Health Care Technology Replacement Planning

Clark, J. Tobey

doi:10.1016/b978-012226570-9/50046-6

Cited by 4 publications

(1 citation statement)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this study, equipment age was chosen as the criterion for establishment of classes because, with constant use, replacement of parts tends to occur more often, and preventive maintenance may be required more frequently. This is an important criterion, since equipment reaches a point in its life-cycle at which frequent failure leads to greater downtime and diminished cost-benefit ratio (Clark, 2004). It was hypothesized, therefore, that corrective maintenance data (i.e., frequency, duration and cost of services, which can be easily extracted from the database) would provide suitable indicators for the establishment of age-based classes, on the assumption that older equipment usually fails more often than recently acquired ones.…”

Section: Introductionmentioning

confidence: 99%

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

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.

show abstract

Section: Introductionmentioning

confidence: 99%

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

Safety Program, Hospital

Dyro¹

2006

Encyclopedia of Medical Devices and Instrumentation

View full text Add to dashboard Cite

This article describes the broad scope of safety issues in the hospital and recommends ways in which hospitals should address these issues. Particular emphasis is placed on medical devices and instrumentation and how they interrelate with the hospital’s environment, facility, patients and device users and other personnel. Medical device safety depends in large part upon a comprehensive medical device technology management program, which includes elements ranging from technology assessment, evaluation, and procurement to device replacement planning and includes such components as user training, medical device incident investigation, and device quality assurance. The clinical engineer by education, training and experience is shown to be ideally suited to implement and execute a technology management program and to lead in the effort to assure hospital‐wide patient safety. Available resources are described including web‐based training, distance learning, standards, publications, and professional organizations.

show abstract