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Anesthesia Patient Risk: A Quantitative Approach to Organizational Factors and Risk Management Options
Author(s) -
PatéCornell M. Elisabeth,
Lakats Linda M.,
Murphy Dean M.,
Gaba David M.
Publication year - 1997
Publication title -
risk analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.972
H-Index - 130
eISSN - 1539-6924
pISSN - 0272-4332
DOI - 10.1111/j.1539-6924.1997.tb00892.x
Subject(s) - alertness , risk management , probabilistic risk assessment , risk assessment , competence (human resources) , risk analysis (engineering) , medical emergency , medicine , risk management information systems , patient safety , affect (linguistics) , psychology , business , engineering , computer science , computer security , psychiatry , information system , management information systems , health care , social psychology , communication , finance , economic growth , economics , electrical engineering
The risk of death or brain damage to anesthesia patients is relatively low, particularly for healthy patients in modern hospitals. When an accident does occur, its cause is usually an error made by the anesthesiologist, either in triggering the accident sequence, or failing to take 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 management 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 probabilistic analysis of the performance shaping factors. These factors are described 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 anesthesiologist and we compute the risk reduction benefits of several risk management policies. Our data sources include the published version of the Australian Incident Monitoring Study as well as expert opinions. We conclude that patient risk could be reduced substantially by closer supervision of residents, the use of anesthesia simulators both in training and for periodic recertification, and regular medical examinations for all anesthesiologists.