Assessment of the Benefits of Anesthesia Patient Risk Reduction Measures

  • M. Elisabeth Paté-Cornell
Part of the International Series in Operations Research & Management Science book series (ISOR, volume 70)


This chapter presents an analytical framework based on Bayesian analysis that was used to evaluate human and management risk factors for patients undergoing anesthesia, and the effects of a variety of proposed measures for mitigating those risks. More specifically, the analysis considers the frequency and the effects of various risk factors, the extent to which safety measures based on management improvements can decrease the chances that they occur, and the effects of these safety measures on patient risk. The analysis demonstrates that the accident sequences that had received the most attention because they had made the headlines were not the largest contributors to the overall patient risk. The analysis finds that most of the problems are not caused by rare events, but by more mundane factors such as fatigue and poor supervision of residents. Closer supervision of residents, periodic re-certification and simulator training appeared to be among the most potentially effective measures for reducing patient risk. A similar model can be applied to other medical problems involving risk, such as assessing the performance of surgeons or early assessment of medical devices (before comprehensive testing on large populations).

Key words

Risk analysis Bayesian analysis Anesthesia 


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Copyright information

© Springer Science + Business Media, Inc. 2005

Authors and Affiliations

  • M. Elisabeth Paté-Cornell
    • 1
  1. 1.Department of Management Science and EngineeringStanford UniversityStanford

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