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"I Just Don't Know Enough:" A Needs Assessment for Artificial Intelligence Adoption in Continuing Professional
Adria Hoffman1, Elissa Hall, Jennifer Curran
1Dr. Hoffman: Senior education specialist, Mayo Clinic School of Continuous Professional Development and instructor in medical education, Mayo Clinic College of Medicine and Science, Rochester, MN. Dr. Hall: Scientific director, advanced digital education, Mayo Clinic Harper Family Foundation Artificial Intelligence Education in Medicine Program and assistant professor of laboratory medicine, Mayo Clinic College of Medicine and Science, Rochester, MN. Dr. Curran: Director of professional education, Mayo Clinic Center for Tuberculosis, Rochester, MN. Ms. Ganther: Senior program coordinator, Mayo Clinic Program in Professionalism and Values and instructor in medical education and health care administration, Mayo Clinic College of Medicine and Science, Jacksonville, FL. Dr. Bowler: Assistant Professor of Health Care Administration; Assistant Professor of Laboratory Medicine and PathologyMayo Clinic Department of Laboratory Medicine and Pathology and Assistant Professor of Medical Education, Mayo Clinic College of Medicine and Science, Rochester, MN.
Generative artificial intelligence (AI) presents opportunities for health professions education, but adoption requires addressing individual and organizational barriers. Understanding AI tool implementation is crucial for effective integration into continuing professional development (CPD).
Area of Science:
- Health Professions Education
- Artificial Intelligence
- Continuing Professional Development
Background:
- Generative artificial intelligence (AI) offers potential for workplace efficiencies and augmenting health professions education.
- There is significant interest in leveraging AI for continuing professional development (CPD).
Purpose of the Study:
- To identify needs of CPD professionals regarding AI.
- To determine organizational approaches for supporting AI tool adoption.
Main Methods:
- Nine focus groups and two interviews were conducted from April to July 2024.
- Interpretive phenomenological analysis was used to analyze participant experiences and barriers.
Main Results:
- Barriers to AI adoption exist at individual, team, and organizational levels.
- Key barriers include knowledge of licensed tools, digital literacy, policy, role clarity, and organizational purpose.
Conclusions:
- Current literature lacks exploration of nuanced AI roles and contexts in CPD.
- Evaluating AI tools requires understanding their function, legal, ethical, and pedagogical aspects within digital literacy.
- Organizational systems, processes, and communication significantly impact AI technology adoption.
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