ArticleBMC medical informatics and decision making2016
Understanding clinical prediction models as 'innovations': a mixed methods study in UK family practice.
Article in BMC medical informatics and decision making, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 25 citations in OpenAlex.
- Article
- Seven Opportunities for Artificial Intelligence in Primary Care Electronic Visits: Qualitative Study of Staff and Patient Views.Annals of family medicine · 2025Article
- Legitimacy as Social Infrastructure: A Critical Interpretive Synthesis of the Literature on Legitimacy in Health and Technology.JMIR human factors · 2025Review
- Systematic review to understand users perspectives on AI-enabled decision aids to inform shared decision making.NPJ digital medicine · 2024Article
- Making predictions under interventions: a case study from the PREDICT-CVD cohort in New Zealand primary care.Frontiers in epidemiology · 2024Article
- Influence of research evidence on the use of cardiovascular clinical prediction rules in primary care: an exploratory qualitative interview study.BMC primary care · 2023Article
- Understanding GPs' views and experiences of using clinical prediction rules in the management of respiratory infections: a qualitative study.BJGP open · 2021Article
- "A catalyst for action": Factors for implementing clinical risk prediction models of infection in home care settings.Journal of the American Medical Informatics Association : JAMIA · 2021Article
- Validation of a Community-Acquired Pneumonia Score To Improve Empiric Antibiotic Selection at an Academic Medical Center.Antimicrobial agents and chemotherapy · 2021Article
- Methodological standards for the development and evaluation of clinical prediction rules: a review of the literature.Diagnostic and prognostic research · 2019Review
- An mHealth App for Decision-Making Support in Wound Dressing Selection (WounDS): Protocol for a User-Centered Feasibility Study.JMIR research protocols · 2018Article
- Development of a Mobile Clinical Prediction Tool to Estimate Future Depression Severity and Guide Treatment in Primary Care: User-Centered Design.JMIR mHealth and uHealth · 2018Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundWell-designed clinical prediction models (CPMs) often out-perform clinicians at estimating probabilities of clinical outcomes, though their adoption by family physicians is variable. How family physicians interact with CPMs is poorly understood, therefore a better understanding and framing within a context-sensitive theoretical framework may improve CPM development and implementation. The aim of this study was to investigate why family physicians do or do not use CPMs, interpreting these findings within a theoretical framework to provide recommendations for the development and implementation of future CPMs.
methodsMixed methods study in North West England that comprised an online survey and focus groups.
resultsOne hundred thirty eight respondents completed the survey, which found the main perceived advantages to using CPMs were that they guided appropriate treatment (weighted rank [r] = 299; maximum r = 414 throughout), justified treatment decisions (r = 217), and incorporated a large body of evidence (r = 156). The most commonly reported barriers to using CPMs were lack of time (r = 163), irrelevance to some patients (r = 161), and poor integration with electronic health records (r = 147). Eighteen clinicians participated in two focus groups (i.e. nine in each), which revealed 13 interdependent themes affecting CPM use under three overarching domains: clinician factors, CPM factors and contextual factors. Themes were interdependent, indicating the tensions family physicians experience in providing evidence-based care for individual patients.
conclusionsThe survey and focus groups showed that CPMs were valued when they supported clinical decision making and were robust. Barriers to their use related to their being time-consuming, difficult to use and not always adding value. Therefore, to be successful, CPMs should offer a relative advantage to current working, be easy to implement, be supported by training, policy and guidelines, and fit within the organisational culture.
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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.