Ensuring the optimal operation and longevity of medical devices is essential for maintaining high safety standards in healthcare. This study presents a significant advancement in the field by enhancing an existing evidence-based maintenance (EBM) framework, which is crucial for the effective management of medical equipment. Building upon previous methodologies, this research introduces a novel, comprehensive taxonomy for categorizing maintenance reports by revising and updating existing failure codes. This refinement addresses gaps in previous models, enabling more precise and effective maintenance strategies. A key innovation of this study is the development of a standard XML protocol, which addresses the current lack of standardization in the field, providing a consistent and unified approach to data management. This standardization is critical for improving communication and data exchange across different healthcare systems and technologies. To validate the enhanced EBM framework, the study applies it to corrective maintenance work orders related to Digital Angiography Systems, Magnetic Resonance Imaging, and Computed Tomography, using data from the Pisa University Hospital's Computerized Maintenance Management System from 2021 to 2022. This validation demonstrates the reproducibility and adaptability of the framework across different medical equipment, healthcare contexts, and timeframes. The findings represent a significant advancement in healthcare technology management, offering a robust, standardized approach that optimizes the safety, functionality, and longevity of medical devices. This research not only expands maintenance standards in the healthcare sector but also provides a critical tool for addressing the current challenges in medical device maintenance, paving the way for more reliable and effective healthcare technologies.

Evidence based management of medical devices: A follow-up experiment / Crapanzano, Fabio; Luschi, Alessio; Satta, Francesca; Sani, Lorenzo; Iadanza, Ernesto. - In: BIOMEDICAL SIGNAL PROCESSING AND CONTROL. - ISSN 1746-8094. - STAMPA. - 99:(In corso di stampa), pp. 106867.0-106867.0. [10.1016/j.bspc.2024.106867]

Evidence based management of medical devices: A follow-up experiment

Satta, Francesca;Sani, Lorenzo;
In corso di stampa

Abstract

Ensuring the optimal operation and longevity of medical devices is essential for maintaining high safety standards in healthcare. This study presents a significant advancement in the field by enhancing an existing evidence-based maintenance (EBM) framework, which is crucial for the effective management of medical equipment. Building upon previous methodologies, this research introduces a novel, comprehensive taxonomy for categorizing maintenance reports by revising and updating existing failure codes. This refinement addresses gaps in previous models, enabling more precise and effective maintenance strategies. A key innovation of this study is the development of a standard XML protocol, which addresses the current lack of standardization in the field, providing a consistent and unified approach to data management. This standardization is critical for improving communication and data exchange across different healthcare systems and technologies. To validate the enhanced EBM framework, the study applies it to corrective maintenance work orders related to Digital Angiography Systems, Magnetic Resonance Imaging, and Computed Tomography, using data from the Pisa University Hospital's Computerized Maintenance Management System from 2021 to 2022. This validation demonstrates the reproducibility and adaptability of the framework across different medical equipment, healthcare contexts, and timeframes. The findings represent a significant advancement in healthcare technology management, offering a robust, standardized approach that optimizes the safety, functionality, and longevity of medical devices. This research not only expands maintenance standards in the healthcare sector but also provides a critical tool for addressing the current challenges in medical device maintenance, paving the way for more reliable and effective healthcare technologies.
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Crapanzano, Fabio; Luschi, Alessio; Satta, Francesca; Sani, Lorenzo; Iadanza, Ernesto
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1391792
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