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Semi-quantitative application to the Functional Resonance Analysis Method for supporting safety management in a complex health-care process

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  • Kaya, Gulsum Kubra
  • Hocaoglu, Mehmet Fatih

Abstract

In complex systems, as in health care, traditional safety management methods have limited capability to understand the system as a whole. The Functional Resonance Analysis Method (FRAM) has been introduced to overcome this challenge. This study applied a semi-quantitative approach to the FRAM on the basis of Monte Carlo simulation to gain an in-depth understanding of the drug administration process and, in turn, to manage performance variability and to support safety management. The contributions of this paper are twofold. Firstly, this study revealed that the semi-quantitative approach to the FRAM facilitates a clear understanding of the critical interactions in the FRAM model. Secondly, the use of the simulation generated a large number of different real-life scenarios to be examined, which is likely to contribute to situational awareness.

Suggested Citation

  • Kaya, Gulsum Kubra & Hocaoglu, Mehmet Fatih, 2020. "Semi-quantitative application to the Functional Resonance Analysis Method for supporting safety management in a complex health-care process," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    • Handle: RePEc:eee:reensy:v:202:y:2020:i:c:s0951832019314103
    DOI: 10.1016/j.ress.2020.106970
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    References listed on IDEAS

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    1. Patriarca, Riccardo & Bergström, Johan & Di Gravio, Giulio, 2017. "Defining the functional resonance analysis space: Combining Abstraction Hierarchy and FRAM," Reliability Engineering and System Safety, Elsevier, vol. 165(C), pages 34-46.
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    4. Kaya, Gulsum Kubra & Ozturk, Fatih & Sariguzel, Emine Emel, 2021. "System-based risk analysis in a tram operating system: Integrating Monte Carlo simulation with the functional resonance analysis method," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    5. Yu, Yuerong & Liu, Kezhong & Fu, Shanshan & Chen, Jihong, 2024. "Framework for process risk analysis of maritime accidents based on resilience theory: A case study of grounding accidents in Arctic waters," Reliability Engineering and System Safety, Elsevier, vol. 249(C).
    6. Simsekler, Mecit Can Emre & Rodrigues, Clarence & Qazi, Abroon & Ellahham, Samer & Ozonoff, Al, 2021. "A comparative study of patient and staff safety evaluation using tree-based machine learning algorithms," Reliability Engineering and System Safety, Elsevier, vol. 208(C).

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