Use of a decision support system for benchmarking analysis and organizational improvement of regional mental health care: Efficiency, stability and entropy assessment of the mental health ecosystem of Gipuzkoa (Basque Country, Spain).

Decision support systems are appropriate tools for guiding policymaking processes, especially in mental health (MH), where care provision should be delivered in a balanced and integrated way. This study aims to develop an analytical process for (i) assessing the performance of an MH ecosystem and (ii) identifying benchmark and target-for-improvement catchment areas. MH provision (inpatient, day and outpatient types of care) was analysed in the Mental Health Network of Gipuzkoa (Osakidetza, Basque Country, Spain) using a decision support system that integrated data envelopment analysis, Monte Carlo simulation and artificial intelligence. The unit of analysis was the 13 catchment areas defined by a reference MH centre. MH ecosystem performance was assessed by the following indicators: relative technical efficiency, stability and entropy to guide organizational interventions. Globally, the MH system of Gipuzkoa showed high efficiency scores in each main type of care (inpatient, day and outpatient), but it can be considered unstable (small changes can have relevant impacts on MH provision and performance). Both benchmark and target-for-improvement areas were identified and described. This article provides a guide for evidence-informed decision-making and policy design to improve the continuity of MH care after inpatient discharges. The findings show that it is crucial to design interventions and strategies (i) considering the characteristics of the area to be improved and (ii) assessing the potential impact on the performance of the global MH care ecosystem. For performance improvement, it is recommended to reduce admissions and readmissions for inpatient care, increase workforce capacity and utilization of day care services and increase the availability of outpatient care services.

A Semiautomated Classification System for Producing Service Directories in Social and Health Care (DESDE-AND): Maturity Assessment Study.

BACKGROUND: DESDE-LTC (Description and Evaluation of Services and DirectoriEs for Long-Term Care) is an international classification system that allows standardized coding and comparisons between different territories and care sectors, such as health and social care, in defined geographic areas. We adapted DESDE-LTC into a computer tool (DESDE-AND) for compiling a directory of care services in Andalucia, Spain. OBJECTIVE: The aim of this study was to evaluate the maturity of DESDE-AND. A secondary objective of this study is to show the practicality of a new combined set of standard evaluation tools for measuring the maturity of health technology products. METHODS: A system for semiautomated coding of service provision has been co-designed. A panel of 23 domain experts and a group of 68 end users participated in its maturity assessment that included its technology readiness level (TRL), usability, validity, adoption (Adoption Impact Ladder [AIL]), and overall degree of maturity [implementation maturity model [IMM]). We piloted the prototype in an urban environment (Seville, Spain). RESULTS: The prototype was demonstrated in an operational environment (TRL 7). Sixty-eight different care services were coded, generating fact sheets for each service and its geolocation map. The observed agreement was 90%, with moderate reliability. The tool was partially adopted by the regional government of Andalucia (Spain), reaching a level 5 in adoption (AIL) and a level 4 in maturity (IMM) and is ready for full implementation. CONCLUSIONS: DESDE-AND is a usable and manageable system for coding and compiling service directories and it can be used as a core module of decision support systems to guide planning in complex cross-sectoral areas such as combined social and health care.

[Everything is on the map: Integrated Mental Health Atlases as support tools for service planning. SESPAS Report 2020]. / Todo está en el mapa: Atlas Integrales de Salud Mental para la planificación de servicios. Informe SESPAS 2020.

OBJECTIVE: This article reviews the usability of the Integrated Atlases of Mental Health as a decision support tool for service planning following a health ecosystem research approach. METHOD: This study describes the types of atlases and the procedure for their development. Atlases carried out in Spain are presented and their impact in mental health service planning is assessed. Atlases comprise information on the local characteristics of the health care system, geographical availability of resources collected with the DESDE-LTC instrument and their use. Atlases use geographic information systems and other visualisation tools. Atlases follow a bottom-up collaborative approach involving decision-makers from planning agencies for their development and external validation. RESULTS: Since 2005, Integrated Atlases of Mental Health have been developed for nine regions in Spain comprising over 65% of the Spanish inhabitants. The impact on service planning has been unequal for the different regions. Catalonia, Biscay and Gipuzkoa, and Andalusia reach the highest impact. In these areas, health advisors have been actively involved in their co-design and implementation in service planning. CONCLUSIONS: Atlases allow detecting care gaps and duplications in care provision; monitoring changes of the system over time, and carrying out national and international comparisons, efficiency modelling and benchmarking. The knowledge provided by atlases could be incorporated to decision support systems in order to support an efficient mental health service planning based on evidence-informed policy.

[Impact assessment of a multisectoral plan for the promotion of health and social wellbeing in Andalusia (Spain)]. / Evaluación del impacto de un plan multisectorial de promoción de la salud y el bienestar social en Andalucía.

OBJECTIVE: To evaluate the impact of the Plan for the promotion of personal autonomy and prevention of disability in Andalusia (2016-2020) in 13 public administrations during the first year of its implementation; and to analyse the usability and feasibility of the impact assessment ladder used. METHOD: The Plan addresses the promotion of personal autonomy and the prevention of disabilities and dependencies through a multisectoral approach. It is structured in strands or lines of work, objectives and actions that have been assessed through the Adoption Impact Ladder (AIL). The analysis of the face validity, feasibility and inter-rater reliability of the impact assessment ladder was carried out in 30 actions of the Plan that were rated by 20 experts from the 13 ministries and public agencies involved in the Plan, and an external rater. RESULTS: 176 actions and programmes were launched in 2017. Of these, 67.2% were implemented during the first year. Only one of the 16 objectives had no action initiated during the first year. Moreover, 7 out of 15 objectives implemented were fully multisectoral involving more than three Regional Ministries. The face validity, feasibility and inter-rater reliability of the AIL were good (κ: 0.72). CONCLUSIONS: This Plan has provided a novel framework to coordinate a broad range of proposed policies and actions within the public administration of Andalusia. For the first time, a multisectoral impact analysis has been conducted providing an effective guide for monitoring, planning and setting public priorities in health, social services, ageing and disabilities.

Standardised description of health and social care: A systematic review of use of the ESMS/DESDE (European Service Mapping Schedule/Description and Evaluation of Services and DirectoriEs).

BACKGROUND: Evidence-informed planning and interpretation of research results both require standardised description of local care delivery context. Such context analysis descriptions should be comparable across regions and countries to allow benchmarking and organizational learning, and for research findings to be interpreted in context. The European Service Mapping Schedule (ESMS) is a classification of adult mental health services that was later adapted for the assessment of health and social systems research (Description and Evaluation of Services and DirectoriEs - DESDE). The aim of the study was to review the diffusion and use of the ESMS/DESDE system in health and social care and its impact in health policy and decision-making. METHOD: We conducted a systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (1997-2018). RESULTS: Out of 155 papers mentioning ESMS/DESDE, 71 have used it for service research and planning. The classification has been translated into eight languages and has been used by seven international research networks. Since 2000, it has originated 11 instruments for health system research with extensive analysis of their metric properties. The ESMS/DESDE coding system has been used in 585 catchment areas in 34 countries for description of services delivery at local, regional and national levels. CONCLUSIONS: The ESMS/DESDE system provides a common terminology, a classification of care services, and a set of tools allowing a variety of aims to be addressed in healthcare and health systems research. It facilitates comparisons across and within countries for evidence-informed planning.

A decision support system for assessing management interventions in a mental health ecosystem: The case of Bizkaia (Basque Country, Spain).

Evidence-informed strategic planning is a top priority in Mental Health (MH) due to the burden associated with this group of disorders and its societal costs. However, MH systems are highly complex, and decision support tools should follow a systems thinking approach that incorporates expert knowledge. The aim of this paper is to introduce a new Decision Support System (DSS) to improve knowledge on the health ecosystem, resource allocation and management in regional MH planning. The Efficient Decision Support-Mental Health (EDeS-MH) is a DSS that integrates an operational model to assess the Relative Technical Efficiency (RTE) of small health areas, a Monte-Carlo simulation engine (that carries out the Monte-Carlo simulation technique), a fuzzy inference engine prototype and basic statistics as well as system stability and entropy indicators. The stability indicator assesses the sensitivity of the model results due to data variations (derived from structural changes). The entropy indicator assesses the inner uncertainty of the results. RTE is multidimensional, that is, it was evaluated by using 15 variable combinations called scenarios. Each scenario, designed by experts in MH planning, has its own meaning based on different types of care. Three management interventions on the MH system in Bizkaia were analysed using key performance indicators of the service availability, placement capacity in day care, health care workforce capacity, and resource utilisation data of hospital and community care. The potential impact of these interventions has been assessed at both local and system levels. The system reacts positively to the proposals by a slight increase in its efficiency and stability (and its corresponding decrease in the entropy). However, depending on the analysed scenario, RTE, stability and entropy statistics can have a positive, neutral or negative behaviour. Using this information, decision makers can design new specific interventions/policies. EDeS-MH has been tested and face-validated in a real management situation in the Bizkaia MH system.

Causal Modelling for Supporting Planning and Management of Mental Health Services and Systems: A Systematic Review.

Mental health services and systems (MHSS) are characterized by their complexity. Causal modelling is a tool for decision-making based on identifying critical variables and their causal relationships. In the last two decades, great efforts have been made to provide integrated and balanced mental health care, but there is no a clear systematization of causal links among MHSS variables. This study aims to review the empirical background of causal modelling applications (Bayesian networks and structural equation modelling) for MHSS management. The study followed the PRISMA guidelines (PROSPERO: CRD42018102518). The quality of the studies was assessed by using a new checklist based on MHSS structure, target population, resources, outcomes, and methodology. Seven out of 1847 studies fulfilled the inclusion criteria. After the review, the selected papers showed very different objectives and subjects of study. This finding seems to indicate that causal modelling has potential to be relevant for decision-making. The main findings provided information about the complexity of the analyzed systems, distinguishing whether they analyzed a single MHSS or a group of MHSSs. The discriminative power of the checklist for quality assessment was evaluated, with positive results. This review identified relevant strategies for policy-making. Causal modelling can be used for better understanding the MHSS behavior, identifying service performance factors, and improving evidence-informed policy-making.

Relative Technical Efficiency Assessment of Mental Health Services: A Systematic Review.

The current prevalence of mental disorders demands improved ways of the management and planning of mental health (MH) services. Relative technical efficiency (RTE) is an appropriate and robust indicator to support decision-making in health care, but it has not been applied significantly in MH. This article systematically reviews the empirical background of RTE in MH services following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Finally, 13 studies were included, and the findings provide new standard classifications of RTE variables, efficiency determinants and strategies to improve MH management and planning.

A Comparison of Mental Health Care Systems in Northern and Southern Europe: A Service Mapping Study.

Mental health services (MHS) have gone through vast changes during the last decades, shifting from hospital to community-based care. Developing the optimal balance and use of resources requires standard comparisons of mental health care systems across countries. This study aimed to compare the structure, personnel resource allocation, and the productivity of the MHS in two benchmark health districts in a Nordic welfare state and a southern European, family-centered country. The study is part of the REFINEMENT (Research on Financing Systems' Effect on the Quality of Mental Health Care) project. The study areas were the Helsinki and Uusimaa region in Finland and the Girona region in Spain. The MHS were mapped by using the DESDE-LTC (Description and Evaluation of Services and Directories for Long Term Care) tool. There were 6.7 times more personnel resources in the MHS in Helsinki and Uusimaa than in Girona. The resource allocation was more residential-service-oriented in Helsinki and Uusimaa. The difference in mental health personnel resources is not explained by the respective differences in the need for MHS among the population. It is important to make a standard comparison of the MHS for supporting policymaking and to ensure equal access to care across European countries.

The REFINEMENT Glossary of Terms: An International Terminology for Mental Health Systems Assessment.

Comparing mental health systems across countries is difficult because of the lack of an agreed upon terminology covering services and related financing issues. Within the European Union project REFINEMENT, international mental health care experts applied an innovative mixed "top-down" and "bottom-up" approach following a multistep design thinking strategy to compile a glossary on mental health systems, using local services as pilots. The final REFINEMENT glossary consisted of 432 terms related to service provision, service utilisation, quality of care and financing. The aim of this study was to describe the iterative process and methodology of developing this glossary.

Evaluation of an integrated system for classification, assessment and comparison of services for long-term care in Europe: the eDESDE-LTC study.

BACKGROUND: The harmonization of European health systems brings with it a need for tools to allow the standardized collection of information about medical care. A common coding system and standards for the description of services are needed to allow local data to be incorporated into evidence-informed policy, and to permit equity and mobility to be assessed. The aim of this project has been to design such a classification and a related tool for the coding of services for Long Term Care (DESDE-LTC), based on the European Service Mapping Schedule (ESMS). METHODS: The development of DESDE-LTC followed an iterative process using nominal groups in 6 European countries. 54 researchers and stakeholders in health and social services contributed to this process. In order to classify services, we use the minimal organization unit or "Basic Stable Input of Care" (BSIC), coded by its principal function or "Main Type of Care" (MTC). The evaluation of the tool included an analysis of feasibility, consistency, ontology, inter-rater reliability, Boolean Factor Analysis, and a preliminary impact analysis (screening, scoping and appraisal). RESULTS: DESDE-LTC includes an alpha-numerical coding system, a glossary and an assessment instrument for mapping and counting LTC. It shows high feasibility, consistency, inter-rater reliability and face, content and construct validity. DESDE-LTC is ontologically consistent. It is regarded by experts as useful and relevant for evidence-informed decision making. CONCLUSION: DESDE-LTC contributes to establishing a common terminology, taxonomy and coding of LTC services in a European context, and a standard procedure for data collection and international comparison.