Barriers and facilitators perceived by physicians when using prediction models in practice

Teus H. Kappen*, Kim Van Loon, Martinus A M Kappen, Leo Van Wolfswinkel, Yvonne Vergouwe, Wilton A. Van Klei, Karel G M Moons, Cor J. Kalkman

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Objectives Prediction models may facilitate risk-based management of health care conditions. In a large cluster-randomized trial, presenting calculated risks of postoperative nausea and vomiting (PONV) to physicians (assistive approach) increased risk-based management of PONV. This increase did not improve patient outcome - that is, PONV incidence. This prompted us to explore how prediction tools guide the decision-making process of physicians. Study Design and Setting Using mixed methods, we interviewed eight physicians to understand how predicted risks were perceived by the physicians and how they influenced decision making. Subsequently, all 57 physicians of the trial were surveyed for how the presented risks influenced their perceptions. Results Although the prediction tool made physicians more aware of PONV prevention, the physicians reported three barriers to use predicted risks in their decision making. PONV was not considered an outcome of utmost importance; decision making on PONV prophylaxis was mostly intuitive rather than risk based; prediction models do not weigh benefits and risks of prophylactic drugs. Conclusion Combining probabilistic output of the model with their clinical experience may be difficult for physicians, especially when their decision-making process is mostly intuitive. Adding recommendations to predicted risks (directive approach) was considered an important step to facilitate the uptake of a prediction tool.

Original languageEnglish
Pages (from-to)136-145
Number of pages10
JournalJournal of Clinical Epidemiology
Volume70
DOIs
Publication statusPublished - 1 Feb 2016

Keywords

  • Decision making
  • Decision support
  • Impact study
  • Implementation
  • Mixed methods
  • Risk prediction model

Cite this