Emergency rooms can now measure how age, race, and language affect triage

Researchers used real hospital data to measure how factors like age, race, and language affect emergency room triage decisions. It turns out these factors lead to measurable differences in how quickly patients are seen, how often their cases are re-evaluated, and what care they receive.

Hospitals have known that patient demographics can affect care, but it was hard to prove exactly how. This paper shows specific ways age, race, language, and insurance status lead to different outcomes in emergency triage. It gives hospitals and AI developers a concrete way to audit their systems and find where unfairness happens.