Use of a large language model integrated within the electronic medical record for the evaluation of surgical site infections – Northern California, 2025

Infection Control and Hospital Epidemiology 2026 Open access

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Authors: Eugenia H. Miranti, Timothy Keyes, Alvaro Ayala, Nerissa Ambers, Gina Newman, Elmer de Leon, Erika Paola Viana-Cardenas, Wajeeha Tariq, Mindy Marie Sampson, Jorge L. Salinas
DOI: 10.1017/ice.2026.10432
Cited by: 1
References: 5

Abstract

Our study evaluated a large language model (gpt-4o-mini) for surgical site infection (SSI) adjudication, achieving 100% sensitivity but 69.4% specificity. While reducing the manual screening workload by 66%, the agent generated many false positives, underscoring the need for refined models to improve specificity without compromising accuracy.

Fields of Study & Subjects

Surgical site infection prevention Sepsis Diagnosis and Treatment Bacterial Identification and Susceptibility Testing

Publication details

Journal / source
Infection Control and Hospital Epidemiology
Publisher
Cambridge University Press (CUP)
Volume
47
Issue
6
Pages
633–635
Publication date
13 April 2026
Language
EN