Competencies for the Use of Artificial Intelligence–Based Tools by Health Care Professionals

Author:

Russell Regina G.1,Lovett Novak Laurie2,Patel Mehool3,Garvey Kim V.4,Craig Kelly Jean Thomas5,Jackson Gretchen P.6,Moore Don7,Miller Bonnie M.8

Affiliation:

1. is director of learning system outcomes, Office of Undergraduate Medical Education, and assistant professor of medical education and administration, Vanderbilt University School of Medicine, Nashville Tennessee; ORCID:.

2. is director, Center of Excellence in Applied Artificial Intelligence, Vanderbilt University Medical Center, and associate professor of biomedical informatics, Vanderbilt University School of Medicine, Nashville, Tennessee; ORCID:.

3. is associate chief health officer and chief medical officer of provider analytics, IBM Watson Health, Cambridge, Massachusetts, and clinical professor, Northeast Ohio Medical University, Rootstown, Ohio.

4. is research instructor in anesthesiology, Vanderbilt University School of Medicine, and director of operations, Center for Advanced Mobile Healthcare Learning, Vanderbilt University Medical Center, Nashville, Tennessee; ORCID:.

5. is lead director, Clinical Evidence Development, Aetna Medical Affairs, CVS Health. At the time this work was completed, the author was deputy chief science officer of evidence-based practice, Center for AI, Research, and Evaluation, IBM Watson Health, Cambridge, Massachusetts; ORCID:.

6. is vice president and scientific medical officer, Intuitive Surgical, Sunnyvale, California, and associate professor of surgery, pediatrics, and biomedical informatics, Vanderbilt University School of Medicine, Nashville, Tennessee. At the beginning of this work, the author was vice president and chief science officer, IBM Watson Health, Cambridge, Massachusetts; ORCID:.

7. is emeritus professor of medical education and administration, Vanderbilt University School of Medicine, Nashville, Tennessee.

8. is professor of medical education and administration, Vanderbilt University School of Medicine, and director, Center for Advanced Mobile Healthcare Learning, Vanderbilt University Medical Center, Nashville, Tennessee; ORCID:.

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.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Education,General Medicine

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