EQUITRIAGE: Comprehensive Fairness Audit Reveals Gender Bias in LLM-Based Emergency Triage Models

A study titled EQUITRIAGE investigates the fairness of large language models (LLMs) used in emergency department triage, focusing on gender bias during acuity assessments. The research evaluates five LLMs across 374,275 assessments and identifies significant flip rates, ranging from 9.9% to 43.8%, exceeding the pre-registered threshold. Findings indicate that two models demonstrated a tendency towards female undertriage, while two others showed near-parity. The results highlight the distinct fairness properties of group parity, counterfactual invariance, and gender calibration. Notably, demographic blinding significantly reduced flip rates, suggesting that age and gender biases are intertwined in triage decisions. The study emphasizes the necessity for per-model counterfactual auditing prior to clinical implementation.