Clarifying the role of Artificial Intelligence in Clinical Skills Education in health professions: A scoping review protocol

Abstract

There is a growing imperative to integrate AI into health professions education to ensure future clinicians are competent in leveraging these tools and adapting to an AI-augmented healthcare environment.
Clinical skills (CS) education, encompassing areas such as history-taking, physical examination, communication and clinical reasoning, and procedural skills, the key to ensuring competence of any clinician leading to better healthcare delivery and patient safety.
CS education involves and impacts multiple stakeholders who play different roles in the process of planning, delivering, assessing or acquiring skills that are relevant to their context of education, practice or healthcare provision. Traditional approaches to clinical skills education often face challenges related to standardisation, scalability, objective feedback, and access to diverse learning and practice experiences. Artificial Intelligence offers promising solutions, that may enhance or facilitate CS education and support the different stakeholders including learnings in their educational journey. Varieties of solutions have been explored in literature including intelligent tutoring systems, virtual reality simulations, AI-powered feedback tools, and automated performance assessment.
While the theoretical potential of AI in clinical skills education is recognised, the actual extent, nature, and reported outcomes of its application across various health professions remain fragmented and unclear. There is a need to systematically map the existing literature to understand how AI has helped or can help support clinical skills education. A scoping review is the most appropriate evidence synthesis methodology for addressing the aforementioned knowledge gap, particularly when compared to other common review types such as systematic reviews or traditional narrative reviews.
Previous scoping reviews addressed health professions education in a broader sense while focusing on medics or certain phase of education and did provide useful mapping of relevant literature however they were not completely inclusive of the broad context of all health professions and the narrow focus and thicker depth of focus on clinical skills that we intend to address in this review (Feigerlova et al., 2025; Gordon et al, 2024; Lee et al., 2021; Lie et al., 2023). Our review aims to explore the role of Artificial Intelligence responding to the question “HOW” while focusing on in Clinical Skills learning, teaching and assessment in undergraduate and postgraduate education in all health professions. It also aims to form a precursor for a systematic review on the same area. This review aims to clarify the role of Artificial Intelligence in Clinical Skills learning, teaching and assessment in undergraduate and postgraduate education between 2015 and 2025, through reviewing published peer-reviewed articles, reports, policies, conference proceedings and commentaries.
Methods: Three databases PubMed, Scopus, and Embase will be systematically searched for relevant studies using the determined key terms during the period 2015 to 2025. Articles duplication among these databases will be eliminated. Articles will be screened by title, abstract then full text. Data extraction and charting will be conducted in alignment with the FACETS framework of AI use in medical education.