Accepted for/Published in: JMIR Medical Education
Date Submitted: Nov 22, 2023
Date Accepted: Apr 29, 2024
Curriculum frameworks and educational programs in artificial intelligence for medical students, residents, and practicing physicians: a scoping review
ABSTRACT
Background:
The successful integration of artificial intelligence (AI) into clinical practice is contingent upon physicians' comprehension of AI principles and its applications. Therefore, it's essential for medical education curricula to incorporate AI topics and concepts, providing future physicians with the foundational knowledge and skills needed. However, there is a knowledge gap in the current understanding and availability of structured AI curriculum frameworks tailored for medical education, which serve as vital guides for instructing and facilitating the learning process.
Objective:
The aim of this scoping review is to synthesize knowledge from the literature on curriculum frameworks and current educational programs that focus on the teaching and learning of AI for medical students, residents, and practicing physicians.
Methods:
The review followed the framework proposed by Arksey and O'Malley (2005) supplemented by Levac et al. (2010), and the Joanna Briggs Institute methodological guidance for scoping reviews. An information specialist performed a comprehensive search from 2000 until May 2023, in the following bibliographic databases: MEDLINE (Ovid), Embase (Ovid), CENTRAL (Cochrane Library), CINAHL (EBSCOhost), and Scopus as well as the grey literature. Articles were limited to the English and French languages. This review included articles that describe curriculum frameworks for teaching and learning AI in medicine, irrespective of country. All types of articles and study designs were included, except conference abstracts and protocols. Two authors independently screened the titles and abstracts, read the full texts, and extracted data using a validated data extraction form. We adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist for reporting the results.
Results:
From the 5,104 articles scanned, 21 studies relevant to our eligibility criteria were identified. Nineteen (90%) papers altogether described 28 current or previously offered educational programs and two (10%) papers described elements of a curriculum framework. One framework describes a general approach to integrating AI curricula throughout the medical learning continuum. No papers described a theory, pedagogy or framework which guided the 30 educational programs. The main curricular concepts include: fundamentals of AI, fundamentals of health care data science, fundamentals of biomedical informatics, applications of AI, implementation of AI in health care setting, strengths and limitations of AI, ethical, legal and economic considerations, and medical decision-making.
Conclusions:
This review synthesizes recent advancements in AI curriculum frameworks and educational programs within the domain of medical education. To build on this foundation, future researchers are encouraged to engage in a multidisciplinary approach to curriculum redesign. Also, it is encouraged to initiate dialogues on the integration of AI into medical curriculum planning and to investigate the development, deployment, and appraisal of these innovative educational programs.
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.