ORCID Profile
0000-0002-6477-5142
Current Organisation
Universidad Loyola Andalucía
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Publisher: MDPI AG
Date: 25-01-2019
Abstract: 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.
Publisher: American Chemical Society (ACS)
Date: 17-07-2019
Publisher: Public Library of Science (PLoS)
Date: 11-01-2022
DOI: 10.1371/JOURNAL.PONE.0261621
Abstract: Major efforts worldwide have been made to provide balanced Mental Health (MH) care. Any integrated MH ecosystem includes hospital and community-based care, highlighting the role of outpatient care in reducing relapses and readmissions. This study aimed (i) to identify potential expert-based causal relationships between inpatient and outpatient care variables, (ii) to assess them by using statistical procedures, and finally (iii) to assess the potential impact of a specific policy enhancing the MH care balance on real ecosystem performance. Causal relationships (Bayesian network) between inpatient and outpatient care variables were defined by expert knowledge and confirmed by using multivariate linear regression (generalized least squares). Based on the Bayesian network and regression results, a decision support system that combines data envelopment analysis, Monte Carlo simulation and fuzzy inference was used to assess the potential impact of the designed policy. As expected, there were strong statistical relationships between outpatient and inpatient care variables, which preliminarily confirmed their potential and a priori causal nature. The global impact of the proposed policy on the ecosystem was positive in terms of efficiency assessment, stability and entropy. To the best of our knowledge, this is the first study that formalized expert-based causal relationships between inpatient and outpatient care variables. These relationships, structured by a Bayesian network, can be used for designing evidence-informed policies trying to balance MH care provision. By integrating causal models and statistical analysis, decision support systems are useful tools to support evidence-informed planning and decision making, as they allow us to predict the potential impact of specific policies on the ecosystem prior to its real application, reducing the risk and considering the population’s needs and scientific findings.
Publisher: SAGE Publications
Date: 28-07-2020
Abstract: Mental health (MH) care in remote areas is frequently scarce and fragmented and difficult to compare objectively with other areas even in the same country. This study aimed to analyze the adult MH service provision in 3 remote areas of Organization for Economic Cooperation and Development countries in the world. We used an internationally agreed set of systems indicators, terminology, and classification of services (Description and Evaluation of Services and DirectoriEs for Long Term Care). This instrument provided a standard description of MH care provision in the Kimberley region (Australia), Nunavik (Canada), and Lapland (Finland), areas characterized by an extremely low population density and high relative rates of Indigenous peoples. All areas showed high rates of deprivation within their national contexts. MH services were mostly provided by the public sector supplemented by nonprofit organizations. This study found a higher provision per inhabitant of community residential care in Nunavik in relation to the other areas higher provision of community outreach services in the Kimberley and a lack of day services except in Lapland. Specific cultural-based services for the Indigenous population were identified only in the Kimberley. MH care in Lapland was self-sufficient, and its care pattern was similar to other Finnish areas, while the Kimberley and Nunavik differed from the standard pattern of care in their respective countries and relied partly on services located outside their boundaries for treating severe cases. We found common challenges in these remote areas but a huge ersity in the patterns of MH care. The implementation of care interventions should be locally tailored considering both the environmental characteristics and the existing pattern of service provision.
Publisher: Public Library of Science (PLoS)
Date: 17-03-2022
DOI: 10.1371/JOURNAL.PONE.0265319
Abstract: 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 s le 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 ( ided 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.
Publisher: Public Library of Science (PLoS)
Date: 22-03-2022
DOI: 10.1371/JOURNAL.PONE.0265669
Abstract: 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.
Publisher: Cambridge University Press (CUP)
Date: 09-2019
DOI: 10.1016/J.EURPSY.2019.07.003
Abstract: 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. We conducted a systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (1997-2018). 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. 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.
Publisher: Springer Science and Business Media LLC
Date: 14-12-1970
DOI: 10.1007/S10488-019-00921-6
Abstract: 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.
Publisher: MDPI AG
Date: 31-05-2018
Publisher: SCITEPRESS - Science and Technology Publications
Date: 2017
Publisher: Springer Science and Business Media LLC
Date: 15-01-2021
DOI: 10.1186/S12888-020-03015-Y
Abstract: Mental health care systems have been dramatically affected by COVID-19. Containment measures have been imposed, with negative consequences on population mental health. Therefore, an increase in both symptomatology and mental disorder incidence is expected. This research aims to identify, describe and assess the empirical background on online strategies and recommendations developed by international organizations and governments to cope with the psychological impact of COVID-19 at a very early stage of the pandemic. The PRISMA guidelines were adapted to review online documents. A new questionnaire was developed to identify the existence of common patterns in the selected documents. Questions were classified into three domains: COVID-19 information, mental health strategies and mental health recommendations. A two-step cluster analysis was carried out to highlight underlying behaviours in the data (patterns). The results are shown as spider graphs (pattern profiles) and conceptual maps (multidimensional links between questions). Twenty-six documents were included in the review. The questionnaire analysed document complexity and identified their common key mental health characteristics (i.e., does the respondent have the tools for dealing with stress, depression and anxiety?). Cluster analysis highlighted patterns from the questionnaire domains. Strong relationships between questions were identified, such as psychological tips for maintaining good mental health and coping with COVID-19 (question n° 4), describing some psychological skills to help people cope with anxiety and worry about COVID-19 (question n° 6) and promoting social connection at home (question n° 8). When fast results are needed to develop health strategies and policies, rapid reviews associated with statistical and graphical methods are essential. The results obtained from the proposed analytical procedure can be relevant to a) classify documents according to their complexity in structuring the information provided on how to cope with the psychological impact of COVID-19, b) develop new documents according to specific objectives matching population needs, c) improve document design to face unforeseen events, and d) adapt new documents to local situations. In this framework, the relevance of adapting e-mental health procedures to community mental health care model principles was highlighted, although some problems related to the digital gap must be considered.
Publisher: Public Library of Science (PLoS)
Date: 14-02-2019
Publisher: Royal Society of Chemistry (RSC)
Date: 2015
DOI: 10.1039/C5CC03941J
Abstract: The structure of the C60 and p-Bu(t)-calix[8]arene complex has been reinvestigated, showing an unprecedented continuous layered tetragonal array of fullerenes encapsulated by calixarenes. Electron diffraction data revealed the tetragonal symmetry, with a stepped structure observed by AFM and SEM, and the thickness of the basal plane was measured by XRD, as 2 nm. The molecular simulated arrangement of fullerenes accounts for the ability to take up to ca. 11% of fullerenes C70 in place of the smaller fullerene.
No related grants have been discovered for Nerea Almeda.