Featured Application The article provides two applications of the Functional Resonance Analysis Method (FRAM) in the healthcare sector. These analyses can be used as a reference by safety managers and practitioners prospectively and retrospectively for the effective risk assessment of interoperable medical device systems.Abstract In the recent literature, numerous tools have been found that have been used to evaluate and improve the resilience of socio-technical systems such as hospitals. The Functional Resonance Analysis Method (FRAM) is certainly one of the most diffused, as it can provide information on the system structure and its components through a systemic analysis approach. FRAM has been successfully applied in different contexts. However, in the healthcare sector, only a few studies propose practical analyses that can support practitioners in systematically observing and analyzing events, both when things go right and when they go wrong. To reduce such a research gap, the current study focuses on the application of FRAM to two different case studies: (1) an accident that occurred in a hyperbaric oxygen therapy unit, and (2) the risk assessment of a magnetic resonance imaging unit. The results show the effectiveness of FRAM in detecting discrepancies and vulnerabilities in the practical management of these devices, providing valuable insights not only regarding the analysis of adverse events (i.e., retrospectively) but also concerning the improvement of safety procedures (i.e., prospectively).

The functional resonance analysis method (fram) application in the healthcare sector: lessons learned from two case studies on medical device management / Fargnoli, Mario; Murgianu, Luca; Tronci, Massimo. - In: APPLIED SCIENCES. - ISSN 2076-3417. - 14:20(2024), pp. 1-19. [10.3390/app14209495]

The functional resonance analysis method (fram) application in the healthcare sector: lessons learned from two case studies on medical device management

Mario Fargnoli
;
Massimo Tronci
2024

Abstract

Featured Application The article provides two applications of the Functional Resonance Analysis Method (FRAM) in the healthcare sector. These analyses can be used as a reference by safety managers and practitioners prospectively and retrospectively for the effective risk assessment of interoperable medical device systems.Abstract In the recent literature, numerous tools have been found that have been used to evaluate and improve the resilience of socio-technical systems such as hospitals. The Functional Resonance Analysis Method (FRAM) is certainly one of the most diffused, as it can provide information on the system structure and its components through a systemic analysis approach. FRAM has been successfully applied in different contexts. However, in the healthcare sector, only a few studies propose practical analyses that can support practitioners in systematically observing and analyzing events, both when things go right and when they go wrong. To reduce such a research gap, the current study focuses on the application of FRAM to two different case studies: (1) an accident that occurred in a hyperbaric oxygen therapy unit, and (2) the risk assessment of a magnetic resonance imaging unit. The results show the effectiveness of FRAM in detecting discrepancies and vulnerabilities in the practical management of these devices, providing valuable insights not only regarding the analysis of adverse events (i.e., retrospectively) but also concerning the improvement of safety procedures (i.e., prospectively).
2024
hyperbaric-oxygen therapy; accident causation; intensive-care; tell us; safety; variability; performance; resilience; framework; discharge
01 Pubblicazione su rivista::01a Articolo in rivista
The functional resonance analysis method (fram) application in the healthcare sector: lessons learned from two case studies on medical device management / Fargnoli, Mario; Murgianu, Luca; Tronci, Massimo. - In: APPLIED SCIENCES. - ISSN 2076-3417. - 14:20(2024), pp. 1-19. [10.3390/app14209495]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1731411
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