ArticleBMJ open2026
Scoping review of the methods used to map clinical expertise and knowledge in the creation of knowledge-based clinical decision support systems.
Article in BMJ open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
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Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDigital 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.
objectivesTo 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
methodsData were extracted on study characteristics, clinical domain and approaches used to capture and structure knowledge for CDSS development. Methods were synthesised descriptively.
resultsOf 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.
conclusionsMethods 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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What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.