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An ecosystems approach to mental health services research.

ABSTRACT: Mental health ecosystems research is an emerging discipline which takes a whole-systems approach to mental healthcare, facilitating analysis of the complex environment and context of mental health systems, and translation of this knowledge into policy and practice. Evidence from the local context is needed in the analysis of complex interventions and of geographic variations in the outcomes of care. Technical tools and support have been developed to gather and interpret evidence from the local context and translate it in a meaningful and relevant manner for planners and policy makers to guide their decision-making.

SUBMITTER: Furst MA

PROVIDER: S-EPMC8274404 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:AimsHealth services research (HSR) is affected by a widespread problem related to service terminology including non-commensurability (using different units of analysis for comparisons) and terminological unclarity due to ambiguity and vagueness of terms. The aim of this study was to identify the magnitude of the terminological bias in health and social services research and health economics by applying an international classification system.MethodsThis study, that was part of the PECUNIA project, followed an ontoterminology approach (disambiguation of technical and scientific terms using a taxonomy and a glossary of terms). A listing of 56 types of health and social services relevant for mental health was compiled from a systematic review of the literature and feedback provided by 29 experts in six European countries. The disambiguation of terms was performed using an ontology-based classification of services (Description and Evaluation of Services and DirectoriEs - DESDE), and its glossary of terms. The analysis focused on the commensurability and the clarity of definitions according to the reference classification system. Interrater reliability was analysed using κ.ResultsThe disambiguation revealed that only 13 terms (23%) of the 56 services selected were accurate. Six terms (11%) were confusing as they did not correspond to services as defined in the reference classification system (non-commensurability bias), 27 (48%) did not include a clear definition of the target population for which the service was intended, and the definition of types of services was unclear in 59% of the terms: 15 were ambiguous and 11 vague. The κ analyses were significant for agreements in unit of analysis and assignment of DESDE codes and very high in definition of target population.ConclusionsService terminology is a source of systematic bias in health service research, and certainly in mental healthcare. The magnitude of the problem is substantial. This finding has major implications for the international comparability of resource use in health economics, quality and equality research. The approach presented in this paper contributes to minimise differentiation between services by taking into account key features such as target population, care setting, main activities and type and number of professionals among others. This approach also contributes to support financial incentives for effective health promotion and disease prevention. A detailed analysis of services in terms of cost measurement for economic evaluations reveals the necessity and usefulness of defining services using a coding system and taxonomical criteria rather than by 'text-based descriptions'.

Project description:BackgroundMental health supported housing services are a key component in the rehabilitation of people with severe and complex needs. They are implemented widely in the UK and other deinstitutionalised countries but there have been few empirical studies of their effectiveness due to the logistic challenges and costs of standard research methods. The Clinical Record Interactive Search (CRIS) tool, developed to de-identify and interrogate routinely recorded electronic health records, may provide an alternative to evaluate supported housing services.MethodsThe feasibility of using the Camden and Islington NHS Foundation Trust CRIS database to identify a sample of users of mental health supported accommodation services. Two approaches to data interrogation and case identification were compared; using structured fields indicating individual's accommodation status, and iterative development of free text searches of clinical notes referencing supported housing. The data used were recorded over a 10-year-period (01-January-2008 to 31-December-2017).ResultsBoth approaches were carried out by one full-time researcher over four weeks (150 hours). Two structured fields indicating accommodation status were found, 2,140 individuals had a value in at least one of the fields representative of supported accommodation. The free text search of clinical notes returned 21,103 records pertaining to 1,105 individuals. A manual review of 10% of the notes indicated an estimated 733 of these individuals had used a supported housing service, a positive predictive value of 66.4%. Over two-thirds of the individuals returned in the free text search (768/1,105, 69.5%) were identified via the structured fields approach. Although the estimated positive predictive value was relatively high, a substantial proportion of the individuals appearing only in the free text search (337/1,105, 30.5%) are likely to be false positives.ConclusionsIt is feasible and requires minimal resources to use de-identified electronic health record search tools to identify large samples of users of mental health supported housing using structured and free text fields. Further work is needed to establish the availability and completion of variables relevant to specific clinical research questions in order to fully assess the utility of electronic health records in evaluating the effectiveness of these services.

Project description:IntroductionMental disorders are a leading cause of long-term disability worldwide. Much of the burden of mental ill-health is mediated by early onset, comorbidities with physical health conditions and chronicity of the illnesses. This study aims to track the early period of mental disorders among young people presenting to Australian mental health services to facilitate more streamlined transdiagnostic processes, highly personalised and measurement-based care, secondary prevention and enhanced long-term outcomes.Methods and analysisRecruitment to this large-scale, multisite, prospective, transdiagnostic, longitudinal clinical cohort study ('Youth Mental Health Tracker') will be offered to all young people between the ages of 12 and 30 years presenting to participating services with proficiency in English and no history of intellectual disability. Young people will be tracked over 3?years with standardised assessments at baseline and 3, 6, 12, 24 and 36 months. Assessments will include self-report and clinician-administered measures, covering five key domains including: (1) social and occupational function; (2) self-harm, suicidal thoughts and behaviour; (3) alcohol or other substance misuse; (4) physical health; and (5) illness type, clinical stage and trajectory. Data collection will be facilitated by the use of health information technology. The data will be used to: (1) determine prospectively the course of multidimensional functional outcomes, based on the differential impact of demographics, medication, psychological interventions and other key potentially modifiable moderator variables and (2) map pathophysiological mechanisms and clinical illness trajectories to determine transition rates of young people to more severe illness forms.Ethics and disseminationThe study has been reviewed and approved by the Human Research Ethics Committee of the Sydney Local Health District (2019/ETH00469). All data will be non-identifiable, and research findings will be disseminated through peer-reviewed journals and scientific conference presentations.

Project description:Community care is increasingly the mainstay of mental healthcare provision in many countries and patient satisfaction is an important barometer of quality of patient care. This paper explores the key factors associated with patient satisfaction with community mental health services in England and then compares providers' performance on patient satisfaction. Our analysis is based on patient-level responses from the community mental health survey, which is run annually by the Care Quality Commission (CQC) for the years 2010 to 2013. We perform a repeated cross-section analysis, identifying factors associated with patient satisfaction via a multi-level ordered probit model, including both patient- and provider-level variables. We identify hospital-specific effects via empirical Bayes estimation. Our analysis identifies a number of novel results. First, patient characteristics such as older age, being employed, and being able to work, are associated with higher satisfaction, while being female is associated with lower satisfaction. Service contact length, time since last visit, condition severity and admission to a mental health institution, are all associated with lower satisfaction. Second, treatment type affects satisfaction, with patients receiving talking therapies or being prescribed medications being more satisfied. Third, care continuity and involvement, as proxied by having a care plan, is associated with higher satisfaction. Fourth, seeing a health professional closer to the community improves satisfaction, with patients seeing a community-psychiatric nurse, a social worker or a mental-health support worker being more satisfied. Finally, our study identifies the need for service integration, with patients experiencing financial, accommodation, or physical health needs being less satisfied. At a provider level, we find a negative association between the percentage of occupied beds and satisfaction. We further identify significant provider-specific effects after accounting for observable differences in patient and provider characteristics which suggests significant differences in provider quality of care.

Project description:BackgroundThe treatment gap for mental illness in Nigeria, as in other sub-Saharan countries, is estimated to be around 85%. There is need to prioritise mental health care in low and middle income countries by providing a strong body of evidence for effective services, particularly with a view to increasing international and government confidence in investment in scaling up appropriate services. This paper lays out the processes by which a programme to integrate evidence-based mental health care into primary care services in Nigeria was designed, including a research framework to provide evidence from a robust evaluation.MethodsThis paper forms the first step in the overall process evaluation of the mhSUN intervention, where standard research practice indicates that the intervention, and its development, is clearly documented prior to subsequent evaluation. The report covers the period of programme development and evaluation design, and study site and design was chosen to allow generalisability and practical conclusions to be drawn for service development in Nigeria. In order to design an intervention that was informed by evidence and took into account local context and input of stakeholders, a structured process was followed, including: (1) Engagement of relevant stakeholders for information gathering and buy-in; (2) Literature review and gathering of pertinent evidence; (3) Situation analysis at a national and local level; (4) Model development (using Theory of Change); (5) Ongoing consultation, recognising the iterative nature of Theory of Change, and need for ongoing refinement of complex interventions.ResultsThe different sections of the structured approach resulted in outputs that built the necessary components (literature review, situation analysis) for informing the Theory of Change. A Theory of Change map is presented, which includes transparent documentation of the assumptions and logic behind the activities to drive the desired change. In addition, it documents the indicators necessary to measure fidelity and draw conclusions as to hypothesised effects of different mechanisms of action in subsequent evaluation.ConclusionIn addition to the details of ensuring robust evaluation design, there are a number of considerations that are particular to the context that must be taken into account in programme development, including the relationships between ultimate beneficiaries, implementers, host government and institutions, donors, and programme evaluators. Structured methods from existing frameworks can be drawn upon to use and collate relevant information to maximise the local applicability of a generic evidence base. Theory of Change, with its documented assumptions can form the basis of subsequent evaluation and iterative programme refinement, contributing to a more scientifically valid means of developing mental health programmes for scale up.

Project description:This paper makes a case for digital mental health and provides insights into how digital technologies can enhance (but not replace) existing mental health services. We describe digital mental health by presenting a suite of digital technologies (from digital interventions to the application of artificial intelligence). We discuss the benefits of digital mental health, for example, a digital intervention can be an accessible stepping-stone to receiving support. The paper does, however, present less-discussed benefits with new concepts such as 'poly-digital', where many different apps/features (e.g. a sleep app, mood logging app and a mindfulness app, etc.) can each address different factors of wellbeing, perhaps resulting in an aggregation of marginal gains. Another benefit is that digital mental health offers the ability to collect high-resolution real-world client data and provide client monitoring outside of therapy sessions. These data can be collected using digital phenotyping and ecological momentary assessment techniques (i.e. repeated mood or scale measures via an app). This allows digital mental health tools and real-world data to inform therapists and enrich face-to-face sessions. This can be referred to as blended care/adjunctive therapy where service users can engage in 'channel switching' between digital and non-digital (face-to-face) interventions providing a more integrated service. This digital integration can be referred to as a kind of 'digital glue' that helps join up the in-person sessions with the real world. The paper presents the challenges, for example, the majority of mental health apps are maybe of inadequate quality and there is a lack of user retention. There are also ethical challenges, for example, with the perceived 'over-promotion' of screen-time and the perceived reduction in care when replacing humans with 'computers', and the trap of 'technological solutionism' whereby technology can be naively presumed to solve all problems. Finally, we argue for the need to take an evidence-based, systems thinking and co-production approach in the form of stakeholder-centred design when developing digital mental health services based on technologies. The main contribution of this paper is the integration of ideas from many different disciplines as well as the framework for blended care using 'channel switching' to showcase how digital data and technology can enrich physical services. Another contribution is the emergence of 'poly-digital' and a discussion on the challenges of digital mental health, specifically 'digital ethics'.

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An ecosystems approach to mental health services research.

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