Aplicación del modelo estocástico de Markov para predecir la degradación de infraestructuras hospitalarias

Abstract

Healthcare buildings are highly operational and have a complex and costly infrastructure. A high level of maintenance is required to ensure the quality of the healthcare service. The objective of this Doctoral Thesis is to optimise the maintenance operations carried out in hospital infrastructures, by applying a stochastic methodology based on Markov Chains. Markov prediction model was applied to evaluate the degradation of the different elements of hospital infrastructures over time. Therefore, maintenance decisions can be undertaken based on contrasted information that allows enlarging the service life of buildings, installations, and healthcare equipment. Maintenance analysis on system reliabilities allowed establishing the repair or replacement maintenance rates, reducing maintenance costs, minimising the impact associated with maintenance staff mobility, and increasing healthcare systems' operational sustainability. Besides, the prediction model happened to be a suitable tool for quantifying the increase in the service life of a system and comparing different construction solutions based on their reliability by increasing the level of maintainability of healthcare buildings. The knowledge generated in this Doctoral Thesis is useful for health system maintenance managers, since it allows establishing design criteria to improve hospital infrastructures. Furthermore, it allows optimal decisions to be made during the operation of both buildings and their equipment, covering their entire life cycle.