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|Type:||Artigo de evento|
|Title:||Health Technology Management: Medical Equipment Classification|
|Abstract:||This paper presents two methods for medical equipment classification according to three maintenance indicators (NCC = annual number of corrective maintenances divided by the median of the number of corrective maintenances for the specific maintenance group; TMC = time spent on corrective maintenance per year divided by the median of the time for the specific maintenance group, MC = annual cost of corrective maintenance divided by 6% of the depreciated acquisition cost of the equipment). The main tool was a simple database for each type of equipment. As shown in a previous paper, one of the methods is based on the fact that the indicator values increase as the equipment gets older. The other method is based on the ABC analysis, in which three limits were established based on Pareto's law. Data of syringe infusion pumps from years 2004 - 2006 (database of the Center for Biomedical Engineering, University of Campinas) were used. One-way analysis of variance revealed that NCc, TMc and Mc values increase significantly with age. Out of 50 syringe infusion pumps, 42% were classified as C, although 80% of the equipments were not in the 10-14 year category. The results of the ABC and age analyses were 96% coincident. Maintenance indicators seem to keep a relation with the equipment age and, if used in nationwide scale, they might be a robust tool for equipment classification. Unexpected behaviors may be relevant warnings to the Clinical Engineering staff, regulatory agencies and manufacturers interested in data mining. © 2009 Springer Berlin Heidelberg.|
|Appears in Collections:||Unicamp - Artigos e Outros Documentos|
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