Scoping review of the methods used to map clinical expertise and knowledge in the creation of knowledge-based clinical decision support systems.

Journal: BMJ open
Published Date:
(1)

Abstract

BACKGROUND: Digital health technologies are rapidly increasing within healthcare services; however, adoption remains limited. Clinical decision support systems (CDSSs) are digital software designed to support decision-making. Reporting practices for CDSS development remain inconsistent and methodological guidance is limited. OBJECTIVES: To identify and synthesise the methods used to capture and map clinical knowledge for the development of knowledge-based CDSSs. ELIGIBILITY CRITERIA: English-language studies (2012-2024) describing the development of knowledge-based CDSSs and reporting of the methods used to construct their knowledge bases. Eligible study designs included qualitative, quantitative and mixed-methods research. Commentaries, editorials and conference abstracts without full texts were excluded. SOURCES OF EVIDENCE: PubMed, IEEE Xplore, Web of Science and Embase were searched. No protocol was published. CHARTING METHODS: Data were extracted on study characteristics, clinical domain and approaches used to capture and structure knowledge for CDSS development. Methods were synthesised descriptively. RESULTS: Of 10 578 records screened, 67 studies met the inclusion criteria. Studies spanned 24 countries and 46 clinical areas. Five main approaches to knowledge-base creation were identified: consultation with domain experts, use of clinical practice guidelines, literature reviews, ontologies and historical clinical data. Domain-expert input was the most common method (65%; 44/67), although reporting was inconsistent, with 61% (27/44) studies not specifying the number of experts involved and 45% (20/44) not reporting their professional backgrounds. Across studies, substantial variation and gaps were observed in the documentation of knowledge-capture processes. CONCLUSIONS: Methods for constructing knowledge bases in CDSSs are highly heterogeneous and often poorly reported. Greater standardisation-potentially through dedicated reporting guidelines or methodological frameworks may strengthen transparency, reproducibility and the design quality of future CDSSs.

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