Artificial Intelligence Education for Health Professions Students: A Scoping Review

Background: The rapid pace at which artificial intelligence (AI) technologies are being integrated into healthcare demands competency on the part of health professionals in how to effectively integrate these tools into their practice. However, not many universities currently teach health professions students (HPS) about AI. A scoping review was undertaken to map key themes and identify gaps in the available literature on how best to teach HPS about AI. Methods: This scoping review followed the PRISMA-ScR checklist and the Arksey and O’Malley five-stage framework. The aim was to discover what AI topics have been taught to HPS and what educational methods have been employed to teach HPS about AI. A search of 4 databases (PubMed, Scopus, CINAHL, ERIC) identified 10,979 unique titles which underwent a two-step screening process and 15 full text studies were included. Data were extracted in an iterative process. A narrative review approach was used to generating themes and reporting results. Results: Most of the included studies taught medical students about AI, although students from other health specialties such as nursing, pharmacy and dentistry also appeared in the literature. A broad range of topics about AI were delivered by the educational interventions which were synthesised using a modified framework from McCoy et al. (2020). The most frequent topics taught were foundational AI literacy and applying AI to healthcare practice. A wide variety of teaching methods were utilised, most commonly reading and lectures. Conclusions: Whilst some university programs are already implementing AI educational interventions for their health professions students, there remains a lack of consensus on what and how to teach about AI to HPS. Further research should be conducted to build an evidence base for the design, implementation and evaluation of AI curricula for HPS, particularly in teaching students from a wider range of health disciplines.