AI-based Clinical Decision Support Systems for the management of musculoskeletal disorders: a scoping review protocol on current applications, development, and intended use
Abstract
Introduction: Artificial Intelligence (AI) is increasingly transforming healthcare, supporting applications such as image interpretation, risk stratification, and treatment personalization. In physiotherapy, however, AI adoption remains limited, with reported uses including movement analysis, prediction of rehabilitation outcomes, patient communication, and clinical documentation. Structural challenges in musculoskeletal care, such as limited assessment time, underscore the need for tools that support clinical decision-making. AI-enhanced Clinical Decision Support Systems (CDSS) have the potential to improve diagnosis, triage, prognosis, treatment planning, and monitoring. This scoping review aims to systematically identify existing AI-based CDSS applications in musculoskeletal disorders, evaluate their development and implementation, and clarify their current and potential clinical utility. Objective: The objective of this scoping review is to map the extent and characteristics of the available evidence on AI-based Clinical Decision Support Systems developed or used for musculoskeletal disorders. Methods: The review will follow the JBI methodology for scoping reviews and will adhere to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA‑ScR). A comprehensive search will be conducted in PubMed, CINAHL, Embase, Cochrane, Scopus, and PEDro. Grey literature sources, including OpenGrey, Google Scholar, institutional repositories, and dissertation databases, will also be explored. Data will be charted using a tailored extraction form and summarized descriptively, with findings presented in both narrative and visual formats. Inclusion criteria: This scoping review will include studies describing the development, implementation, or clinical use of AI–based CDSS for musculoskeletal conditions. Studies presenting tools specifically designed for the musculoskeletal field, or applications intended to support their clinical decision‑making processes, will be considered. No restrictions will be applied regarding the clinical setting. Populations with musculoskeletal conditions, all types of AI-based CDSS, and all study designs, including grey literature, will be eligible.
Fields of Study & Subjects
Artificial Intelligence in Healthcare and Education
Electronic Health Records Systems
Artificial Intelligence in Healthcare
Publication details
- Publication date
- 1 January 2026
- Language
- EN
- Document type
- Preprint