About this Journal


Article Abstract

Online ISSN: 1099-176X    Print ISSN: 1091-4358
The Journal of Mental Health Policy and Economics
Volume 10, Issue 2, 2007. Pages: 87-100
Published Online: 18 Jun 2007

Copyright © 2007 ICMPE.


 

Use of an Operational Model of Community Care to Assess Technical Efficiency and Benchmarking of Small Mental Health Areas in Spain

Luis Salvador-Carulla,1* Carlos Garc¡a-Alonso,2 Juan Luis Gonzalez-Caballero,3 Marco Garrido-Cumbrera4

1MD, Ph.D , PSICOST/RIRAG Research Association, Jerez, Spain
2Ph.D Operational Research Unit, ETEA, Universidad de Cordoba, Cordoba, Spain
3MD, Ph.D Dept. Biostatistics, Universidad de Cadiz, Cadiz, Spain
4Ph.D, Department of Mental Health and Substance Abuse, WHO, Geneva, Switzerland

* Correspondence to: Luis Salvador-Carulla, MD, PhD, President, PSICOST Research Association, Plaza San Marcos 6, Jerez11403, Spain
Tel.: +34-956-311 587
Fax: +34-956-331 759
E-mail: luis.salvador@telefonica.net

Source of Funding: This research was partly funded by the Catalan Department of Health, the Andalusian Research Plan (PAI P06-CTS-01765), and the Spanish Health Research Fund (Instituto Carlos III - RIRAG research network -G03/061).

Abstract

To develop an operational model of basic mental health community care (B-MHCC) and to use it to assess the technical efficiency of small health areas (SHA). A hybrid method was followed to develop a B-MHCC model which was used for providing ratings of 12 SHA and to design a Data Envelopment Analysis (DEA) model to assess technical efficiency. One area was classified as efficient (benchmark) and seven as inefficient. The DEA model rated 6 areas as inefficient, five of these coincided with the experts´ opinion (ICC: 0.87). The improvements required to reach efficiency were also estimated. The B-MHCC is appropriate to test technical efficiency in Spain. The DEA model, combined with the qualitative rating, proved more useful to detect inefficiency than efficiency. It also provided the size of improvements needed to reach efficiency.

 

Background: Little is known on the efficiency of mental health care in small health areas (SHA) particularly where care is organised in sectors and information is incomplete.

Aims of the Study: To develop an operational model of basic mental health community care (B-MHCC). and to use it to assess the technical efficiency of small health areas.

Method: A hybrid qualitative and quantitative method was followed to develop a B-MHCC model based on 12 indicators of residential and day care availability and utilisation. It was used for providing qualitative ratings of 12 SHA and to design an standard weighted input-oriented variable returns to scale-Data Envelopment Analysis (DEA) to assess the technical efficiency in each area with a maximum discrimination. The agreement between both strategies was tested via Intraclass Correlation Coefficient (ICC) and predictive validity.

Results: One SHA was classified as efficient (benchmark) and seven as inefficient by experts. A DEA model based on two input and 4 output variables rated 6 areas as inefficient, five of these coincided with the experts' opinion (ICC: 0.87). The improvements which every inefficient area required to reach efficiency were also estimated.

Discussion: The expert-driven model of community care (B-MHCC) is appropriate to test technical efficiency in Spain. The DEA model, combined with the qualitative rating, proved more useful to detect inefficiency than efficiency. It also provided the size of improvements needed to reach efficiency.

Implications for Health Care Provision and Use: This model may help decision makers to adjust resource allocation as well as to monitor the efficiency changes over time within small health areas. However, further statistical correlation analysis must be carried out to determine parameter relationships and new mathematical parameter transformations must also be carried out to improve DEA results, as we cannot state that the model will provide similar results when applied to other SHA.

Implications for Health Policies: The DEA model can be applied to care decision, planning and benchmarking. This approach could be relevant for health planning in countries where mental healthcare is organised in sectors, particularly when the available information on service availability and use is not comprehensive.


Received 6 October 2006; accepted 28 May 2007

Copyright 2007 ICMPE