From Community to Meta-Community Mental Health Care

Bouras, Nick; Ikkos, George; Craig, Thomas J.

doi:10.3390/ijerph15040806

Cited by 19 publications

(17 citation statements)

References 44 publications

(48 reference statements)

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“…Many high-income countries have established community-based mental health care programs and services, including CMHCs, as outstanding examples of this endeavor. However, for many others, including most low-income and middle-income countries, it remains an aspiration ( 28 ). The current paper outlined a history of the development of the CMHCs in Iran and how it has played out in the Seraj program, which is a comprehensive psychosocial program to address the psychosocial needs of the population.…”

Section: Discussionmentioning

confidence: 99%

Specialized Outpatient: Community Mental Health Centers (CMHCs)

Sharifi¹,

Hajebi²,

Damari³

et al. 2021

IJPS

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Objective: The Iranian Mental Health Survey (IranMHS) in 2011 has demonstrated that almost 1 out of 4 adult individuals suffer from psychiatric disorders; however, more than two-thirds are left unrecognized and untreated and many of the services have poor quality of care. In this paper we present our experience in developing and employing community-based mental health services through community mental health centers (CMHCs), which has been incorporated in Iran's comprehensive mental and social health services (the Seraj program). Method: The service model of the CMHCs was developed though an evidence-based service planning approach and was then incorporated as the specialized outpatient services model into the Seraj program in 2015. Results: The CMHCs in the Seraj program provide mental health care to patients with common mental and severe mental disorders in a defined catchment area. The services include the collaborative care, the aftercare, and day rehabilitation. The collaborative care model works with primary care providers in the health centers to provide detection and treatment of common mental illnesses. In the aftercare, services are offered to patients with severe mental disorders following discharge from the hospital and include telephone follow-ups and home visits. Day rehabilitation is mostly focused on providing psychoeducation and skill trainings. During the first 4 years of implementation in 2 pilot areas, more than 6200 patients (10% having severe mental disorders) received care at CMHCs. Conclusion: The main challenge of the implementation of the CMHC component in the Seraj program is to secure funds and employ skilled personnel. We need to incorporate Seraj in the existing national health system, and if successful, it can fill the treatment gap that has been so huge in the country.

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Section: Discussionmentioning

confidence: 99%

Specialized Outpatient: Community Mental Health Centers (CMHCs)

Sharifi¹,

Hajebi²,

Damari³

et al. 2021

IJPS

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“…Additionally, a challenge is the continuity of rehabilitation in the community immediately after discharge from the hospital. For this to happen, appropriate outpatient structures are needed, which is not always possible, as many countries have been in a hurry to over-de-institutionalize, which has led to a deterioration in the prognosis and quality of life for a subgroup of chronic patients whose quality of life have decreased whilst morbidity has increased due to lack of appropriate community mental health services [44]. In this case, there is an unmet need for coordination and close co-operation between the general practitioners and community mental health services in order to improve appropriateness of referals [45].…”

Section: Discussionmentioning

confidence: 99%

“…High accessibility is related to less stigma and vice versa in the context of equity in healthcare, human rights, community involvement, continuity of care until patients' recovery [48]. However, beyond stigma, accessibility also depends on the adequacy and availability of appropriate hospital and community mental health structures [44,49,50], as well as the absence of waiting lists for evaluations, hospitalizations, and outpatient therapies, as can be described.…”

Section: Discussionmentioning

confidence: 99%

Assessing and Improving the Quality in Mental Health Services

Samartzis

Talias

2019

IJERPH

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Background: The mental health of the population consists of the three essential pillars of quality of life, economy, and society. Mental health services take care of the prevention and treatment of mental disorders and through them maintain, improve, and restore the mental health of the population. The purpose of this study is to describe the methodology for qualitative and quantitative evaluation and improvement of the mental health service system. Methods: This is a narrative review study that searches the literature to provide criteria, indicators, and methodology for evaluating and improving the quality of mental health services and the related qualitative and quantitative indicators. The bibliography was searched in popular databases PubMed, Google Scholar, CINAHL, using the keywords "mental", "health", "quality", "indicators", alone or in combinations thereof. Results: Important quality indicators of mental health services have been collected and presented, and modified where appropriate. The definition of each indicator is presented here, alongside its method of calculation and importance. Each indicator belongs to one of the eight dimensions of quality assessment: (1) Suitability of services, (2) Accessibility of patients to services, (3) Acceptance of services by patients, (4) Ability of healthcare professionals to provide services, (5) Efficiency of health professionals and providers, (6) Continuity of service over time (ensuring therapeutic continuity), (7) Efficiency of health professionals and services, (8) Safety (for patients and for health professionals). Discussion/Conclusions: Accessibility and acceptability of service indicators are important for the attractiveness of services related to their use by the population. Profitability indicators are important economic indicators that affect the viability and sustainability of services, factors that are now taken into account in any health policy. All of the indicators mentioned are related to public health, affecting the quality of life, morbidity, mortality, and life expectancy, directly or indirectly. The systematic measurement and monitoring of indicators and the measurement and quantification of quality through them, are the basis for evidence-based health policy for improvement of the quality of mental health services.

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“…Community mental health care is understood as the promotion of mental health for a target population, considering its needs and strengths, favouring social support, and highlighting evidence-based and recovery-oriented services [3]. Nevertheless, the provision of integrated care into the community is still a major challenge [4] due to the added complexity of mental health systems [5,6].…”

Section: Introductionmentioning

confidence: 99%

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

Almeda

García‐Alonso

Salinas-Pérez

et al. 2019

IJERPH

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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.

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From Community to Meta-Community Mental Health Care

Cited by 19 publications

References 44 publications

Specialized Outpatient: Community Mental Health Centers (CMHCs)

Specialized Outpatient: Community Mental Health Centers (CMHCs)

Assessing and Improving the Quality in Mental Health Services

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

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