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.
Keywords
Risk prediction model
Decision support
Mixed methods
Impact study
Decision making
Implementation
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Funding: This work was supported by The Netherlands Organization for Health Research and Development (ZonMW), The Hague, South Holland, The Netherlands. ZonMW grant numbers: 945.16.202, 912.08.004, and 918.10.615.
Role of the sponsors: The funding agreement ensured the authors' independence in design and conduct of the study; collection, management, analysis, and interpretation of the data; and preparation, review, or approval of the manuscript.