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Introduction
Many health systems depend on prediction algorithms to identify and help patients with various health conditions. Some of these algorithms, however, exhibit significant racial bias and result in millions of people of color being overlooked medically and treated inequitably. On July 6, 2023, the Roundtable on the Promotion of Health Equity hosted a 1-day virtual workshop to discuss the premise, history, and development of race-based clinical algorithms and their effect on the health of people of color and on health inequities. The workshop, Examining the History, Consequences, and Effects of Race-Based Clinical Algorithms on Health Equity, explored underlying assumptions of racial differences in physiology. It also examined parameters for identifying instances when race and ethnicity as social constructs are legitimate considerations in efforts to improve health equity (e.g., when promoting outreach, screening, and community education and engagement). The contents of this workshop proceedings are based on the discussion of the individual workshop participants and should not be misconstrued as consensus.1
This publication is organized into 4 chapters. Chapter 1 provides an outline to the report structure. The full workshop statement of task can
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1 The planning committee’s role was limited to planning the workshop, and the Proceedings of a Workshop has been prepared by the workshop rapporteurs as a factual summary of what occurred at the workshop. Statements, recommendations, and opinions expressed are those of individual presenters and participants, and are not necessarily endorsed or verified by the National Academies of Sciences, Engineering, and Medicine, and they should not be construed as reflecting any group consensus.
be found in Appendix A. Chapters 2 through 4 include highlights from the presentations given by speakers and discussions among panel members. Chapter 2, titled History of Race-Based Clinical Algorithms and Their Implication on Achieving Health Equity, provides an overview of the historical and ideological origins of race-based algorithms and their use in predictive clinical models. Chapter 3, Moving From Race-Based to Race-Conscious Medicine to Address Health Inequities, discusses the use of race-free equations and provides an example of the appropriate use of race to improve diabetes screening. Chapter 4, Efforts to Promote Race-Conscious Medicine in Health Organizations and Systems, highlights examples of strategies used by organizations to move towards race-conscious medicine. The workshop agenda is provided in Appendix B, speaker biosketches can be found in Appendix C, and moderator and planning committee member biosketches are in Appendix D.
