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Mental disorders cause an enormous burden to society. Considering the current economic context, an efficient use of scarce inputs, with an appropriate outcome production, is crucial. This situation defines a classical Relative Technical Efficiency (RTE) problem. A well-known methodology to assess RTE is the Data Envelopment Analysis, although it presents some limitations. These may be overcome through a hybrid strategy that integrates Monte-Carlo simulation and artificial intelligence. This study aims to (1) design of a Decision Support System for the assessment of RTE of Small Mental Health Areas based on DEA; and (2) analyse 19 mental health areas of the Bizkaian Healthcare System (Spain) to classify them and to identify potential management improvements. The results have showed higher global RTE in the output-oriented orientation than in the input-oriented one. This suggests that a decision strategy based on improving the input management, within the ranges of the expert-driven model of community healthcare, could be appropriate. A future research line will focus our attention on the validation process through the analysis of micromanagement interventions and their potential impacts in the real system.

Assessment of Relative Technical Efficiency of Small Mental Health Areas in Bizkaia (Basque Country, Spain)