Teus H Kappen1, Kim van Loon2, Martinus A M Kappen2, Leo van Wolfswinkel2, Yvonne Vergouwe3, Wilton A van Klei2, Karel G M Moons4, Cor J Kalkman2. 1. Division of Anesthesiology, Department of Anesthesiology, Intensive Care and Emergency Medicine, University Medical Center Utrecht, P.O. Box 85500, Mail Stop F.06.149, Utrecht 3508 GA, The Netherlands. Electronic address: teus_kappen@yahoo.com. 2. Division of Anesthesiology, Department of Anesthesiology, Intensive Care and Emergency Medicine, University Medical Center Utrecht, P.O. Box 85500, Mail Stop F.06.149, Utrecht 3508 GA, The Netherlands. 3. Julius Center for Health Sciences and Primary Care, Department of Epidemiology, University Medical Center Utrecht, P.O. Box 85500, Mail Stop STR.6.131, Utrecht 3508 GA, The Netherlands; Department of Public Health, Erasmus Medical Center, P.O. Box 1738, Rotterdam 3000 DR, South Holland, The Netherlands. 4. Division of Anesthesiology, Department of Anesthesiology, Intensive Care and Emergency Medicine, University Medical Center Utrecht, P.O. Box 85500, Mail Stop F.06.149, Utrecht 3508 GA, The Netherlands; Julius Center for Health Sciences and Primary Care, Department of Epidemiology, University Medical Center Utrecht, P.O. Box 85500, Mail Stop STR.6.131, Utrecht 3508 GA, The Netherlands.
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.
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.
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