Evidence map›Paper›PMID 42275446›Full record

ArticleJMIR research protocols2026

Effectiveness of Guideline-Based Clinical Decision Support Systems: Protocol for a Systematic Review.

Berkay Newroz Aksu, Bora Gashi, Fridtjof Schiefenhövel, Martin Boeker

Abstract read
In one paragraph

Article in JMIR research protocols, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Berkay Newroz AksuChair of Medical Informatics, Institute of Artificial Intelligence and Informatics in Medicine, TUM University Hospital, School of Medicine and Health, Technical University of Munich, Ismaninger 22, Munich, 81675, Germany, 49 89 4140 4320.ORCID 0009-0006-5206-7022
Bora GashiChair of Medical Informatics, Institute of Artificial Intelligence and Informatics in Medicine, TUM University Hospital, School of Medicine and Health, Technical University of Munich, Ismaninger 22, Munich, 81675, Germany, 49 89 4140 4320.ORCID 0009-0000-9872-352X
Fridtjof SchiefenhövelChair of Medical Informatics, Institute of Artificial Intelligence and Informatics in Medicine, TUM University Hospital, School of Medicine and Health, Technical University of Munich, Ismaninger 22, Munich, 81675, Germany, 49 89 4140 4320.ORCID 0000-0002-1612-9357
Martin BoekerChair of Medical Informatics, Institute of Artificial Intelligence and Informatics in Medicine, TUM University Hospital, School of Medicine and Health, Technical University of Munich, Ismaninger 22, Munich, 81675, Germany, 49 89 4140 4320.ORCID 0000-0003-2972-2042

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Clinical guidelines (CGs) standardize care through evidence-based recommendations, while clinical decision support systems (CDSS) can assist in applying these guidelines to individual patients. The scientific basis for the decisions offered by decision support systems is often not explicitly stated or not clearly specified in the literature on CDSS. Therefore, a systematic examination of the literature is needed to map the current state of CDSS, with a particular focus on the integration of CGs. Objective: This study aims to systematically collect, describe, and synthesize evidence of randomized controlled studies of interventions using CDSS with a well-defined integration of evidence-based CGs and evaluating direct medical outcomes. Methods: This systematic review adheres to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) and PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklists. The eligibility criteria for this review are defined using the patient, intervention, control, outcome, and study design framework, including studies involving patients with any medical condition or disease. Study interventions need to include guideline-based CDSS, encompassing all types of interventions used for treatment. Each intervention must provide a sufficiently accessible technical description, including the types of data and algorithms used for decision-support procedures. The guidelines used within these CDSS interventions must be derived from a clearly defined, evidence-based guideline development process published by a discernible guideline-producing body. Studies must use a randomized controlled study design. Only studies evaluating the effectiveness of the interventions on direct medical outcomes are included. Web of Science, including MEDLINE, and Scopus will be searched with search expressions aligned with the eligibility criteria. Results: On August 11, 2022, the initial search was conducted on Web of Science and Scopus. From a total of 6203 records, 1347 were removed prior to screening as duplicates, 2506 records were excluded during the first screening step, and 2291 were excluded during the second step. Next, 41 papers were excluded based on full-text review, and 18 papers were finally included in the review following this initial search. This review explores whether CDSS based on CGs can improve clinical outcomes, although their effectiveness may vary depending on various factors. Potential limitations, such as high study heterogeneity, have already been identified. An update of the review has been started in April 2025. Conclusions: To our knowledge, this is the first rigorous systematic review on the effectiveness of guideline-based decision support systems in which the technical integration and algorithmic embedding of CGs have been described or can be inferred from secondary literature. With this review, we aim to address this gap by providing a detailed analysis of existing research and identifying best practices, challenges, and areas for future investigation.

Indexed as

Decision Support Systems, ClinicalPractice Guidelines as TopicEvidence-Based MedicineHumansSystematic Reviews as TopicCDSSclinical decision support systemclinical guidelinesguideline formalizationPreferred Reporting Items for Systematic reviews and Meta-AnalysesPRISMAsystematic review

Identifiers

PMID42275446
PMCPMC13256483

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Registered trials

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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 OpenQuestion graph.