Since the management and maintenance of biomedical equipment constitute a considerable economic commitment for the hospitals, the purpose of the current work is to provide an effective mathematical-statistical tool, based on the parametric distribution of Vilfredo Pareto, allowing both a rapid analysis and optimization of costs. Pareto's principle states that about 20% of the causes produces 80% of the effects and the goal, in this study, is to determine the minority group of biomedical equipment that has the greatest impact on hospital costs, allowing the implementation of a strategy for the rationalization of economic resources. Pareto's analysis is applied to three different case studies: firstly, to the purchase values of all the biomedical equipment; secondly, to the purchase values of the technologies resulting from eliminating the clinical department with major economic impact; and, finally, to the maintenance costs of the biomedical equipment in both cases. Real data, from the Clinical Engineering Service of the University Hospital Campus Bio-Medico have been utilized. Results indicate that a small number of biomedical equipment (between 7% and 13% of the total) require 80% of the annual overall maintenance cost, and consequently, concentrating the cost optimization policy exclusively on this small fraction of technologies it is possible to obtain considerable economic savings.

An adaptation of Pareto's parametric distribution as a support tool for the analysis of maintenance costs of biomedical equipment

Silvestri S
2021-01-01

Abstract

Since the management and maintenance of biomedical equipment constitute a considerable economic commitment for the hospitals, the purpose of the current work is to provide an effective mathematical-statistical tool, based on the parametric distribution of Vilfredo Pareto, allowing both a rapid analysis and optimization of costs. Pareto's principle states that about 20% of the causes produces 80% of the effects and the goal, in this study, is to determine the minority group of biomedical equipment that has the greatest impact on hospital costs, allowing the implementation of a strategy for the rationalization of economic resources. Pareto's analysis is applied to three different case studies: firstly, to the purchase values of all the biomedical equipment; secondly, to the purchase values of the technologies resulting from eliminating the clinical department with major economic impact; and, finally, to the maintenance costs of the biomedical equipment in both cases. Real data, from the Clinical Engineering Service of the University Hospital Campus Bio-Medico have been utilized. Results indicate that a small number of biomedical equipment (between 7% and 13% of the total) require 80% of the annual overall maintenance cost, and consequently, concentrating the cost optimization policy exclusively on this small fraction of technologies it is possible to obtain considerable economic savings.
2021
cost optimization, biomedical equipment maintenance, management
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12610/15515
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