Development and spatial representation of synthetic indexes of outpatient mental health care in Andalusia (Spain)

Assessment of care provision integration in a community-based mental health system: balanced care model implementation in Andalusia (Spain)

BACKGROUND

Andalusia is the second largest region in Spain, and it has developed a comprehensive mental health (MH) plan that encourages the consolidation of the balanced care model. However, its geographical and socioeconomic disparity is a great challenge for a community-based MH system. Both the assessment of the implementation of the MH plan and the development of new tools to support decision-making can be considered critical.

OBJECTIVES

The present study aims (i) to assess how the integration of different types of MH care may influence system performance and (ii) to check the performance evolution of the integration process geographically regarding the small MH areas of Andalusia.

METHODS

The performance of the Andalusian MH system was assessed by combining Monte Carlo simulation, fuzzy inference and data envelopment analysis. The relative technical efficiency was the main performance indicator.

RESULTS

A correct integration of appropriate types of MH care, according to population needs, increases the performance of the Andalusian MH system both from global and regional perspectives. The spatial representation (based on small MH areas) of the results highlights how the performance depends on specific geographical characteristics. By analyzing the identified spatial clusters, defined by different management patterns depending on user and socioeconomic characteristics, benchmark areas and areas for improvement can be studied to design evidence-informed policies and interventions.

CONCLUSIONS

A global analysis of MH system performance was carried out, including both the successive integration of different types of care and its spatial evolution. Although an appropriate integration of different types of MH care has a positive effect on the Andalusian MH system, this process has different profiles depending on specific geographically based user and socioeconomic characteristics. The balanced care model can be considered the paradigm for assessing the performance of a large and populated territory such as Andalusia, which has a community-based MH system. This methodological approach (performance assessment and spatial analysis) may be used as a guide for developing future evidence-informed policies and managerial interventions.

The critical factor: The role of quality in the performance of supported accommodation services for complex mental illness in England

Rehabilitation services have a key role in ensuring integrated and comprehensive mental health (MH) care in the community for people suffering from long-term and severe mental disorders. MH-supported accommodation services aim to promote service users’ autonomy and independence. Given the complexity associated with MH-supported accommodation services in England, a comparative evaluation of critical performance indicators, including service provision and quality of care, seems to be necessary in designing evidence-informed policies. This study aims to explore the influence of service quality indicators on the performance of MH-supported accommodation services in England. The analysed sample includes supported accommodation services from 14 nationally representative local authorities in England from the QuEST study grouped by three main types of care: residential care homes (divided into two subgroups: move-on and non-move-on oriented), supported housing and floating outreach. EDeS-MH (efficient decision support-mental health) was used to assess the performance indicators for the selected services by combining a Monte Carlo simulation engine, data envelopment analysis and a fuzzy inference engine for integrating expert knowledge. Depending on the type of care, six/seven quality domains were sequentially included after a baseline scenario (only technical) was analysed. Relative technical efficiency scores for the baseline scenarios revealed high performance in all the selected supported accommodation services, but the statistical variability was high. Quality domains significantly improved performance in every type of care. The inclusion of quality indicators has a positive impact on the global performance of each type of care. Remaining at the corresponding services more than expected for two years has a negative impact on performance. These findings can be considered from a planning perspective to facilitate the design of pathways of care with more realistic expectations about gaining autonomy in two years.

Development of the Australian neighborhood social fragmentation index and its association with spatial variation in depression across communities

PURPOSE

We know little about how community structures influence the risk of common mental illnesses. This study presents a new way to establish links between depression and social fragmentation, thereby identifying pathways to better target mental health services and prevention programs to the right people in the right place.

METHOD

A principal components analysis (PCA) was conducted to develop the proposed Australian neighborhood social fragmentation index (ANSFI). General practice clinical data were used to identify cases of diagnosed depression. The association between ANSFI and depression was explored using multilevel logistic regression. Spatial hot spots (clusters) of depression prevalence and social fragmentation at the statistical area level 1 (SA1) were examined.

RESULTS

Two components of social fragmentation emerged, reflecting fragmentation related to family structure and mobility. Individuals treated for depression in primary care were more likely to live in neighborhoods with lower socioeconomic status and with higher social fragmentation related to family structure. A 1-SD increase in social fragmentation was associated with a 16% higher depression prevalence (95% CI 11%, 20%). However, the association attenuated with adjustment for neighborhood socio-economic status. Considerable spatial variation in social fragmentation and depression patterns across communities was observed.

CONCLUSIONS

Developing a social fragmentation index for the first time in Australia at a small area level generates a new line of knowledge on the impact of community structures on health risks. Findings may extend our understanding of the mechanisms that drive geographical variation in the incidence of common mental disorders and mental health care.

A preliminary taxonomy and a standard knowledge base for mental-health system indicators in Spain

Background

There are many sources of information for mental health indicators but we lack a comprehensive classification and hierarchy to improve their use in mental health planning. This study aims at developing a preliminary taxonomy and its related knowledge base of mental health indicators usable in Spain.

Methods

A qualitative method with two experts panels was used to develop a framing document, a preliminary taxonomy with a conceptual map of health indicators, and a knowledge base consisting of key documents, glossary and database of indicators with an evaluation of their relevance for Spain.

Results

A total of 661 indicators were identified and organised hierarchically in 4 domains (Context, Resources, Use and Results), 12 subdomains and 56 types. Among these the expert panels identified 200 indicators of relevance for the Spanish system.

Conclusions

The classification and hierarchical ordering of the mental health indicators, the evaluation according to their level of relevance and their incorporation into a knowledge base are crucial for the development of a basic list of indicators for use in mental health planning.