Cytotoxic drugs are prepared in pharmacy systems, and therefore the operation of these systems can have a direct influence on patients. This study describes a Decision Support System (DSS) for the optimal selection of a combination of maintenance policies to improve hospital pharmacy systems. The DSS is created using the fuzzy multicriteria Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The judgements required in the DSS were provided by a group made up of the heads of Facilities maintenance, Maintenance of medical equipment, Health and safety at work, Environment, and Programming-admission, Main clinical services, and the Medical supervisors, of a Spanish hospital. The DSS is constructed with the criteria: Costs (with subcriteria Investment costs and Maintenance cost), Quality of health care (evaluated with the mean availability), Impact on hospital management (with subcriteria Working environment in the organisation and Impact on health care) and Maintenance planning optimisation. Descriptors with five scale-levels permitted each alternative to be accurately assessed. The alternatives were: Corrective and preventive maintenance, Corrective and preventive maintenance plus a spare hood, Corrective and preventive maintenance plus two spare hoods, and Corrective, preventive and predictive maintenance. The group evaluated each alternative via linguistic variables to obtain the fuzzy weights of the criteria and to evaluate each alternative in each criterion. The methodology of fuzzy TOPSIS determines that the Closeness Coefficient of the Corrective and Preventive Maintenance plus two spare hoods is 0.396 and is therefore the best decision, followed by Corrective, preventive and predictive maintenance with 0.382.

Authors:
María Carmen Carnero, University of Castilla-La Mancha, Spain

About the Presenter(s)
María Carmen Carnero is full professor in the Higher Technical School of Industrial Engineering in the University of Castilla-La Mancha (Spain)

See this presentation on the full schedule – On Demand Schedule

Bookmark