Exploring the impact of missingness on racial disparities in predictive performance of a machine learning model for emergency department triage.

Journal: JAMIA open
Published Date: Dec 20, 2023

Abstract

OBJECTIVE: To investigate how missing data in the patient problem list may impact racial disparities in the predictive performance of a machine learning (ML) model for emergency department (ED) triage.

Authors

  • Stephanie Teeple
    Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19143, United States.
  • Aria Smith
    Department of Emergency Medicine, Johns Hopkins University, Baltimore, MD 21218, United States.
  • Matthew Toerper
    Department of Emergency Medicine, Johns Hopkins University, Baltimore, MD 21218, United States.
  • Scott Levin
    Department of Emergency Medicine, Johns Hopkins University, Baltimore, MD 21218, United States.
  • Scott Halpern
    Palliative and Advanced Illness Research (PAIR) Center, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, United States.
  • Oluwakemi Badaki-Makun
    Department of Pediatric Emergency Medicine, Johns Hopkins University, Baltimore, MD 21218, United States.
  • Jeremiah Hinson
    Department of Emergency Medicine, Johns Hopkins University, Baltimore, MD 21218, United States.

Keywords

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