An Event-Tree-Based Mathematical Formula for The Removal of Biomedical Equipment From a Hospital Inventory

Miguel-Cruz, Antonio; Denis, Ernesto Rodríguez; Villar, M C Sánchez; Gonzalez, L M Lic

doi:10.1097/00004669-200202710-00039

Cited by 9 publications

(1 citation statement)

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“…The cost (CM) was calculated by dividing the average annual cost of corrective maintenance (Annual(Cost)) by 6% of the equipment acquisition cost. This percentage is within the expected range of expenditure with corrective maintenance (3-15% of the acquisition cost; Cruz et al, 2002) and was calculated by the straight-line depreciation method (Albrecht et al, 2010) assuming a minimum equipment lifetime of 15 years. Because the age range of the equipment in this study was 0-14 years, the maximum depreciation would be 6.7 % per year.…”

Section: A Database (Microsoft Excelmentioning

confidence: 96%

Medical equipment classification according to corrective maintenance data: a strategy based on the equipment age

Oshiyama¹,

Silveira²,

Bassani³

et al. 2014

RBEB

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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.

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Section: A Database (Microsoft Excelmentioning

confidence: 96%

Medical equipment classification according to corrective maintenance data: a strategy based on the equipment age

Oshiyama¹,

Silveira²,

Bassani³

et al. 2014

RBEB

View full text Add to dashboard Cite

show abstract

Gestión Tecnológica Clínico-Hospitalaria

Rodríguez-Denis

Sanchez

Ferro

2007

IV Latin American Congress on Biomedical Engineering 2007, Bioengineering Solutions for Latin America Health

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Medical equipment classification: method and decision-making support based on paraconsistent annotated logic

Oshiyama

Bassani

D’Ottaviano

et al. 2012

Med Biol Eng Comput

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As technology evolves, the role of medical equipment in the healthcare system, as well as technology management, becomes more important. Although the existence of large databases containing management information is currently common, extracting useful information from them is still difficult. A useful tool for identification of frequently failing equipment, which increases maintenance cost and downtime, would be the classification according to the corrective maintenance data. Nevertheless, establishment of classes may create inconsistencies, since an item may be close to two classes by the same extent. Paraconsistent logic might help solve this problem, as it allows the existence of inconsistent (contradictory) information without trivialization. In this paper, a methodology for medical equipment classification based on the ABC analysis of corrective maintenance data is presented, and complemented with a paraconsistent annotated logic analysis, which may enable the decision maker to take into consideration alerts created by the identification of inconsistencies and indeterminacies in the classification.

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An Event-Tree-Based Mathematical Formula for The Removal of Biomedical Equipment From a Hospital Inventory

Cited by 9 publications

References 0 publications

Medical equipment classification according to corrective maintenance data: a strategy based on the equipment age

Medical equipment classification according to corrective maintenance data: a strategy based on the equipment age

Gestión Tecnológica Clínico-Hospitalaria

Medical equipment classification: method and decision-making support based on paraconsistent annotated logic

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