Barriers to and facilitators of clinician acceptance and use of artificial intelligence in healthcare settings: a scoping review.

Journal: BMJ open
PMID: 40233955

Abstract

OBJECTIVES: This study aimed to systematically map the evidence and identify patterns of barriers and facilitators to clinician artificial intelligence (AI) acceptance and use across the types of AI healthcare application and levels of income of geographic distribution of clinician practice.

Authors

  • Catherine E A Scipion
    Department of Health Policy and Behavioral Sciences, Georgia State University School of Public Health, Atlanta, Georgia, USA cscipion1@gsu.edu.
  • Margaret A Manchester
    Department of Health Policy and Behavioral Sciences, Georgia State University School of Public Health, Atlanta, Georgia, USA.
  • Alex Federman
    Division of General Internal Medicine, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
  • Yufei Wang
    State Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, Sichuan, China.
  • Jalayne J Arias
    Department of Health Policy and Behavioral Sciences, Georgia State University School of Public Health, Atlanta, Georgia, USA.

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