aceLarge Language Models in the Emergency Department: Fairness Implications for Clinicians
Applications of artificial intelligence (AI), particularly large language models (LLMs), are rapidly expanding in emergency medicine, but concerns remain regarding their fairness across diverse patient populations. Fairness extends beyond model accuracy and includes equal performance across patient groups, equitable outcomes and allocation of clinical benefits, and procedural fairness throughout the lifecycle of AI implementation. This narrative review aims to provide a practical framework for understanding and…
AI and LLM tools in emergency care can produce subgroup-specific errors and unequal benefits across patient groups, even when overall model performance appears strong.
The source is a narrative review offering a conceptual framework, and it does not report measured rates of unfair performance or outcomes in emergency departments.
Evidence
- Peer-reviewedClinical and Experimental Emergency Medicine2026-10-15
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Truvace Impact Record TRV-2026-1559, v1: “Large Language Models in the Emergency Department: Fairness Implications for Clinicians.” Truvace, 2026-10-16. /record/TRV-2026-1559 (accessed at citation time). sha256 9391a8bdc0a6af5e…
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