Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2025 Mar 5:27:e59217.
doi: 10.2196/59217.

Opportunities and Challenges in Using Electronic Health Record Systems to Study Postacute Sequelae of SARS-CoV-2 Infection: Insights From the NIH RECOVER Initiative

Hannah L Mandel  1 , Shruti N Shah  1 , L Charles Bailey  2 , Thomas Carton  3 , Yu Chen  1 , Shari Esquenazi-Karonika  1 , Melissa Haendel  4 , Mady Hornig  5 , Rainu Kaushal  6 , Carlos R Oliveira  7   8 , Alice A Perlowski  9 , Emily Pfaff  10 , Suchitra Rao  11 , Hanieh Razzaghi  2 , Elle Seibert  12 , Gelise L Thomas  13 , Mark G Weiner  6 , Lorna E Thorpe  1 , Jasmin Divers  14 ; RECOVER EHR Cohort  15
Affiliations

Opportunities and Challenges in Using Electronic Health Record Systems to Study Postacute Sequelae of SARS-CoV-2 Infection: Insights From the NIH RECOVER Initiative

Hannah L Mandel et al. J Med Internet Res. .

Abstract

The benefits and challenges of electronic health records (EHRs) as data sources for clinical and epidemiologic research have been well described. However, several factors are important to consider when using EHR data to study novel, emerging, and multifaceted conditions such as postacute sequelae of SARS-CoV-2 infection or long COVID. In this article, we present opportunities and challenges of using EHR data to improve our understanding of long COVID, based on lessons learned from the National Institutes of Health (NIH)-funded RECOVER (REsearching COVID to Enhance Recovery) Initiative, and suggest steps to maximize the usefulness of EHR data when performing long COVID research.

Keywords: COVID-19; Long COVID, post-acute COVID-19 syndrome; SARS-CoV-2; clinical data research network; clinical research network; common data model; digital health; electronic health record data; electronic health record network; electronic health records; electronic medical record; epidemiological; infection; infectious; machine learning; medical informatics; pandemic; post-infection syndrome; public health surveillance; respiratory.

PubMed Disclaimer

Conflict of interest statement

Conflicts of Interest: LCB, TC, EP, HR, and MW report funding from the Patient-Centered Outcomes Research Institute. HR, LCB, TC, EP, and MW report research funding from the NIH. LCB reports research funding from the National Institute of Diabetes and Digestive and Kidney Diseases, and Centers for Disease Control and Prevention. CO has received grants from the National Institutes of Allergy and Infectious Diseases, has a council role with the Eastern Society of Pediatric Research, and received an honorarium from the NIH. EP reports consulting fees from the NIH and a speaker honorarium from Cincinnati Children’s Hospital. SR has received consulting fees from Sequiris. All other authors declare no competing interests.

References

    1. Woodrow M, Carey C, Ziauddeen N, Thomas R, Akrami A, Lutje V, Greenwood DC, Alwan NA. Systematic review of the prevalence of long COVID. Open Forum Infect Dis. 2023;10(7):ofad233. doi: 10.1093/ofid/ofad233. https://europepmc.org/abstract/MED/37404951 ofad233 - DOI - PMC - PubMed
    1. Brown K, Yahyouche A, Haroon S, Camaradou J, Turner G. Long COVID and self-management. Lancet. 2022;399(10322):355. doi: 10.1016/S0140-6736(21)02798-7. https://europepmc.org/abstract/MED/35065779 S0140-6736(21)02798-7 - DOI - PMC - PubMed
    1. RECOVER: researching COVID to enhance recovery. Recover. [2025-01-16]. https://recovercovid.org .
    1. Thygesen JH, Tomlinson C, Hollings S, Mizani MA, Handy A, Akbari A, Banerjee A, Cooper J, Lai AG, Li K, Mateen BA, Sattar N, Sofat R, Torralbo A, Wu H, Wood A, Sterne JAC, Pagel C, Whiteley WN, Sudlow C, Hemingway H, Denaxas S, Longitudinal Health and Wellbeing COVID-19 National Core Study and the CVD-COVID-UK/COVID-IMPACT Consortium COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records. Lancet Digit Health. 2022;4(7):e542–e557. doi: 10.1016/S2589-7500(22)00091-7. https://linkinghub.elsevier.com/retrieve/pii/S2589-7500(22)00091-7 S2589-7500(22)00091-7 - DOI - PMC - PubMed
    1. Lam ICH, Wong CKH, Zhang R, Chui CSL, Lai FTT, Li X, Chan EWY, Luo H, Zhang Q, Man KKC, Cheung BMY, Tang SCW, Lau CS, Wan EYF, Wong ICK. Long-term post-acute sequelae of COVID-19 infection: a retrospective, multi-database cohort study in Hong Kong and the UK. EClinicalMedicine. 2023;60:102000. doi: 10.1016/j.eclinm.2023.102000. https://linkinghub.elsevier.com/retrieve/pii/S2589-5370(23)00177-3 S2589-5370(23)00177-3 - DOI - PMC - PubMed

LinkOut - more resources