Patient risk in anaesthesia: Probabilistic risk analysis and management improvements

In this paper, the authors present a pilot study in which they use probabilistic risk analysis (PRA) to assess patient risk in anaesthesia and its human factor component. The authors then identify and evaluate the benefits of several risk reduction policies. They focus on healthy patients, in modern hospitals, and on cases where the anaesthetist is a trained medical doctor. When an accident occurs for such patients, it is often because an error was made by the anaesthesiologist, either triggering the event that initiated the accident sequence, or failing to take timely corrective measures. The authors present first a dynamic PRA model of anaesthesia accidents. The present data include published results of the Australian Incident Monitoring Study as well as expert opinions. The authors link the probabilities of the different types of accidents to the ‘state of the anaesthesiologist’ characterized both in terms of alertness and competence. They consider different management factors that affect the state of the anaesthesiologist, the authors identify several risk reduction policies, and they compute the corresponding risk reduction benefits based on the PRA model. The authors conclude that periodic recertification of all anaesthesiologists, the use of anaesthesia simulators in training, and closer supervision of residents could reduce substantially the patient risk.