Diagnostic Stewardship of Blood Cultures in the Pediatric ICU Using Machine Learning.

Journal: Hospital pediatrics
Published Date: Jun 1, 2025

Abstract

OBJECTIVE: The medical community recently experienced a severe shortage of blood culture media bottles. Rates of blood stream infection (BSI) among critically ill children are low. We sought to design a machine learning (ML) model able to identify children at low risk for BSI to improve blood culture diagnostic stewardship.

Authors

  • Blake Martin
    Departments of Biomedical Informatics and Pediatrics (Critical Care Medicine), University of Colorado School of Medicine, Aurora, CO.
  • Peter E DeWitt
    Department of Biomedical Informatics, University of Colorado School of Medicine, Aurora, Colorado.
  • Marisa Payan
    Research Informatics and Data Science, Children's Hospital Colorado, Aurora, Colorado.
  • Christopher H Greer
    Precision Medicine Institute, Children's Hospital Colorado, Aurora, Colorado.
  • Seth Russell
    Data Science to Patient Value (D2V) Initiative, University of Colorado School of Medicine, Aurora, CO.
  • Charlotte Gray
    Department of Biomedical Informatics, University of Colorado School of Medicine, Aurora, Colorado.
  • Sara J Deakyne Davies
    Research Informatics and Data Science, Children's Hospital Colorado, Aurora, Colorado.
  • Charlotte Z Woods-Hill
    Department of Anesthesiology and Critical Care Medicine, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania.
  • Halden F Scott
    Section of Emergency Medicine, Department of Pediatrics, University of Colorado School of Medicine, Aurora, Colorado.
  • Sarah Parker
    Section of Infectious Disease, Department of Pediatrics, University of Colorado School of Medicine, Aurora, Colorado.
  • David Albers
    Department of Biomedical Informatics, Columbia University, N.Y., USA.
  • Tellen D Bennett
    Section of Informatics and Data Science, Department of Pediatrics, University of Colorado School of Medicine, Aurora, CO.

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