Educating Future Physicians in Artificial Intelligence (AI): An Integrative Review and Proposed Changes. (September 2021)

• Record Type: Journal Article
• Authors: Grunhut, Joel; Wyatt, Adam TM; Marques, Oge
• Is Part Of: Journal of medical education and curricular development. Volume 8(2021)
• Publication Date: 2021-09
• Subjects: artificial intelligence -- education -- medical/methods -- education -- undergraduate medical -- empathy -- humans; Medical education -- Periodicals; Medicine -- Study and teaching -- Periodicals; Education, Medical; Medical education; Periodicals; Fulltext; Internet Resources; Periodicals; Periodicals; 610.71
• DOI: 10.1177/23821205211036836
• Languages: English
• ISSNs: 2382-1205

Abstract

BACKGROUND: As medicine and the delivery of healthcare enters the age of Artificial Intelligence (AI), the need for competent human–machine interaction to aid clinical decisions will rise. Medical students need to be sufficiently proficient in AI, its advantages to improve healthcare's expenses, quality, and access. Similarly, students must be educated about the shortfalls of AI such as bias, transparency, and liability. Overlooking a technology that will be transformative for the foreseeable future would place medical students at a disadvantage. However, there has been little interest in researching a proper method to implement AI in the medical education curriculum. This study aims to review the current literature that covers the attitudes of medical students towards AI, implementation of AI in the medical curriculum, and describe the need for more research in this area. METHODS: An integrative review was performed to combine data from various research designs and literature. Pubmed, Medline (Ovid), GoogleScholar, and Web of Science articles between 2010 and 2020 were all searched with particular inclusion and exclusion criteria. Full text of the selected articles was analyzed using the Extension of Technology Acceptance Model and the Diffusions of Innovations theory. Data were successively pooled together, recorded, and analyzed quantitatively using a modified Hawkings evaluation form. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses was utilized to help improve reporting. RESULTS: A total of 39 articles meeting inclusion criteria were identified. Primary assessments of medical students attitudes were identified (n = 5). Plans to implement AI in the curriculum for the purpose of teaching students about AI (n = 6) and articles reporting actual implemented changes (n = 2) were assessed. Finally, 26 articles described the need for more research on this topic or calling for the need of change in medical curriculum to anticipate AI in healthcare. CONCLUSIONS: There are few plans or implementations reported on how to incorporate AI in the medical curriculum. Medical schools must work together to create a longitudinal study and initiative on how to successfully equip medical students with knowledge in AI.