Considering Clinician Competencies for the Implementation of Artificial Intelligence–Based Tools in Health Care: Findings From a Scoping Review

• Published in: JMIR medical informatics Vol. 10; no. 11; p. e37478
• Main Authors: Garvey, Kim V, Thomas Craig, Kelly Jean, Russell, Regina, Novak, Laurie L, Moore, Don, Miller, Bonnie M
• Format: Journal Article
• Language: English
• Published: Canada JMIR Publications 16.11.2022
• Subjects: Ambulatory care; Artificial intelligence; Clinical decision making; Computer simulation; Deep learning; Education; Electronic health records; Health informatics; Information systems; Information technology; Instructional design; Machine learning; Medical Subject Headings-MeSH; Multimedia; Natural language processing; Personal computers; Pharmacy; Professional development; Professionals; Review; Software; Therapists; clinical tool; competency; health information; clinical education; artificial intelligence; digital health; decision-making; clinical decision; patient; digital tool; physician; health technology; educational framework; health care
• ISSN: 2291-9694; 2291-9694
• DOI: 10.2196/37478

The use of artificial intelligence (AI)-based tools in the care of individual patients and patient populations is rapidly expanding. The aim of this paper is to systematically identify research on provider competencies needed for the use of AI in clinical settings. A scoping review was conducted to identify articles published between January 1, 2009, and May 1, 2020, from MEDLINE, CINAHL, and the Cochrane Library databases, using search queries for terms related to health care professionals (eg, medical, nursing, and pharmacy) and their professional development in all phases of clinical education, AI-based tools in all settings of clinical practice, and professional education domains of competencies and performance. Limits were provided for English language, studies on humans with abstracts, and settings in the United States. The searches identified 3476 records, of which 4 met the inclusion criteria. These studies described the use of AI in clinical practice and measured at least one aspect of clinician competence. While many studies measured the performance of the AI-based tool, only 4 measured clinician performance in terms of the knowledge, skills, or attitudes needed to understand and effectively use the new tools being tested. These 4 articles primarily focused on the ability of AI to enhance patient care and clinical decision-making by improving information flow and display, specifically for physicians. While many research studies were identified that investigate the potential effectiveness of using AI technologies in health care, very few address specific competencies that are needed by clinicians to use them effectively. This highlights a critical gap.