Equity and bias in electronic health records data

• Published in: Contemporary clinical trials Vol. 130; p. 107238
• Main Authors: Boyd, Andrew D., Gonzalez-Guarda, Rosa, Lawrence, Katharine, Patil, Crystal L., Ezenwa, Miriam O., O'Brien, Emily C., Paek, Hyung, Braciszewski, Jordan M., Adeyemi, Oluwaseun, Cuthel, Allison M., Darby, Juanita E., Zigler, Christina K., Ho, P. Michael, Faurot, Keturah R., Staman, Karen, Leigh, Jonathan W., Dailey, Dana L., Cheville, Andrea, Del Fiol, Guilherme, Knisely, Mitchell R., Marsolo, Keith, Richesson, Rachel L., Schlaeger, Judith M.
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.07.2023
• Subjects: Bias; Cardiovascular; Community engagement; Data Accuracy; Electronic Health Records; Health Equity; Health literacy; Health Promotion; Hematology, Oncology, and Palliative Medicine; Humans; Patient-reported outcomes; Social determinants of health; Community engagement; Social determinants of health; Health literacy; Health equity; Patient-reported outcomes
• ISSN: 1551-7144; 1559-2030; 1559-2030
• DOI: 10.1016/j.cct.2023.107238

Embedded pragmatic clinical trials (ePCTs) are conducted during routine clinical care and have the potential to increase knowledge about the effectiveness of interventions under real world conditions. However, many pragmatic trials rely on data from the electronic health record (EHR) data, which are subject to bias from incomplete data, poor data quality, lack of representation from people who are medically underserved, and implicit bias in EHR design. This commentary examines how the use of EHR data might exacerbate bias and potentially increase health inequities. We offer recommendations for how to increase generalizability of ePCT results and begin to mitigate bias to promote health equity.