Utilizing large language models for detecting hospital-acquired conditions: an empirical study on pulmonary embolism.

Journal: Journal of the American Medical Informatics Association : JAMIA
PMID: 40105654

Abstract

OBJECTIVES: Adverse event detection from Electronic Medical Records (EMRs) is challenging due to the low incidence of the event, variability in clinical documentation, and the complexity of data formats. Pulmonary embolism as an adverse event (PEAE) is particularly difficult to identify using existing approaches. This study aims to develop and evaluate a Large Language Model (LLM)-based framework for detecting PEAE from unstructured narrative data in EMRs.

Authors

  • Cheligeer Cheligeer
    The Centre for Health Informatics, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.
  • Danielle A Southern
    Centre for Health Informatics, Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.
  • Jun Yan
    Department of Statistics, University of Connecticut, Storrs, CT 06269, USA.
  • Guosong Wu
    Centre for Health Informatics, Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.
  • Jie Pan
  • Seungwon Lee
    Department of Computer and Information Science, University of Pennsylvania, Philadelphia, PA, USA.
  • Elliot A Martin
    Centre for Health Informatics, University of Calgary, Calgary, Canada; Health Research Methods and Analytics, Alberta Health Services, Calgary, Canada. Electronic address: eamartin@ucalgary.ca.
  • Hamed Jafarpour
    Concordia Institute for Information Systems Engineering, Concordia University, Montreal H3G 2W1, Canada.
  • Cathy A Eastwood
    Centre for Health Informatics, University of Calgary, Calgary, Canada; Department of Community Health Science, University of Calgary, Calgary, Canada.
  • Yong Zeng
    a College of Pharmacy , Chengdu University of Traditional Chinese Medicine , Chengdu , P.R. China.
  • Hude Quan
    Department of Community Health Sciences, University of Calgary, Calgary, Canada.

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