Potential bias and lack of generalizability in electronic health record data: Reflections on health equity from the National Institutes of Health Pragmatic Trials Collaboratory Guidelines


Authors: Boyd, A. D.; Gonzalez-Guarda, R.; Lawrence, K.; Patil, C. L.; Ezenwa, M. O.; O'Brien, E. C.; Paek, H.; Braciszewski, J. M.; Adeyemi, O.; Cuthel, A. M.; Darby, J. E.; Zigler, C. K.; Ho, P. M.; Faurot, K. R.; Staman, K. L.; Leigh, J. W.; Dailey, D. L.; Cheville, A.; Del Fiol, G.; Knisely, M. R.; Grudzen, C. R.; Marsolo, K.; Richesson, R. L.; Schlaeger, J. M.
Title: Potential bias and lack of generalizability in electronic health record data: Reflections on health equity from the National Institutes of Health Pragmatic Trials Collaboratory
Abstract: Embedded pragmatic clinical trials (ePCTs) play a vital role in addressing current population health problems, and their use of electronic health record (EHR) systems promises efficiencies that will increase the speed and volume of relevant and generalizable research. However, as the number of ePCTs using EHR-derived data grows, so does the risk that research will become more vulnerable to biases due to differences in data capture and access to care for different subsets of the population, thereby propagating inequities in health and the healthcare system. We identify 3 challenges-incomplete and variable capture of data on social determinants of health, lack of representation of vulnerable populations that do not access or receive treatment, and data loss due to variable use of technology-that exacerbate bias when working with EHR data and offer recommendations and examples of ways to actively mitigate bias. © The Author(s) 2023. Published by Oxford University Press on behalf of the American Medical Informatics Association.
Keywords: united states; patient-reported outcomes; health care delivery; national health organization; national institutes of health (u.s.); delivery of health care; bias; health literacy; electronic health records; humans; human; social determinants of health; electronic health record; statistical bias; health equity; community engagement
Journal Title: Journal of the American Medical Informatics Association
Volume: 30
Issue: 9
ISSN: 1067-5027
Publisher: Oxford University Press  
Date Published: 2023-09-01
Start Page: 1561
End Page: 1566
Language: English
DOI: 10.1093/jamia/ocad115
PUBMED: 37364017
PROVIDER: scopus
PMCID: PMC10436149
DOI/URL:
Notes: Article -- Source: Scopus
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  1. Corita Reilley Grudzen
    31 Grudzen