JMIR Publications

ABSTRACT

Background:

As the adoption of Artificial Intelligence (AI) in health care increases, it becomes increasingly crucial to involve health care practitioners (HCP) in developing, validating, and implementing AI-enabled technologies become more crucial. However, due to a lack of AI literacy, most HCPs are not adequately educated for this revolution; this is a significant barrier to adopting and implementing AI that will impact our patients. Additionally, the limited existing AI education programs also face barriers to development and implementation at various levels of medical education. Towards informing future AI educational programs for HCPs, this scoping review aimed to provide an overview of the types of current or past AI educational programs pertaining to the programs’ curriculum content, modes of delivery, critical implementation factors for education delivery, and outcomes used to assess the programs’ effectiveness.

Objective:

This scoping review aims to establish a foundational understanding of education programs on AI for health care professionals by determining: 1. What were the most effective education approaches to enabling health care professionals to harness AI in enhancing and optimizing health care delivery? i. What curricular content was delivered/proposed? ii. What was the scope of content that should be delivered? iii. What learning objectives/outcomes were used in these approaches? 2. What were the enablers or barriers that contributed to the success of these programs and the implementation of AI curricula in healthcare education programs? How was education most effectively delivered? 3. What outcomes were used to assess the effectiveness of education programs?

Methods:

Following by the creation of a search strategy and keyword searches, a two-stage screening process was conducted by two independent reviewers to determine study eligibility. When consensus was not reached, the conflict was resolved by consulting a third reviewer. This process consisted of a title/abstract scan and a full-text review. The articles were included if they: 1) discussed an actual training program/education intervention or potential training program/educational intervention and the desired content to be covered; 2) focused on artificial intelligence; 3) have been designed/intended for health care professionals (at any stage of their career)

Results:

Of the 10,094 unique citations scanned, this review identified 41 studies relevant to our eligibility criteria. Among the 41 included studies, 10 studies described 11 unique programs and 31 studies discussed recommended curricular content. The curricular content of the unique programs ranged from AI use, AI interpretation, and cultivating skills to explain results derived from AI algorithms. The curricular topics were categorized into three main domains: cognitive, psychomotor, and affective.

Conclusions:

This review provided an overview of the current landscape of AI in medical education and highlighted the skills and competencies required in HCP to effectively use AI in enhancing the quality of care and optimizing patient outcomes. Future education efforts should focus on the development of regulatory strategies, a multidisciplinary approach to curriculum redesign, a competency-based curriculum, and patient-clinician interaction. Clinical Trial: N/A