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Application of a decision support system for providing better mental health care: the case of the Basque Country (Spain)

Published online by Cambridge University Press:  01 September 2022

N. Almeda ,
C. García-Alonso  and
L. Salvador-Carulla
N. Almeda*
Affiliation:
Loyola University, Psychology, Seville, Spain
C. García-Alonso
Affiliation:
Loyola University, Quantitative Methods, Seville, Spain
L. Salvador-Carulla
Affiliation:
University of Canberra, Faculty Of Health, Canberra, Australia
*
*Corresponding author.

Abstract

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Introduction

Decision Support Systems (DSS) are appropriate tools for guiding policymaking processes in Mental Health (MH) management, especially where a balanced and integrated care provision is required.

Objectives

To assess the performance of a MH ecosystem for identifying benchmark and target-for-improvement catchment areas according to the Balanced Care model.

Methods

The MH provision, distinguishing inpatient, day and outpatient main types of care, has been assessed in the Mental Health Network of Gipuzkoa (Basque Country, Spain) using a DSS, integrating Data Envelopment Analysis, Monte-Carlo Simulation and Artificial Intelligence. 13 catchment areas, defined by a reference MH centre, are the units (universe) for the analysis. The indicators for MH ecosystem performance were: relative technical efficiency, stability and entropy, for identifying both benchmarking and target-for-improvement areas. The analysis of the differences between the two groups can be used to design organizational interventions.

Results

The Mental Health Network of Gipuzkoa showed high global efficiency scores, but it can be considered statistically unstable (small changes in variable values can have relevant impacts on its performance). For a global performance improvement, it is recommended to reduce admissions and readmissions in inpatient care, increase workforce capacity and utilization of day care services and, finally, increase the availability of outpatient care services.

Conclusions

This research offers a guide for evidence-informed policy-making to improve MH care provision in the main types of care and provide aftercare. The characteristics of the area to be improved are critical to design interventions and assess their potential impact on the MH ecosystem.

Disclosure

No significant relationships.

Keywords

Mental health servicesPolicymakingEfficiencymental health care
Type
Abstract
Information
European Psychiatry , Volume 65 , Special Issue S1: Abstracts of the 30th European Congress of Psychiatry , June 2022 , pp. S631
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© The Author(s), 2022. Published by Cambridge University Press on behalf of the European Psychiatric Association
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