Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/105493
Type: Artigo de evento
Title: Management Technology For Health: Classification Of Medical And Hospital Equipment [gerenciamento De Tecnologia Para Saúde: Classificação De Equipamentos Médico-hospitalares]
Author: Silveira A.C.
Oshiyama N.F.
Bassani J.W.M.
Abstract: This paper presents a method for ranking and classification of medical equipment according to three maintenance indicators: NCC (number of corrective maintenance per year); TMC (total maintenance time per year, divided by the median of the maintenance time for the specific maintenance group) and $MC (maintenance cost, expressed as the total cost divided by 6% of the acquisition cost). A simple database containing equipment details and maintenance data, including the indicators and other relevant information, must be created. Equipment of the same type are separated in 3 age ranges (0-4, 5-9 and >10 years). In each range, mean ± SEM of NCC, TMC and $MC are calculated to establish 3 classes (A, B and C). A is compatible with newer equipment and considered better than the other classes. These classes are then considered as standards to classify each equipment. A given equipment is ranked A if it is A for all indicators, C if it is ranked C for at least one indicator, and otherwise it is B. One-way analysis of variance revealed that indicators vary with age (in most cases, increase), for different equipment types (ventilator, physiologic monitor and infusion pump). As an application, the 75 ventilators from the medical area of the Universidade Estadual de Campinas (UNICAMP) were analyzed. Data were obtained from the database of the Centro de Engenharia Biomédica at UNICAMP. Equipment ranked as C had an average age of 10 years. About 42% of the equipments ranked B were above 9 years old. However, one of the ventilators ranked C was only 3 years old. It was concluded that the proposed indicators and classification are helpful to detect unexpected behavior and can be applied to both management and data mining concerning the performance of the medical equipment. © Springer-Verlag Berlin Heidelberg 2007.
Editor: Springer Verlag
Rights: fechado
Identifier DOI: 10.1007/978-3-540-74471-9_192
Address: http://www.scopus.com/inward/record.url?eid=2-s2.0-84902152733&partnerID=40&md5=23abe5b9b23ef0178a313b1ac33f48a7
Date Issue: 2008
Appears in Collections:Unicamp - Artigos e Outros Documentos

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