Since 2019, medical societies have reconsidered race-specific clinical equations often in parallel to and largely independent from algorithmic fairness research. Focusing on lung function reference algorithms that affect medical care, insurance, and employment for hundreds of millions globally, we analyze the transition from race-specific GLI-2012 to race-averaged GLI-Global through a fairness lens. Drawing on historical context, citation analysis, and quantitative evaluation, we show (i) limited cross-citation between FAccT and clinical guideline revision efforts; (ii) that GLI-Global implicitly encodes assumptions about social determinants of health, behaving as if ~62% of the Black-White gap in FEV1 is exposure-related; and (iii) clinical validation studies operationalized a sufficiency-like fairness criterion long before its formalization in fairness literature, while neglecting foundational results such as the impossibility theorem has led to inefficiencies in clinical research. Overall, our analysis highlights the value of deeper, mutually beneficial engagement between medical and fairness communities and the public to accelerate progress toward equitable healthcare algorithms.

翻译：自2019年以来，医学界开始重新考虑种族特异性临床公式，这一进程与算法公平性研究大体平行且相互独立。以影响全球数亿人医疗保健、保险和就业的肺功能参考算法为焦点，我们通过公平性视角分析了从种族特异性GLI-2012算法向种族平均化GLI-Global算法的转变。结合历史背景、引文分析和定量评估，我们发现：(i) FAccT与临床指南修订工作之间的交叉引用有限；(ii) GLI-Global隐含地编码了关于健康社会决定因素的假设，表现为约62%的黑白人群FEV1差异与暴露因素相关；(iii) 临床验证研究早在其正式纳入公平性文献之前就已实际操作了类似充分性的公平性准则，而忽视基本结论（如不可能性定理）已导致临床研究效率低下。总体而言，我们的分析凸显了医学界、公平性研究界及公众之间深化互利合作对于加速实现公平医疗算法的重要性。