A 12-hospital prospective evaluation of a clinical decision support prognostic algorithm based on logistic regression as a form of machine learning to facilitate decision making for patients with suspected COVID-19.

Journal: PloS one
Published Date:

Abstract

OBJECTIVE: To prospectively evaluate a logistic regression-based machine learning (ML) prognostic algorithm implemented in real-time as a clinical decision support (CDS) system for symptomatic persons under investigation (PUI) for Coronavirus disease 2019 (COVID-19) in the emergency department (ED).

Authors

  • Monica I Lupei
    Division of Critical Care, Department of Anesthesiology, University of Minnesota Medical School, Minneapolis, Minnesota, United States of America.
  • Danni Li
    Radiology Department, The People's Hospital of Lezhi, Ziyang, Sichuan, China.
  • Nicholas E Ingraham
    Division of Pulmonary and Critical Care, Department of Medicine, University of Minnesota Medical School, Minneapolis, Minnesota, United States of America.
  • Karyn D Baum
    Division of General Internal Medicine, Department of Medicine, Section of Hospital Medicine, University of Minnesota Medical School, Minneapolis, Minnesota, United States of America.
  • Bradley Benson
    Division of General Internal Medicine, Department of Medicine, Section of Hospital Medicine, University of Minnesota Medical School, Minneapolis, Minnesota, United States of America.
  • Michael Puskarich
    Department of Emergency Medicine, University of Minnesota Medical School, Minneapolis, Minnesota, United States of America.
  • David Milbrandt
    Department of Emergency Medicine, University of Minnesota Medical School, Minneapolis, Minnesota, United States of America.
  • Genevieve B Melton
    Institute for Health Informatics, University of Minnesota, Minneapolis, Minnesota, USA.
  • Daren Scheppmann
    Institute for Health Informatics, University of Minnesota, Minneapolis, Minnesota, United States of America.
  • Michael G Usher
    Division of General Internal Medicine, Department of Medicine, Section of Hospital Medicine, University of Minnesota Medical School, Minneapolis, Minnesota, United States of America.
  • Christopher J Tignanelli
    From the Department of Surgery (C.J.T., G.B., G.B.M.), University of Minnesota, Minneapolis, Minnesota; Institute for Health Informatics (C.J.T., G.M.S., R.F., R.M., B.C.K., S.P., E.A.L., G.B.M.), University of Minnesota, Minneapolis, Minnesota; Department of Surgery (C.J.T., J.L.G.), North Memorial Health Hospital, Robbinsdale, Minnesota; North Memorial Health Hospital Emergency Medical Services (A.L.T.), Robbinsdale, Minnesota; and Department of Emergency Medicine (J.W.L.), North Memorial Health Hospital Emergency Medical Services, Robbinsdale, Minnesota.