Contents lists available at ScienceDirect Reliability Engineering and System Safety journal homepage: www.elsevier.com/locate/ress Resilience engineering for socio-technical risk analysis: Application in neuro-surgery Riccardo Patriarca a,⁎, Andrea Falegnami a , Francesco Costantino a , Federico Bilotta b a Department of Mechanical and Aerospace Engineering, Sapienza University of Rome, Italy b Department of Anesthesiology, Critical Care and Pain Medicine, Sapienza University of Rome, Italy A R T I C L E I N F O Keywords: System safety Complex systems Resilience engineering Resilience indicators Healthcare management Healthcare engineering Patient pathway A B S T R A C T Healthcare practitioners are generally forced to adapt their actions to cope with the complexity of daily con- ditions, taking advantage of their inherent potential for resilient performance. Following the principles of Resilience Engineering, this article details the application of the Functional Resonance Analysis Method (FRAM), for a semi-quantitative risk analysis of patient's pathway. The analysis adopts a holistic perspective on the complexity of everyday work in order to manage emergent behaviours, mainly related to iatrogenic disease associated with neuro-anesthesia treatment. Enhancing the traditional FRAM approach, the paper presents a structured systemic analysis for a case study in the neurosurgery peri‑operative patient's pathway. A multi-layer semi-quantitative framework is used as a basis for a novel decision support tool: the Variability Impact Matrix (VIM). The VIM aids to prioritize corrective measures and the need for functional performance indicators. A combination of social and technical perspectives is confirmed being necessary to cope with complex work environments, such as healthcare practices.
Resilience engineering for socio-technical risk analysis. Application in neuro-surgery / Patriarca, Riccardo; Falegnami, Andrea; Costantino, Francesco; Bilotta, Federico. - In: RELIABILITY ENGINEERING & SYSTEM SAFETY. - ISSN 0951-8320. - 180:(2018), pp. 321-335. [10.1016/j.ress.2018.08.001]
Resilience engineering for socio-technical risk analysis. Application in neuro-surgery
Patriarca, Riccardo
;FALEGNAMI, ANDREA;Costantino, Francesco;Bilotta, Federico
2018
Abstract
Contents lists available at ScienceDirect Reliability Engineering and System Safety journal homepage: www.elsevier.com/locate/ress Resilience engineering for socio-technical risk analysis: Application in neuro-surgery Riccardo Patriarca a,⁎, Andrea Falegnami a , Francesco Costantino a , Federico Bilotta b a Department of Mechanical and Aerospace Engineering, Sapienza University of Rome, Italy b Department of Anesthesiology, Critical Care and Pain Medicine, Sapienza University of Rome, Italy A R T I C L E I N F O Keywords: System safety Complex systems Resilience engineering Resilience indicators Healthcare management Healthcare engineering Patient pathway A B S T R A C T Healthcare practitioners are generally forced to adapt their actions to cope with the complexity of daily con- ditions, taking advantage of their inherent potential for resilient performance. Following the principles of Resilience Engineering, this article details the application of the Functional Resonance Analysis Method (FRAM), for a semi-quantitative risk analysis of patient's pathway. The analysis adopts a holistic perspective on the complexity of everyday work in order to manage emergent behaviours, mainly related to iatrogenic disease associated with neuro-anesthesia treatment. Enhancing the traditional FRAM approach, the paper presents a structured systemic analysis for a case study in the neurosurgery peri‑operative patient's pathway. A multi-layer semi-quantitative framework is used as a basis for a novel decision support tool: the Variability Impact Matrix (VIM). The VIM aids to prioritize corrective measures and the need for functional performance indicators. A combination of social and technical perspectives is confirmed being necessary to cope with complex work environments, such as healthcare practices.File | Dimensione | Formato | |
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