ArticlePloS one2019
A decision support system for assessing management interventions in a mental health ecosystem: The case of Bizkaia (Basque Country, Spain).
Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Combined Applications of Artificial Intelligence and Simulation for Healthcare Process Optimization: A Systematic Review.Healthcare (Basel, Switzerland) · 2025Review
- Key Performance Indicators Applied in Medicine.International archives of otorhinolaryngology · 2025Article
- Modelling the impact on a local mental health system of previously implemented care programs: the experience of assertive outreach teams in Bizkaia (Spain).Epidemiology and psychiatric sciences · 2025Article
- Assessment of care provision integration in a community-based mental health system: balanced care model implementation in Andalusia (Spain).BMC public health · 2024Article
- Prevalence of depression and anxiety in Colombia: What happened during Covid-19 pandemic?PloS one · 2024Article
- Impact of the workforce allocation on the technical performance of mental health services: the collective case of Helsinki-Uusimaa (Finland).Health research policy and systems · 2023Article
- Patterns of mental healthcare provision in rural areas: A demonstration study in Australia and Europe.Frontiers in psychiatry · 2023Article
- Magnitude of terminological bias in international health services research: a disambiguation analysis in mental health.Epidemiology and psychiatric sciences · 2022Review
- Fit for Purpose-Re-Designing Australia's Mental Health Information System.International journal of environmental research and public health · 2022Review
- Modelling the balance of care: Impact of an evidence-informed policy on a mental health ecosystem.PloS one · 2022Article
- Article
- The critical factor: The role of quality in the performance of supported accommodation services for complex mental illness in England.PloS one · 2022Article
- Using Geospatial Analysis to Inform Development of a Place-Based Integrated Care Initiative: The Healthy Homes and Neighbourhoods Experience.International journal of integrated care · 2021Article
- A Semiautomated Classification System for Producing Service Directories in Social and Health Care (DESDE-AND): Maturity Assessment Study.Journal of medical Internet research · 2021Article
- Article
- A Comprehensive Assessment to Enable Recovery of the Homeless: The HOP-TR Study.Frontiers in public health · 2021Article
- Rapid response to crisis: Health system lessons from the active period of COVID-19.Health policy and technology · 2020Article
- Patterns of Service Provision in Older People's Mental Health Care in Australia.International journal of environmental research and public health · 2020Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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