ArticleBMC medical informatics and decision making2021
Barriers and facilitators to the adoption of electronic clinical decision support systems: a qualitative interview study with UK general practitioners.
Article in BMC medical informatics and decision making, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 papers, 4 of them syntheses that pooled 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.
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
57 citing papers in PubMed, 4 syntheses or guidelines pooled it, 79 citations in OpenAlex.
- The implementation challenge of computerised clinical decision support systems for the detection of disease in primary care: systematic review and recommendations.Implementation science : IS · 2025Pooled it
- Understanding "Alert Fatigue" in Primary Care: Qualitative Systematic Review of General Practitioners Attitudes and Experiences of Clinical Alerts, Prompts, and Reminders.Journal of medical Internet research · 2025Pooled it
- Pooled it
- Exploring the role of professional identity in the implementation of clinical decision support systems-a narrative review.Implementation science : IS · 2024Pooled it
- Implementation of Electronic Clinical Decision Support for Radiology Referrals: The Role of Governance, Clinician Engagement and Education.Emergency medicine Australasia : EMA · 2026Article
- Uptake of Clinical Decision Support Systems Among Health Care Professionals in Six European Countries and the United States: Cross-Sectional Survey Within the I-CARE4OLD Project.Journal of medical Internet research · 2026Article
- The use of an innovative clinical decision support system focused on psychosocial vulnerabilities during pregnancy: the Born in Belgium Professionals Platform.BMC health services research · 2026Observational
- Orchestrating the Development of a Sustainable Network IT Solution for a Research Network: Qualitative Participatory Multimethod Design.JMIR formative research · 2026Article
- Scale, Skill-Mix, and Access Implications of the Production of Appointments by Primary Care Practices in England.Health economics · 2026Article
- Experiences of Alert Fatigue and Its Contributing Factors in Hospitals: Qualitative Study.Journal of medical Internet research · 2026Article
- Exploring the views of key stakeholders on dementia risk prediction in primary care in areas of socioeconomic deprivation: a qualitative study.The British journal of general practice : the journal of the Royal College of General Practitioners · 2026Article
- Qualitative Evaluation of a Clinical Decision-Support Tool for Improving Anticoagulation Control in Non-Valvular Atrial Fibrillation in Primary Care.Healthcare (Basel, Switzerland) · 2026Article
- Understanding Cervical Spine Injury Imaging Decision-Making in Pediatric Trauma Patients.Pediatrics open science · 2026Article
- Five essential features for adoption of clinical risk prediction tools: Insights from the VOCAL-Penn score.Hepatology communications · 2025Article
- Explainable prediction of hypothermia risk in laparoscopic surgery: a retrospective cross-sectional study using machine learning.BMC surgery · 2025Article
- Facilitators, barriers, and insights using an HFA-PEFF-based clinical decision support system: A proof-of-concept study.ESC heart failure · 2025Article
- Clinical Decision Support Systems in Indian Healthcare Settings: Benefits, Barriers, and Future Implications.Healthcare (Basel, Switzerland) · 2025Review
- Identifying people at risk of rheumatoid arthritis in primary care: a qualitative study.The British journal of general practice : the journal of the Royal College of General Practitioners · 2025Article
- Development of a Knowledge Base for an Integrated Older Adult Care Model (SMART System) Based on an Intervention Mapping Framework: Mixed Methods Study.JMIR nursing · 2025Article
- A Mixed-Method Case Study to Evaluate Adoption of Clinical Decision Support for Cancer Symptom Management.Applied clinical informatics · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 4 institutions in 1 country.
Funding
Abstract
backgroundWell-established electronic data capture in UK general practice means that algorithms, developed on patient data, can be used for automated clinical decision support systems (CDSSs). These can predict patient risk, help with prescribing safety, improve diagnosis and prompt clinicians to record extra data. However, there is persistent evidence of low uptake of CDSSs in the clinic. We interviewed UK General Practitioners (GPs) to understand what features of CDSSs, and the contexts of their use, facilitate or present barriers to their use.
methodsWe interviewed 11 practicing GPs in London and South England using a semi-structured interview schedule and discussed a hypothetical CDSS that could detect early signs of dementia. We applied thematic analysis to the anonymised interview transcripts.
resultsWe identified three overarching themes: trust in individual CDSSs; usability of individual CDSSs; and usability of CDSSs in the broader practice context, to which nine subthemes contributed. Trust was affected by CDSS provenance, perceived threat to autonomy and clear management guidance. Usability was influenced by sensitivity to the patient context, CDSS flexibility, ease of control, and non-intrusiveness. CDSSs were more likely to be used by GPs if they did not contribute to alert proliferation and subsequent fatigue, or if GPs were provided with training in their use.
conclusionsBuilding on these findings we make a number of recommendations for CDSS developers to consider when bringing a new CDSS into GP patient records systems. These include co-producing CDSS with GPs to improve fit within clinic workflow and wider practice systems, ensuring a high level of accuracy and a clear clinical pathway, and providing CDSS training for practice staff. These recommendations may reduce the proliferation of unhelpful alerts that can result in important decision-support being ignored.
Indexed as
Identifiers
What OpenQuestion 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 OpenQuestion graph.