Artificial intelligence-based clinical decision support in the emergency department: A scoping review.

Journal: Academic emergency medicine : official journal of the Society for Academic Emergency Medicine
PMID: 39905631

Abstract

OBJECTIVE: Artificial intelligence (AI)-based clinical decision support (CDS) has the potential to augment high-stakes clinical decisions in the emergency department (ED). However, its current usage and translation to implementation remains poorly understood. We asked: (1) What is the current landscape of AI-CDS for individual patient care in the ED? and (2) What phases of development have AI-CDS tools achieved?

Authors

  • Hashim Kareemi
    From the, Department of Emergency Medicine, University of Ottawa, Ottawa, Ontario, Canada.
  • Krishan Yadav
    From the, Department of Emergency Medicine, University of Ottawa, Ottawa, Ontario, Canada.
  • Courtney Price
    Department of Emergency Medicine, University of Ottawa, Ottawa, Ontario, Canada.
  • Niklas Bobrovitz
    Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.
  • Andrew Meehan
    Department of Emergency Medicine, University of Ottawa, Ottawa, Ontario, Canada.
  • Henry Li
    Program in Applied Mathematics, Yale University, New Haven, CT, USA.
  • Gautam Goel
    Department of Emergency Medicine, Queensway Carleton Hospital, Ottawa, ON, Canada.
  • Sameer Masood
    Department of Medicine, University of Toronto, Toronto, Ontario, Canada.
  • Lars Grant
    Department of Emergency Medicine, McGill University, Montreal, QC, Canada.
  • Maxim Ben-Yakov
    Department of Medicine, Division of Emergency Medicine, University of Toronto, Toronto, ON, Canada.
  • Wojtek Michalowski
    Telfer School of Management, University of Ottawa, Ottawa, ON, Canada.
  • Christian Vaillancourt
    From the, Department of Emergency Medicine, University of Ottawa, Ottawa, Ontario, Canada.

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