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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)

Summary

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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References

  1. [1]
    Paté-Cornell, M.E., D.M. Murphy, L.M. Lakats and D.M. Gaba (1996). Patient risk in anesthesia: Probabilistic risk analysis, management effects and improvements. Annals of Operations Research, 67, 211–233.CrossRefGoogle Scholar
  2. [2]
    Paté-Cornell, M.E., L.M. Lakats, D.M. Murphy, and D.M. Gaba (1997). Anesthesia patient risk: A quantitative approach to organizational factors and risk management options. Risk Analysis, 17, 511–523.PubMedCrossRefGoogle Scholar
  3. [3]
    Paté-Cornell, M.E. (1999). Medical application of engineering risk analysis and anesthesia patient risk illustration. American Journal of Therapeutics, 6, 245–255.PubMedCrossRefGoogle Scholar
  4. [4]
    Kaplan, S. and B.J. Garrick (1981). On the quantitative definition of risk. Risk Analysis, 1, 11–27.CrossRefGoogle Scholar
  5. [5]
    US Nuclear Regulatory Commission (1975). The Reactor Safety Study. WASH-1400, Washington, DC.Google Scholar
  6. [6]
    Paté-Cornell, M.E. and P.S. Fischbeck (1994). Risk management for the tiles of the space shuttle. Interfaces, 24, 64–86.CrossRefGoogle Scholar
  7. [7]
    Hillier, F.S. and G.J. Lieberman (1990). Introduction to Operations Research. McGraw-Hill, New York.Google Scholar
  8. [8]
    Davies, J. M., and L. Strunin (1984). Anesthesia in 1984: How safe is it? Canadian Medical Association Journal, 131, 437–441.PubMedGoogle Scholar
  9. [9]
    Runciman, W.B., A. Sellen, R.K. Webb, J.A. Williamson, M. Currie, C. Morgan, and W.J. Russell (1993). Errors, incidents and accidents in anaesthetic practice. Anaesthesia and Intensive Care, 21, 506–519.PubMedGoogle Scholar
  10. [10]
    Murphy, D.M. and M.E. Paté-Cornell (1996). The SAM framework: A systems analysis approach to modeling the effects of management on human behavior in risk analysis. Risk Analysis, 16, 501–515.PubMedCrossRefGoogle Scholar
  11. [11]
    Paté-Cornell, M.E. and D.M. Murphy (1996). Human and management factors in probabilistic risk analysis: the SAM approach and observations from recent applications. Reliability Engineering and System Safety, 53, 115–126.CrossRefGoogle Scholar
  12. [12]
    Paté-Cornel1, M.E. (1990). Organizational aspects of engineering system safety: the case of offshore platforms. Science, 250, 1210–1217.ADSCrossRefGoogle Scholar
  13. [13]
    Gaba, D.M. (1992). Improving anesthesiologists’ performance by simulating reality. Anesthesiology, 76, 491–494.PubMedCrossRefGoogle Scholar
  14. [14]
    Gaba, D.M. (1994). Human work environment and simulators. In Miller, R.D., Ed., Anesthesia. Churchill Livingstone, New York, Chapter 85.Google Scholar
  15. [15]
    Pietzsch, J.B., T.M. Krummel and M.E. Paté-Cornell (2002). Early technology assessment of new medical devices and procedures: A systems analysis approach using probabilistic modeling. Proceedings of ISTAHC2002, 18 th Annual Meeting of the International Society of Technology Assessment in Health Care, Berlin, Germany, June 2002.Google Scholar

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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