Scoping review of machine learning tools in hospital settings

Summary

The goal of this study was to identify machine learning (ML) tools in hospital settings and how they were implemented to inform decision-making for patient care through a scoping review. They found limited evidence related to the implementation of ML tools to assist clinicians with patient healthcare decisions in hospital settings. Future research should examine other approaches to integrating ML into hospital clinician decisions related to patient care, and report on PROGRESS-PLUS items.

Project Resources

Funded By

  • Canadian Institutes of Health Research (CIHR) Foundation grant awarded to Dr. Sharon Straus
  • CIHR Strategy for Patient Oriented-Research Initiative (GSR-154442)

Principal Investigator

  • Andrea Tricco

Co-Investigators

  • Sharon Straus

Collaborators

  • Orna Fennelly (Irish Centre for High End Computing (ICHEC) National University of Ireland Galway)
  • Jessie McGowan (School of Epidemiology and Public Health, University of Ottawa)
  • P Alison Paprica (Institute for Health Policy, Management and Evaluation University of Toronto Dalla Lana School of Public Health)

KTP Project Staff

  • Charmalee Harris
  • Areej Hezam
  • Marco Ghassemi
  • Vera Nincic
  • Amanda Parker
  • Sonia M Thomas