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

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

Reducing medical device alarms by an order of magnitude: A human factors approach

The intensive care unit (ICU) is one of the most technically advanced environments in healthcare, using a multitude of medical devices for drug administration, mechanical ventilation and patient monitoring. However, these technologies currently come with disadvantages, namely noise pollution, information overload and alarm fatigue—all caused by too many alarms. Individual medical devices currently generate alarms independently, without any coordination or prioritisation with other devices, leading to a cacophony where important alarms can be lost amongst trivial ones, occasionally with serious or even fatal consequences for patients. We have called this approach to the design of medical devices the single-device paradigm, and believe it is obsolete in modern hospitals where patients are typically connected to several devices simultaneously. Alarm rates of one alarm every four minutes for only the physiological monitors (as recorded in the ICUs of two hospitals contributing to this paper) degrades the quality of the patient’s healing environment and threatens patient safety by constantly distracting healthcare professionals. We outline a new approach to medical device design involving the application of human factors principles which have been successful in eliminating alarm fatigue in commercial aviation. Our approach comprises the networked-device paradigm, comprehensive alarms and humaniform information displays. Instead of each medical device alarming separately at the patient’s bedside, our proposed approach will integrate, prioritise and optimise alarms across all devices attached to each patient, display information more intuitively and hence increase alarm quality while reducing the number of alarms by an order of magnitude below current levels