Visweswaran Shyam, Sadhu Eugene M, Morris Michele M, Vis Anushka R, Samayamuthu Malarkodi Jebathilagam
Department of Biomedical Informatics, University of Pittsburgh, 5607 Baum Boulevard, Pittsburgh, PA, USA.
Intelligent Systems Program, University of Pittsburgh, Pittsburgh, PA, USA.
Sci Rep. 2025 Mar 29;15(1):10913. doi: 10.1038/s41598-025-94152-5.
Some clinical algorithms incorporate an individual's race, ethnicity, or both as an input variable or predictor in determining diagnoses, prognoses, treatment plans, or risk assessments. Inappropriate use of race and ethnicity in clinical algorithms at the point of care may exacerbate health disparities and promote harmful practices of race-based medicine. Using database analysis primarily, we identified 42 risk calculators that use race and ethnicity as predictors, five laboratory test results with reference ranges that differed based on race and ethnicity, one therapy recommendation based on race and ethnicity, 15 medications with race- and ethnicity-based initiation and monitoring guidelines, and five medical devices with differential racial and ethnic performances. Information on these clinical algorithms is freely available at https://www.clinical-algorithms-with-race-and-ethnicity.org/ . This resource aims to raise awareness about the use of race and ethnicity in clinical algorithms and track progress toward eliminating their inappropriate use. The database is actively updated to include clinical algorithms that were missed and additional characteristics of these algorithms.
一些临床算法将个人的种族、族裔或两者都作为输入变量或预测因素,用于确定诊断、预后、治疗方案或风险评估。在医疗护理过程中,临床算法对种族和族裔的不当使用可能会加剧健康差距,并助长基于种族的医学的有害做法。我们主要通过数据库分析,识别出42种将种族和族裔作为预测因素的风险计算器、5种参考范围因种族和族裔而异的实验室检测结果、1种基于种族和族裔的治疗建议、15种有基于种族和族裔的起始及监测指南的药物,以及5种具有不同种族和族裔性能的医疗设备。有关这些临床算法的信息可在https://www.clinical-algorithms-with-race-and-ethnicity.org/上免费获取。该资源旨在提高人们对临床算法中种族和族裔使用情况的认识,并跟踪在消除其不当使用方面取得的进展。该数据库会不断更新,以纳入遗漏的临床算法以及这些算法的其他特征。