Competencies for the Use of Artificial Intelligence–Based Tools by Health Care Professionals. (6th September 2022)

• Record Type: Journal Article
• Authors: Russell, Regina G.; Lovett Novak, Laurie; Patel, Mehool; Garvey, Kim V.; Craig, Kelly Jean Thomas; Jackson, Gretchen P.; Moore, Don; Miller, Bonnie M.
• Is Part Of: Academic medicine. Volume 98:Number 3(2023)
• Page Start: 348
• Page End: 356
• Publication Date: 2022-09-06
• Subjects: Medical education -- Periodicals; Medical policy -- Periodicals; Medical personnel -- Periodicals; Periodicals; 610.711
• DOI: 10.1097/ACM.0000000000004963
• Languages: English
• ISSNs: 1040-2446

Abstract

Abstract : Purpose: The expanded use of clinical tools that incorporate artificial intelligence (AI) methods has generated calls for specific competencies for effective and ethical use. This qualitative study used expert interviews to define AI-related clinical competencies for health care professionals. Method: In 2021, a multidisciplinary team interviewed 15 experts in the use of AI-based tools in health care settings about the clinical competencies health care professionals need to work effectively with such tools. Transcripts of the semistructured interviews were coded and thematically analyzed. Draft competency statements were developed and provided to the experts for feedback. The competencies were finalized using a consensus process across the research team. Results: Six competency domain statements and 25 subcompetencies were formulated from the thematic analysis. The competency domain statements are: (1) basic knowledge of AI: explain what AI is and describe its health care applications; (2) social and ethical implications of AI: explain how social, economic, and political systems influence AI-based tools and how these relationships impact justice, equity, and ethics; (3) AI-enhanced clinical encounters: carry out AI-enhanced clinical encounters that integrate diverse sources of information in creating patient-centered care plans; (4) evidence-based evaluation of AI-based tools: evaluate the quality, accuracy, safety, contextual appropriateness, and biases of AI-based tools and their underlying data sets in providing care to patients and populations; (5) workflow analysis for AI-based tools: analyze and adapt to changes in teams, roles, responsibilities, and workflows resulting from implementation of AI-based tools; and (6) practice-based learning and improvement regarding AI-based tools: participate in continuing professional development and practice-based improvement activities related to use of AI tools in health care. Conclusions: The 6 clinical competencies identified can be used to guide future teaching and learning programs to maximize the potential benefits of AI-based tools and diminish potential harms.