Medical equipment classification according to corrective maintenance data: a strategy based on the equipment age
| Autor: | Rosana A. Bassani, Natália F. Oshiyama, Ana Carolina Silveira, José Wilson Magalhães Bassani |
|---|---|
| Rok vydání: | 2014 |
| Předmět: |
Engineering
Class (computer programming) medicine.medical_specialty Corrective maintenance business.industry Biomedical Engineering Medical equipment management Medical equipment Reliability engineering Identification (information) Maintenance testing Computerized maintenance management system medicine Operations management business Clinical engineering |
| Zdroj: | Revista Brasileira de Engenharia Biomédica. 30:64-69 |
| ISSN: | 1984-7742 1517-3151 |
| Popis: | INTRODUCTION: Decision-making on medical equipment management is a daily task for clinical engineers, but it may prove difficult to easily extract relevant information from the large amount of data from computerized maintenance management systems. This article describes a simple method of medical equipment classification based on corrective maintenance indicators. METHODS: Three indicators were calculated based on the number of events, duration and cost of corrective maintenance. Three classes were defined according to the indicator values of different equipment ages: class A for 0-4 years, class B for 5-9 years, and class C for equipment older than 10 years. The method was applied to 2,134 pieces of equipment from the Health Service system of the University of Campinas. RESULTS: From the total, 51.7% of the equipment were classified as C, 4.2% as B and 44.1% as A. The infusion pump for general use was the type of equipment of which most units were in the C class (84.7%), even though almost 50% of them were acquired within less than 9 years, and would thus be expected to be classified as A and B. Among the pumps in class C, 39.5% were from a single manufacturer, although the equipments were acquired recently. CONCLUSION: The developed classification may be an important tool for raising alerts about equipment more prone to maintenance problems, as well as for identification of equipments with acceptable maintenance history, supporting decision-making on equipment replacement. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|