one to identify potential long COVID patients across the whole dataset and two others that focused separately on people who had or hadn’t been hospitalized.
All three models proved effective for identifying people with potential Long-COVID. Each of the models had an 85 percent or better discrimination threshold, indicating they are highly accurate. That’s important because, once researchers can identify those with Long COVID in a large database of people such as N3C, they can begin to ask and answer many critical questions about any differences in an individual’s risk factors or treatment that might explain why some get Long COVID and others don’t.
This new study is also an excellent example of N3C’s goal to assemble data from EHRs that enable researchers around the world to get rapid answers and seek effective interventions for COVID-19, including its long-term health effects. It’s also made important progress toward the urgent goal of the RECOVER initiative to identify people with or at risk for Long COVID who may be eligible to participate in clinical trials of promising new treatment approaches.
Long COVID remains a puzzling public health challenge. Another recent NIH study published in the journal Annals of Internal Medicine set out to identify people with symptoms of Long COVID, most of whom had recovered from mild-to-moderate COVID-19 [2]. More than half had signs of Long COVID. But, despite extensive testing, the NIH researchers were unable to pinpoint any underlying cause of the Long COVID symptoms in most cases.
So if you’d like to help researchers solve this puzzle, RECOVER is now enrolling adults and kids—including those who have and have not had COVID—at more than 80 study sites around the country.
References:
[1] Identifying who has long COVID in the USA: a machine learning approach using N3C data. Pfaff ER, Girvin AT, Bennett TD, Bhatia A, Brooks IM, Deer RR, Dekermanjian JP, Jolley SE, Kahn MG, Kostka K, McMurry JA, Moffitt R, Walden A, Chute CG, Haendel MA; N3C Consortium. Lancet Digit Health. 2022 May 16:S2589-7500(22)00048-6.
[2] A longitudinal study of COVID-19 sequelae and immunity: baseline findings. Sneller MC, Liang CJ, Marques AR, Chung JY, Shanbhag SM, Fontana JR, Raza H, Okeke O, Dewar RL, Higgins BP, Tolstenko K, Kwan RW, Gittens KR, Seamon CA, McCormack G, Shaw JS, Okpali GM, Law M, Trihemasava K, Kennedy BD, Shi V, Justement JS, Buckner CM, Blazkova J, Moir S, Chun TW, Lane HC. Ann Intern Med. 2022 May 24:M21-4905.
Links:
COVID-19 Research (NIH)
National COVID Cohort Collaborative (N3C) (National Center for Advancing Translational Sciences/NIH)
Emily Pfaff (University of North Carolina, Chapel Hill)
Melissa Haendel (University of Colorado, Aurora)
NIH Support: National Center for Advancing Translational Sciences; National Institute of General Medical Sciences; National Institute of Allergy and Infectious Diseases
All of Us: Release of Nearly 100,000 Whole Genome Sequences Sets Stage for New Discoveries
Posted on by Joshua Denny, M.D., M.S., and Lawrence Tabak, D.D.S., Ph.D.
Nearly four years ago, NIH opened national enrollment for the All of Us Research Program. This historic program is building a vital research community within the United States of at least 1 million participant partners from all backgrounds. Its unifying goal is to advance precision medicine, an emerging form of health care tailored specifically to the individual, not the average patient as is now often the case. As part of this historic effort, many participants have offered DNA samples for whole genome sequencing, which provides information about almost all of an individual’s genetic makeup.
Earlier this month, the All of Us Research Program hit an important milestone. We released the first set of nearly 100,000 whole genome sequences from our participant partners. The sequences are stored in the All of Us Researcher Workbench, a powerful, cloud-based analytics platform that makes these data broadly accessible to registered researchers.
The All of Us Research Program and its many participant partners are leading the way toward more equitable representation in medical research. About half of this new genomic information comes from people who self-identify with a racial or ethnic minority group. That’s extremely important because, until now, over 90 percent of participants in large genomic studies were of European descent. This lack of diversity has had huge impacts—deepening health disparities and hindering scientific discovery from fully benefiting everyone.
The Researcher Workbench also contains information from many of the participants’ electronic health records, Fitbit devices, and survey responses. Another neat feature is that the platform links to data from the U.S. Census Bureau’s American Community Survey to provide more details about the communities where participants live.
This unique and comprehensive combination of data will be key in transforming our understanding of health and disease. For example, given the vast amount of data and diversity in the Researcher Workbench, new diseases are undoubtedly waiting to be uncovered and defined. Many new genetic variants are also waiting to be identified that may better predict disease risk and response to treatment.
To speed up the discovery process, these data are being made available, both widely and wisely. To protect participants’ privacy, the program has removed all direct identifiers from the data and upholds strict requirements for researchers seeking access. Already, more than 1,500 scientists across the United States have gained access to the Researcher Workbench through their institutions after completing training and agreeing to the program’s strict rules for responsible use. Some of these researchers are already making discoveries that promote precision medicine, such as finding ways to predict how to best to prevent vision loss in patients with glaucoma.
Beyond making genomic data available for research, All of Us participants have the opportunity to receive their personal DNA results, at no cost to them. So far, the program has offered genetic ancestry and trait results to more than 100,000 participants. Plans are underway to begin sharing health-related DNA results on hereditary disease risk and medication-gene interactions later this year.
This first release of genomic data is a huge milestone for the program and for health research more broadly, but it’s also just the start. The program’s genome centers continue to generate the genomic data and process about 5,000 additional participant DNA samples every week.
The ultimate goal is to gather health data from at least 1 million or more people living in the United States, and there’s plenty of time to join the effort. Whether you would like to contribute your own DNA and health information, engage in research, or support the All of Us Research Program as a partner, it’s easy to get involved. By taking part in this historic program, you can help to build a better and more equitable future for health research and precision medicine.
Note: Joshua Denny, M.D., M.S., is the Chief Executive Officer of NIH’s All of Us Research Program.
Links:
All of Us Research Program (NIH)
Join All of Us (NIH)
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