Using Natural Language Processing to Predict Fatal Drug Overdose From Autopsy Narrative Text: Algorithm Development and Validation Study.

Journal: JMIR public health and surveillance
PMID: 37204824

Abstract

BACKGROUND: Fatal drug overdose surveillance informs prevention but is often delayed because of autopsy report processing and death certificate coding. Autopsy reports contain narrative text describing scene evidence and medical history (similar to preliminary death scene investigation reports) and may serve as early data sources for identifying fatal drug overdoses. To facilitate timely fatal overdose reporting, natural language processing was applied to narrative texts from autopsies.

Authors

  • Leigh Anne Tang
    Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, United States.
  • Jessica Korona-Bailey
    Office of Informatics and Analytics, Tennessee Department of Health, Nashville, TN, United States.
  • Dimitrios Zaras
    Office of Informatics and Analytics, Tennessee Department of Health, Nashville, TN, United States.
  • Allison Roberts
    Office of Informatics and Analytics, Tennessee Department of Health, Nashville, TN, United States.
  • Sutapa Mukhopadhyay
    Office of Informatics and Analytics, Tennessee Department of Health, Nashville, TN, United States.
  • Stephen Espy
    Office of Informatics and Analytics, Tennessee Department of Health, Nashville, TN, United States.
  • Colin G Walsh
    Vanderbilt University Medical Center, Vanderbilt University, Nashville, TN, United States.

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