Peer-Reviewed Publication
JAMIA Open2026;9(3):ooag081.June 1, 2026Journal Article
Strategies for mitigating artificial intelligence bias in healthcare: a systematic review.
Kais Gadhoumi1, Rashaud Senior2,3, Sijia Wei4, Leila Ledbetter5, Michael D Green3, Bethany D Bonner3,6, Yvonne Mosley7, Katie Seidler3,8, Kristle Green8, Donghwan Lee1, Chuan Hong3, Vincent Guilamo Ramos9, Michael P Cary1,3
1Duke University School of Nursing, Durham, NC, 27710, United States.
2Avance Care, Raleigh, NC, United States.
3Duke University School of Medicine, Durham, NC, 27710, United States.
4Feinberg School of Medicine and Kellogg School of Management, Northwestern University, Chicago, IL, United States.
5Evidence Synthesis Information Scientist at the Virginia Tech Blacksburg, VA, 24061, United States.
6Triad HealthCare Network, Greensboro, NC, 27401, United States.
7Belk College of Business, University of North Carolina at Charlotte, Charlotte, NC, 28223, United States.
8Food and Drug Administration, Silver Spring, MD, 20993, United States.
9Johns Hopkins School of Nursing, Baltimore, MD, 20001, United States.
Abstract
OBJECTIVES: Artificial intelligence is used in healthcare to identify and manage health conditions across diverse patient populations and clinical settings, but biases in algorithms can perpetuate and exacerbate inequalities in health and healthcare delivery. While some research has focused on addressing this critical issue, there is a lack of comprehensive information on the types of strategies e…
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