Understanding clinical prediction models as 'innovations': a mixed methods study in UK family practice

BMC Med Inform Decis Mak. 2016 Aug 9;16:106. doi: 10.1186/s12911-016-0343-y.


Background: Well-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.

Methods: Mixed methods study in North West England that comprised an online survey and focus groups.

Results: One 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.

Conclusions: The 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.

Keywords: Attitude of health personnel; Clinical decision support systems; Clinical prediction models; Clinicians; Diagnostic models; Family physicians; Healthcare information technology adoption; Practice patterns; Primary care information systems; Prognostic models; Risk stratification.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Clinical Decision-Making / methods*
  • England
  • Family Practice
  • Focus Groups
  • Humans
  • Inventions
  • Models, Theoretical*
  • Physicians, Family / statistics & numerical data*
  • Practice Guidelines as Topic / standards*
  • Surveys and Questionnaires