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Optimization of Maintenance in Critical Equipment in Neonatology

Optimization of Maintenance in Critical Equipment in Neonatology
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Author(s): María Carmen Carnero (University of Castilla-La Mancha, Spain & University of Lisbon, Portugal)and Andrés Gómez (University of Castilla-La Mancha, Spain)
Copyright: 2017
Pages: 23
Source title: Handbook of Research on Data Science for Effective Healthcare Practice and Administration
Source Author(s)/Editor(s): Elham Akhond Zadeh Noughabi (University of Calgary, Canada), Bijan Raahemi (University of Ottawa, Canada), Amir Albadvi (Tarbiat Modares University, Iran)and Behrouz H. Far (University of Calgary, Canada)
DOI: 10.4018/978-1-5225-2515-8.ch002

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Abstract

Maintenance decisions by medical staff play an essential role in achieving availability, quality and safety in care services provided. This has, in turn, an effect on the quality of care perceived by patients. Nonetheless, despite its importance, there is a serious deficiency in models facilitating optimization of maintenance decisions in critical care equipment. This chapter shows a decision support system (DSS) for choosing the best combination of maintenance policies, together with other actions for improvement, such as the increase in the number of back-up devices used in the assisted breathing unit in the Neonatology Service of a hospital. This DSS is combined with an innovative form of continuous time Markov chains, and the multicriteria Measuring Attractiveness by a Categorical Based Evaluation Technique (MACBETH). The result is a ranking of the various maintenance alternatives to be applied. Finally, the real implications for availability and quality of care of applying the best solution are described.

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