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