Detecting emergencies in patient portal messages using large language models and knowledge graph-based retrieval-augmented generation.

Journal: Journal of the American Medical Informatics Association : JAMIA
Published Date: Jun 1, 2025

Abstract

OBJECTIVES: This study aims to develop and evaluate an approach using large language models (LLMs) and a knowledge graph to triage patient messages that need emergency care. The goal is to notify patients when their messages indicate an emergency, guiding them to seek immediate help rather than using the patient portal, to improve patient safety.

Authors

  • Siru Liu
    School of Medicine, University of Utah, Salt Lake City, Utah, US.
  • Aileen P Wright
    Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37212, United States.
  • Allison B McCoy
    Vanderbilt University Medical Center, Nashville, TN.
  • Sean S Huang
    Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37212, United States.
  • Bryan Steitz
    Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37203, United States.
  • Adam Wright
    Harvard Medical School, Boston, MA; Brigham and Women's Hospital, Boston, MA.

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