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

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Elsevier Sci Ltd

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info:eu-repo/semantics/closedAccess

Özet

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.

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FRAM, Monte Carlo simulations, Performance variability, Resilience, Risk assessment

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Reliability Engineering & System Safety

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202

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Onay

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