Evidence map›Paper›PMID 40671071›Full record

SynthesisImplementation science : IS2025

The implementation challenge of computerised clinical decision support systems for the detection of disease in primary care: systematic review and recommendations.

Christina Derksen, Fiona M Walter, Adriana B Akbar, Asha V E Parmar, Tyler S Saunders, Thomas Round, Greg Rubin, Suzanne E Scott

Abstract readSystematic Review
In one paragraph

Synthesis in Implementation science : IS, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 2 pooled it
–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

15 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Why aren't they used? Systematic review of barriers to implementation of clinical decision support systems for early cancer detection in primary care.The British journal of general practice : the journal of the Royal College of General Practitioners · 2026
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  9. Authors' response.The British journal of general practice : the journal of the Royal College of General Practitioners · 2026
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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

8 authors.

Christina DerksenWolfson Institute of Population Health, Faculty of Medicine and Dentistry, Queen Mary University of London, London, UK. christina.derksen@qmul.ac.uk.ORCID 0000-0002-4663-1882
Fiona M WalterWolfson Institute of Population Health, Faculty of Medicine and Dentistry, Queen Mary University of London, London, UK.
Adriana B AkbarThe London School of Medicine and Dentistry, Faculty of Medicine and Dentistry, Queen Mary University of London, London, UK.
Asha V E ParmarThe London School of Medicine and Dentistry, Faculty of Medicine and Dentistry, Queen Mary University of London, London, UK.
Tyler S SaundersWolfson Institute of Population Health, Faculty of Medicine and Dentistry, Queen Mary University of London, London, UK.
Thomas RoundSchool of Life Course and Population Sciences, Kings College London, London, UK.
Greg RubinPopulation Health Sciences Institute, Newcastle University, Newcastle Upon Tyne, UK.
Suzanne E ScottWolfson Institute of Population Health, Faculty of Medicine and Dentistry, Queen Mary University of London, London, UK.

Funding

Barts Charity G-001520Barts Charity MRC&U0036Cancer Research UK EDDPGM-May22\100002
6 · The paper itself

Abstract

backgroundEarly detection of diseases in primary care is crucial for timely treatment and better outcomes. Complex care demands and limited resources can make early detection challenging. Clinical decision support systems (CDSS) aim to improve the diagnostic process. However, barriers to implementation have so far prevented their effective use.  This systematic review aimed to identify barriers for the implementation of CDSS for disease detection in primary care and use this to develop recommendations for implementation.

methodsWe searched MEDLINE, EMBASE, Scopus, Web of Science and Cochrane databases. Included studies reported barriers to the implementation of CDSS for the detection of undiagnosed, prevalent diseases in primary care. Two independent researchers undertook screening and data extraction. The QuADS tool was used for quality assessment. Data on barriers and facilitators were synthesised using an inductive-deductive approach based on the Theoretical Domains Framework. This was used to identify solutions via the Behaviour Change Wheel.

results10498 titles and abstracts were screened, and 768 full texts were assessed. We included 99 studies describing 85 tools, mostly in high-income countries. Most studies (66, 66.7%) applied qualitative methods and described CDSS implemented in pilot studies (64, 64.7%). Included studies had very limited stakeholder involvement or theoretical underpinning.  We identified 2563 unique barriers and facilitators to implementation. Barriers were spread across the Theoretical Domains Framework including technical and workflow implementation issues at practice level, wider healthcare system issues, problems with the usability of systems, PCPs' and patients' attitudes and beliefs, a lack of skills and knowledge, and social barriers. Implementation recommendations for development teams involve selecting appropriate diagnostic challenges for CDSS, ensuring usability, engaging stakeholders and testing CDSS prior to implementation. Primary care teams need to clarify responsibilities, provide training and support patients. Underlying barriers across healthcare systems will need to be addressed at policy level.

conclusionsThe range and scale of the barriers and complexity of recommendations highlight implementation challenges for CDSS in primary care. Although recommendations can be used to improve implementation, our findings emphasise the need to carefully reflect on the feasibility of CDSS in primary care at the point of design and development.  The systematic review was preregistered using PROSPERO (CRD42024517054): https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=517054.

Indexed as

Decision Support Systems, ClinicalPrimary Health CareEarly DiagnosisHumansImplementation ScienceBehaviour change wheelClinical decision supportDesign and developmentImplementationPolicyPrimary careSystematic reviewTheoretical domains framework

Identifiers

PMID40671071
PMCPMC12269258

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.