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A Modeling Framework for Exposing Risks in Complex Systems

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  • Joseph Sharit

Abstract

This article introduces and develops a modeling framework for exposing risks in the form of human errors and adverse consequences in high‐risk systems. The modeling framework is based on two components: a two‐dimensional theory of accidents in systems developed by Perrow in 1984, and the concept of multiple system perspectives. The theory of accidents differentiates systems on the basis of two sets of attributes. One set characterizes the degree to which systems are interactively complex; the other emphasizes the extent to which systems are tightly coupled. The concept of multiple perspectives provides alternative descriptions of the entire system that serve to enhance insight into system processes. The usefulness of these two model components derives from a modeling framework that cross‐links them, enabling a variety of work contexts to be exposed and understood that would otherwise be very difficult or impossible to identify. The model components and the modeling framework are illustrated in the case of a large and comprehensive trauma care system. In addition to its general utility in the area of risk analysis, this methodology may be valuable in applications of current methods of human and system reliability analysis in complex and continually evolving high‐risk systems.

Suggested Citation

  • Joseph Sharit, 2000. "A Modeling Framework for Exposing Risks in Complex Systems," Risk Analysis, John Wiley & Sons, vol. 20(4), pages 469-482, August.
  • Handle: RePEc:wly:riskan:v:20:y:2000:i:4:p:469-482
    DOI: 10.1111/0272-4332.204045
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    Cited by:

    1. Anders Jensen & Terje Aven, 2017. "Hazard/threat identification: Using functional resonance analysis method in conjunction with the Anticipatory Failure Determination method," Journal of Risk and Reliability, , vol. 231(4), pages 383-389, August.
    2. Joseph Sharit & Lorgia McCane & Deborah M. Thevenin & Paul Barach, 2008. "Examining Links Between Sign‐Out Reporting During Shift Changeovers and Patient Management Risks," Risk Analysis, John Wiley & Sons, vol. 28(4), pages 969-981, August.
    3. James H. Lambert & Rachel K. Jennings & Nilesh N. Joshi, 2006. "Integration of risk identification with business process models," Systems Engineering, John Wiley & Sons, vol. 9(3), pages 187-198, September.
    4. David M. Vanlandingham & Wesley Hampton & Kimberly M. Thompson & Kamran Badizadegan, 2020. "Modeling Pathology Workload and Complexity to Manage Risks and Improve Patient Quality and Safety," Risk Analysis, John Wiley & Sons, vol. 40(2), pages 421-434, February.
    5. James H. Lambert & Benjamin L. Schulte & Priya Sarda, 2005. "Tracking the complexity of interactions between risk incidents and engineering systems," Systems Engineering, John Wiley & Sons, vol. 8(3), pages 262-277, September.

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