Potential bias and lack of generalizability in electronic health record data: reflections on health equity from the National Institutes of Health Pragmatic Trials Collaboratory
Recommended Citation
Boyd AD, Gonzalez-Guarda R, Lawrence K, Patil CL, Ezenwa MO, O'Brien EC, Paek H, Braciszewski JM, Adeyemi O, Cuthel AM, Darby JE, Zigler CK, Ho PM, Faurot KR, Staman KL, Leigh JW, Dailey DL, Cheville A, Del Fiol G, Knisely MR, Grudzen CR, Marsolo K, Richesson RL, and Schlaeger JM. Potential bias and lack of generalizability in electronic health record data: reflections on health equity from the National Institutes of Health Pragmatic Trials Collaboratory. J Am Med Inform Assoc 2023.
Document Type
Article
Publication Date
6-26-2023
Publication Title
Journal of the American Medical Informatics Association : JAMIA
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.
PubMed ID
37364017
ePublication
ePub ahead of print
