“How Ai Can Remedy Racial Disparities in Healthcare.” Forbes Magazine, 15 Feb. Potential to address racial disparities: Pearl, R. “Dissecting Racial Bias in an Algorithm Used to Manage the Health of Populations.” Science, 36(6464):447-53, October 25, 2019 Racial Bias in Other Health Care Algorithms Obermeyer Z, Powers B, Vogeli C, and Mullainathan S. ![]() Thus, race is not included in the heartįailure risk score used by hospitals in Get With The Guidelines® - Heart Failure. Letter states that while race was included as a variable in the publication, Get With The Guidelines® clinical thought leaders elected not to include race in the model programmed into the registry.NOTE: Get with the Guidelines–Heart Failure Risk Score: American Hearth Association Letter to the House Committee on Ways and Means, September 24, 2020. STONE Score: American College of Emergency Physicians letter to the House Committee on Ways and Means, December 4, 2020.“Researchers Remove Race from a Calculator for Childbirth.” STAT, 3 June 2021. The Vaginal Birth after Cesarean: Katie Palmer June, et al.“New Creatinine- AND Cystatin C–Based Equations to Estimate GFR without Race.” New England Journal of Medicine, 2021. “Hidden in Plain Sight - Reconsidering the Use of Race Correction in Clinical Algorithms.” New England Journal of Medicine, vol. Racial Bias in Clinical Care Algorithms and Examples of Race Correction in Clinical Medicine: Vyas, Darshali A., et al. This infographic highlights strategies to address bias in algorithms and the potential for AI to support health equity. ![]() It also shows how health care AI tools use data that inadvertently capture systemic racism, adding to existing inequities in health care access and status. ![]() This new infographic shows how embedding race into health care data and decisions can unintentionally advance racial health disparities and direct more attention or resources to White patients rather than Black, Latino, and other medically underserved patient populations. Despite evidence that race is not a reliable proxy for genetic differences, how to allocate clinical resources or treatment adherence, using race as a factor has become a common practice when designing clinical algorithms. These tools can unintentionally increase the impact of existing racial biases in medicine through the explicit use of race to predict outcomes and risk. Artificial intelligence (AI) tools such as algorithms are increasingly being used to determine who gets health care.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |