Breaking Digital Health Barriers: Development and Validation of an LLM-Based Tool for Automated OMOP Mapping.

Journal: Journal of medical Internet research
Published Date: May 15, 2025

Abstract

BACKGROUND: The integration of diverse clinical data sources requires standardization through models like OMOP (Observational Medical Outcomes Partnership). However, mapping data elements to OMOP concepts demands significant technical expertise and time. While large healthcare systems often have resources for OMOP conversion, smaller clinical trials and studies frequently lack such support, leaving valuable research data siloed.

Authors

  • Meredith C B Adams
    Department of Anesthesiology, Artificial Intelligence, Translational Neuroscience, and Public Health Sciences, Wake Forest University School of Medicine, Medical Center Boulevard, Winston-Salem, US.
  • Matthew L Perkins
    Department of Cancer Biology, Wake Forest University School of Medicine, Winston-Salem, US.
  • Cody Hudson
    Department of Cancer Biology, Wake Forest University School of Medicine, Winston-Salem, US.
  • Vithal Madhira
    Palila Software LLC, Reno, US.
  • Oguz Akbilgic
    1Department of Pediatrics, University of Tennessee Health Science Center - Oak Ridge National Laboratory- (UTHSC-ORNL), Center for Biomedical Informatics, Memphis, TN USA.
  • Da Ma
    School of Engineering Science, Simon Fraser University, Burnaby, Canada.
  • Robert W Hurley
    Department of Anesthesiology, Translational Neuroscience, and Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, US.
  • Umit Topaloglu
    Clinical Translational Research Informatics Branch, National Cancer Institute, Bethesda, US.

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