ANESTHESIA PATIENT RISK - A QUANTITATIVE APPROACH TO ORGANIZATIONAL-FACTORS AND RISK MANAGEMENT OPTIONS

The risk of death or brain damage to anesthesia patients is relatively low, particularly for healthy patients in modem hospitals. When an ac cident does occur, its cause is usually an error made by the anesthesi ologist, either in triggering the accident sequence, or failing to tak e timely corrective measures. This paper presents a pilot study which explores the feasibility of extending probabilistic risk analysis (PRA ) of anesthesia accidents to assess the effects of human and managemen t components on the patient risk. We develop first a classic PRA model for the patient risk per operation. We then link the probabilities of the different accident types to their root causes using a probabilist ic analysis of the performance shaping factors. These factors are desc ribed here as the ''state of the anesthesiologist'' characterized both in terms of alertness and competence. We then analyze the effects of different management factors that affect the state of the anesthesiolo gist and we compute the risk reduction benefits of several risk manage ment policies. Our data sources include the published version of the A ustralian Incident Monitoring Study as well as expert opinions. We con clude that patient risk could be reduced substantially by closer super vision of residents, the use of anesthesia simulators both in training and for periodic recertification, and regular medical examinations fo r all anesthesiologists.