Bias and Disparities in the Electronic Health Record

In Matthew C. Altman & David Schwan, Ethics and Medical Technology: Essays on Artificial Intelligence, Enhancement, Privacy, and Justice. Cham: Springer Nature Switzerland. pp. 245-260 (2025)
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Abstract

Healthcare disparities, characterized by systematic differences in health outcomes among demographic groups, are often driven by bias, both explicit and implicit. Electronic Health Records (EHRs), integral to modern healthcare, pose unique bias and equity risks in healthcare delivery, which arise through EHR design, data entry, management practices, and clinical decision support tools. This chapter explores these risks and opportunities, identifying the “Four D’s of a Bias-D EHR” system—design, data, documentation, and care delivery. It offers strategies to mitigate bias and emphasizes the importance of addressing these issues to promote health equity. Ensuring that EHR systems support fair, unbiased care is essential to improving outcomes across minoritized patient populations.

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