Effect of Machine Learning on Dispatcher Recognition of Out-of-Hospital Cardiac Arrest During Calls to Emergency Medical Services: A Randomized Clinical Trial.

Journal: JAMA network open
PMID: 33404620

Abstract

IMPORTANCE: Emergency medical dispatchers fail to identify approximately 25% of cases of out-of-hospital cardiac arrest (OHCA), resulting in lost opportunities to save lives by initiating cardiopulmonary resuscitation.

Authors

  • Stig Nikolaj Blomberg
    Emergency Medical Services Copenhagen, Denmark; Department of Clinical Medicine, University of Copenhagen, Denmark. Electronic address: Stig.Nikolaj.Fasmer.Blomberg@regionh.dk.
  • Helle Collatz Christensen
    Emergency Medical Services Copenhagen, Denmark.
  • Freddy Lippert
    Copenhagen Emergency Medical Services, Copenhagen, Denmark.
  • Annette Kjær Ersbøll
    National Institute of Public Health, University of Southern Denmark, Denmark.
  • Christian Torp-Petersen
    Department of Clinical Investigation, Nordsjællands Hospital, Hillrød, Denmark.
  • Michael R Sayre
    Department of Emergency Medicine, University of Washington, United States.
  • Peter J Kudenchuk
    Department of Medicine, University of Washington, Seattle.
  • Fredrik Folke
    Copenhagen Emergency Medical Services, University of Copenhagen, Ballerup, Denmark.

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