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Preventative maintenance and unscheduled downtime from an economic perspective

A spreadsheet‐based model for economically characterizing the operation of a radiation treatment program has been used to perform a quantitative financial analysis of scheduled and unscheduled downtime. The incremental cost of downtime is broken down into three categories: remuneration of in‐house o...

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Detalles Bibliográficos
Autores principales: Dunscombe, Peter, Roberts, Gisele, Valiquette, Lianne
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2000
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5726151/
https://www.ncbi.nlm.nih.gov/pubmed/11674820
http://dx.doi.org/10.1120/jacmp.v1i2.2647
Descripción
Sumario:A spreadsheet‐based model for economically characterizing the operation of a radiation treatment program has been used to perform a quantitative financial analysis of scheduled and unscheduled downtime. The incremental cost of downtime is broken down into three categories: remuneration of in‐house or third party service technologists, decreased patient capacity, and local operating procedures for dealing with downtime. Different service arrangements and operating procedures are simulated to demonstrate the financial cost of treatment machine unavailability due to either preventative maintenance or unexpected breakdown. Depending on the service arrangement and operating policies for accommodating downtime, the combined cost of scheduled and unscheduled downtime (at 5%) can exceed 10% of the total cost of the radiation treatment program. It has also been demonstrated that the greatest cost component of downtime is decreased patient capacity, which can exceed $400,000 (CAN) when unscheduled downtime reaches 5%. The interpretation of this cost depends on the funding environment. Although the emphasis of this study has been the financial consequences of downtime, there are other factors which must be considered when developing policies and procedures for accommodating downtime such as effects on treatment, patient convenience and quality of life for staff. Even though the numerical results are strictly valid only within the context of the simulations performed, they do provide a broad framework within which medical physicists can make recommendations regarding service support and downtime. © 2000 American College of Medical Physics. PACS number(s): 87.52.–g, 87.90.+y