Assessing the uptake of incentivised physical health checks for people with serious mental illness: a cohort study in primary care.

BACKGROUND: People with serious mental illness are more likely to experience physical illnesses. The onset of many of these illnesses can be prevented if detected early. Physical health screening for people with serious mental illness is incentivised in primary care in England through the Quality and Outcomes Framework (QOF). GPs are paid to conduct annual physical health checks on patients with serious mental illness, including checks of body mass index (BMI), cholesterol, and alcohol consumption. AIM: To assess the impact of removing and reintroducing QOF financial incentives on uptake of three physical health checks (BMI, cholesterol, and alcohol consumption) for patients with serious mental illness. DESIGN AND SETTING: Cohort study using UK primary care data from the Clinical Practice Research Datalink between April 2011 and March 2020. METHOD: A difference-in-difference analysis was employed to compare differences in the uptake of physical health checks before and after the intervention, accounting for relevant observed and unobserved confounders. RESULTS: An immediate change was found in uptake after physical health checks were removed from, and after they were added back to, the QOF list. For BMI, cholesterol, and alcohol checks, the overall impact of removal was a reduction in uptake of 14.3, 6.8, and 11.9 percentage points, respectively. The reintroduction of BMI screening in the QOF increased the uptake by 10.2 percentage points. CONCLUSION: This analysis supports the hypothesis that QOF incentives lead to better uptake of physical health checks.

Measuring the overall performance of mental healthcare providers.

To date there have been no attempts to construct composite measures of healthcare provider performance which reflect preferences for health and non-health benefits, as well as costs. Health and non-health benefits matter to patients, healthcare providers and the general public. We develop a novel provider performance measurement framework that combines health gain, non-health benefit, and cost and illustrate it with an application to 54 English mental health providers. We apply estimates from a discrete choice experiment eliciting the UK general population's valuation of non-health benefits relative to health gains, to administrative and patient survey data for years 2013-2015 to calculate equivalent health benefit (eHB) for providers. We measure costs as forgone health and quantify the relative performance of providers in terms of equivalent net health benefit (eNHB): the value of the health and non-health benefits minus the forgone benefit equivalent of cost. We compare rankings of providers by eHB, eNHB, and by the rankings produced by the hospital sector regulator. We find that taking account of the non-health benefits in the eNHB measure makes a substantial difference to the evaluation of provider performance. Our study demonstrates that the provider performance evaluation space can be extended beyond measures of health gain and cost, and that this matters for comparison of providers.

Microsimulation Models on Mental Health: A Critical Review of the Literature.

OBJECTIVES: To retrieve and synthesize the literature on existing mental health-specific microsimulation models or generic microsimulation models used to examine mental health, and to critically appraise them. METHODS: All studies on microsimulation and mental health published in English in MEDLINE, Embase, PsycINFO, and EconLit between January 1, 2010, and September 30, 2022, were considered. Snowballing, Google searches, and searches on specific journal websites were also undertaken. Data extraction was done on all studies retrieved and the reporting quality of each model was assessed using the Quality Assessment Reporting for Microsimulation Models checklist, a checklist developed by the research team. A narrative synthesis approach was used to synthesize the evidence. RESULTS: Among 227 potential hits, 19 studies were found to be relevant. Some studies covered existing economic-demographic models, which included a component on mental health and were used to answer mental-health-related research questions. Other studies were focused solely on mental health and included models that were developed to examine the impact of specific policies or interventions on specific mental disorders or both. Most models examined were of medium quality. The main limitations included the use of model inputs based on self-reported and/or cross-sectional data, small and/or nonrepresentative samples and simplifying assumptions, and lack of model validation. CONCLUSIONS: This review found few high-quality microsimulation models on mental health. Microsimulation models developed specifically to examine mental health are important to guide healthcare delivery and service planning. Future research should focus on developing high-quality mental health-specific microsimulation models with wide applicability and multiple functionalities.

Severe and common mental disorders and risk of emergency hospital admissions for ambulatory care sensitive conditions among the UK Biobank cohort.

BACKGROUND: People with mental disorders have worse physical health compared with the general population, which could be attributable to receiving poorer quality healthcare. AIMS: To examine the relationship between severe and common mental disorders and risk of emergency hospital admissions for ambulatory care sensitive conditions (ACSCs), and factors associated with increased risk. METHOD: Baseline data for England (N = 445 814) were taken from UK Biobank, which recruited participants aged 37-73 years during 2006-2010, and linked to hospital admission records up to 31 December 2019. Participants were grouped into those with a history of either schizophrenia, bipolar disorder, depression or anxiety, or no mental disorder. Survival analysis was used to assess the risk of hospital admission for ACSCs among those with mental disorders compared with those without, adjusting for factors in different domains (sociodemographic, socioeconomic, health and biomarkers, health-related behaviours, social isolation and psychological). RESULTS: People with schizophrenia had the highest (unadjusted) risk of hospital admission for ACSCs compared with those with no mental disorder (hazard ratio 4.40, 95% CI 4.04-4.80). People with bipolar disorder (hazard ratio 2.48, 95% CI 2.28-2.69) and depression or anxiety (hazard ratio 1.76, 95% CI 1.73-1.80) also had higher risk. Associations were more conservative when including all admissions, as opposed to first admissions only. The observed associations persisted after adjusting for a range of factors. CONCLUSIONS: People with severe mental disorders have the highest risk of preventable hospital admissions. Ensuring people with mental disorders receive adequate ambulatory care is essential to reduce the large health inequalities they experience.

The impact of COVID-19 on mental health service utilisation in England.

The COVID-19 pandemic has had a significant impact on population mental health and the need for mental health services in many countries, while also disrupting critical mental health services and capacity, as a response to the pandemic. Mental health providers were asked to reconfigure wards to accommodate patients with COVID-19, thereby reducing capacity to provide mental health services. This is likely to have widened the existing mismatch between demand and supply of mental health care in the English NHS. We quantify the impact of these rapid service reconfigurations on activity levels for mental health providers in England during the first thirteen months (March 2020-March 2021) of the COVID-19 pandemic. We use monthly mental health service utilisation data for a large subset of mental health providers in England from January 1, 2015 to March 31, 2021. We use multivariate regression to estimate the difference between observed and expected utilisation from the start of the pandemic in March 2020. Expected utilisation levels (i.e. the counterfactual) are estimated from trends in utilisation observed during the pre-pandemic period January 1, 2015 to February 31, 2020. We measure utilisation as the monthly number of inpatient admissions, discharges, net admissions (admissions less discharges), length of stay, bed days, number of occupied beds, patients with outpatient appointments, and total outpatient appointments. We also calculate the accumulated difference in utilisation from the start of the pandemic period. There was a sharp reduction in total inpatient admissions and net admissions at the beginning of the pandemic, followed by a return to pre-pandemic levels from September 2020. Shorter inpatient stays are observed over the whole period and bed days and occupied bed counts had not recovered to pre-pandemic levels by March 2021. There is also evidence of greater use of outpatient appointments, potentially as a substitute for inpatient care.

Development of a Supported Self-management Intervention for People With Severe Mental Illness and Type 2 Diabetes: Theory and Evidence-Based Co-design Approach.

BACKGROUND: Type 2 diabetes is 2 to 3 times more common among people with severe mental illness (SMI). Self-management is crucial, with additional challenges faced by people with SMI. Therefore, it is essential that any diabetes self-management program for people with SMI addresses the unique needs of people living with both conditions and the inequalities they experience within health care services. OBJECTIVE: We combined theory, empirical evidence, and co-design approaches to develop a type 2 diabetes self-management intervention for people with SMI. METHODS: The development process encompassed 4 steps: step 1 involved prioritizing the mechanisms of action (MoAs) and behavior change techniques (BCTs) for the intervention. Using findings from primary qualitative research and systematic reviews, we selected candidate MoAs to target in the intervention and candidate BCTs to use. Expert stakeholders then ranked these MoAs and BCTs using a 2-phase survey. The average scores were used to generate a prioritized list of MoAs and BCTs. During step 2, we presented the survey results to an expert consensus workshop to seek expert agreement with the definitive list of MoAs and BCTs for the intervention and identify potential modes of delivery. Step 3 involved the development of trigger films using the evidence from steps 1 and 2. We used animations to present the experiences of people with SMI managing diabetes. These films were used in step 4, where we used a stakeholder co-design approach. This involved a series of structured workshops, where the co-design activities were informed by theory and evidence. RESULTS: Upon the completion of the 4-step process, we developed the DIAMONDS (diabetes and mental illness, improving outcomes and self-management) intervention. It is a tailored self-management intervention based on the synthesis of the outputs from the co-design process. The intervention incorporates a digital app, a paper-based workbook, and one-to-one coaching designed to meet the needs of people with SMI and coexisting type 2 diabetes. CONCLUSIONS: The intervention development work was underpinned by the MoA theoretical framework and incorporated systematic reviews, primary qualitative research, expert stakeholder surveys, and evidence generated during co-design workshops. The intervention will now be tested for feasibility before undergoing a definitive evaluation in a pragmatic randomized controlled trial.

Differential costs for the non-adult ADHD population in Catalonia.

Attention-Deficit/Hyperactivity Disorder (ADHD) is young children's most common mental health disorder. We aim to provide causal estimates of the differential costs for the non-adult population with ADHD. We used longitudinal administrative data covering the non-adult population over five years and different healthcare providers (general practitioners, hospitalisations and emergency departments, visits to mental healthcare centres-day-care or hospitals) of 1,101,215 individuals in Catalonia (Spain). We also include the consumption of pharmaceuticals and cognitive therapies. We instrumented ADHD diagnosis by the probability of being diagnosed by the most visited healthcare provider based on individual monthly visits to the provider in which this visit was related to ADHD and the density of professionals in the different mental health providers. After using matching procedures to include a proper control group, we estimated two-part and finite mixture models. Our results indicate that ADHD children and adolescents displayed 610€ higher annual health direct costs compared to not diagnosed counterparts. We provide average costs disentangling the sample by age boundaries, gender, and comorbidities to offer values for cost-effective analyses and incremental costs after diagnosis, which is around 400€. A significant differential annual direct health cost for the non-adult population with ADHD is determined, which will be helpful for cost-effectiveness analysis and complete cost-of-illness studies.

Organisational drivers of performance in mental health providers.

PURPOSE: This study aims to compare and contrast the core organisational processes across high and low performing mental health providers in the English National Health Service (NHS). DESIGN/METHODOLOGY/APPROACH: A multiple case study qualitative design incorporating a full sample of low and high performing mental health providers. FINDINGS: This study suggests that the organisational approaches used to govern and manage mental health providers are associated with their performance, and the study's findings give clues as to what areas might need attention. They include, but are not limited to: developing appropriate governance frameworks and organisational cultures, ensuring that staff across the organisation feel "psychologically safe" and able to speak up when they see things that are going wrong; a focus on enhancing quality of services rather than prioritising cost-reduction; investing in new technology and digital applications; and nurturing positive inter-organisational relationships across the local health economy. ORIGINALITY/VALUE: Highlights considerable divergence in organisation and management practices that are associated with the performance of mental health trusts in the English NHS.

Impact of COVID-19 in mental health trusts.

OBJECTIVE: To explore how mental health trusts in England adapted and responded to the challenges posed by the COVID-19 pandemic, with the aim of identifying lessons that can be learned during and beyond the pandemic. METHODS: Following a scoping study, we undertook 52 semi-structured interviews with senior managers, clinicians, patient representatives and commissioning staff across four case study sites. These sites varied in size, location and grading awarded by a national regulatory body. We explored how services have been repurposed and reorganized in response to the pandemic and the participants' perceptions of the impact of these changes on quality of care and the wellbeing of staff. RESULTS: Mental health trusts have shown great flexibility and resilience in rapidly implementing new models of care and developing creative digital solutions at speed. New collaborative arrangements have been stimulated by a shared sense of urgency and enabled by additional funding and a more permissive policy environment. But there has also been a significant negative impact on the wellbeing of staff, particularly those staff from a minority ethnic background. Also, there were concerns that digital technology could effectively disenfranchise some vulnerable groups and exacerbate existing health inequalities. CONCLUSIONS: Many of the service changes and digital innovations undertaken during the pandemic appear promising. Nevertheless, those changes need to be urgently and rigorously appraised to assure their effectiveness and to assess their impact on social exclusion and health inequalities.

The Role of Mental Health on Workplace Productivity: A Critical Review of the Literature.

BACKGROUND: Mental health disorders in the workplace have increasingly been recognised as a problem in most countries given their high economic burden. However, few reviews have examined the relationship between mental health and worker productivity. OBJECTIVE: To review the relationship between mental health and lost productivity and undertake a critical review of the published literature. METHODS: A critical review was undertaken to identify relevant studies published in MEDLINE and EconLit from 1 January 2008 to 31 May 2020, and to examine the type of data and methods employed, study findings and limitations, and existing gaps in the literature. Studies were critically appraised, namely whether they recognised and/or addressed endogeneity and unobserved heterogeneity, and a narrative synthesis of the existing evidence was undertaken. RESULTS: Thirty-eight (38) relevant studies were found. There was clear evidence that poor mental health (mostly measured as depression and/or anxiety) was associated with lost productivity (i.e., absenteeism and presenteeism). However, only the most common mental disorders were typically examined. Studies employed questionnaires/surveys and administrative data and regression analysis. Few studies used longitudinal data, controlled for unobserved heterogeneity or addressed endogeneity; therefore, few studies were considered high quality. CONCLUSION: Despite consistent findings, more high-quality, longitudinal and causal inference studies are needed to provide clear policy recommendations. Moreover, future research should seek to understand how working conditions and work arrangements as well as workplace policies impact presenteeism.

Impact of prevention in primary care on costs in primary and secondary care for people with serious mental illness.

A largely unexplored part of the financial incentive for physicians to participate in preventive care is the degree to which they are the residual claimant from any resulting cost savings. We examine the impact of two preventive activities for people with serious mental illness (care plans and annual reviews of physical health) by English primary care practices on costs in these practices and in secondary care. Using panel two-part models to analyze patient-level data linked across primary and secondary care, we find that these preventive activities in the previous year are associated with cost reductions in the current quarter both in primary and secondary care. We estimate that there are large beneficial externalities for which the primary care physician is not the residual claimant: the cost savings in secondary care are 4.7 times larger than the cost savings in primary care. These activities are incentivized in the English National Health Service but the total financial incentives for primary care physicians to participate were considerably smaller than the total cost savings produced. This suggests that changes to the design of incentives to increase the marginal reward for conducting these preventive activities among patients with serious mental illness could have further increased welfare.

Multimorbidity clusters among people with serious mental illness: a representative primary and secondary data linkage cohort study.

BACKGROUND: People with serious mental illness (SMI) experience higher mortality partially attributable to higher long-term condition (LTC) prevalence. However, little is known about multiple LTCs (MLTCs) clustering in this population. METHODS: People from South London with SMI and two or more existing LTCs aged 18+ at diagnosis were included using linked primary and mental healthcare records, 2012-2020. Latent class analysis (LCA) determined MLTC classes and multinominal logistic regression examined associations between demographic/clinical characteristics and latent class membership. RESULTS: The sample included 1924 patients (mean (s.d.) age 48.2 (17.3) years). Five latent classes were identified: 'substance related' (24.9%), 'atopic' (24.2%), 'pure affective' (30.4%), 'cardiovascular' (14.1%), and 'complex multimorbidity' (6.4%). Patients had on average 7-9 LTCs in each cluster. Males were at increased odds of MLTCs in all four clusters, compared to the 'pure affective'. Compared to the largest cluster ('pure affective'), the 'substance related' and the 'atopic' clusters were younger [odds ratios (OR) per year increase 0.99 (95% CI 0.98-1.00) and 0.96 (0.95-0.97) respectively], and the 'cardiovascular' and 'complex multimorbidity' clusters were older (ORs 1.09 (1.07-1.10) and 1.16 (1.14-1.18) respectively). The 'substance related' cluster was more likely to be White, the 'cardiovascular' cluster more likely to be Black (compared to White; OR 1.75, 95% CI 1.10-2.79), and both more likely to have schizophrenia, compared to other clusters. CONCLUSION: The current study identified five latent class MLTC clusters among patients with SMI. An integrated care model for treating MLTCs in this population is recommended to improve multimorbidity care.

IT and the Quality and Efficiency of Mental Health Care in a Time of COVID-19: Case Study of Mental Health Providers in England.

BACKGROUND: In England, COVID-19 has significantly affected mental health care and tested the resilience of health care providers. In many areas, the increased use of IT has enabled traditional modes of service delivery to be supported or even replaced by remote forms of provision. OBJECTIVE: This study aimed to assess the use and impact of IT, in remote service provision, on the quality and efficiency of mental health care during the pandemic. We drew on sociotechnical systems theory as a conceptual framework to help structure the gathering, analysis, and interpretation of data. METHODS: We conducted a national scoping survey that involved documentary analysis and semistructured interviews with 6 national stakeholders and case studies of 4 purposefully selected mental health providers in England involving interviews with 53 staff members. RESULTS: Following the outbreak of COVID-19, mental health providers rapidly adjusted their traditional forms of service delivery, switching to digital and telephone consultations for most services. The informants provided nuanced perspectives on the impact on the quality and efficiency of remote service delivery during the pandemic. Notably, it has allowed providers to attend to as many patients as possible in the face of COVID-19 restrictions, to the convenience of both patients and staff. Among its negative effects are concerns about the unsuitability of remote consultation for some people with mental health conditions and the potential to widen the digital divide and exacerbate existing inequalities. Sociotechnical systems theory was found to be a suitable framework for understanding the range of systemic and sociotechnical factors that influence the use of technology in mental health care delivery in times of crisis and normalcy. CONCLUSIONS: Although the use of IT has boosted mental health care delivery during the pandemic, it has had mixed effects on quality and efficiency. In general, patients have benefited from the convenience of remote consultation when face-to-face contact was impossible. In contrast, patient choice was often compromised, and patient experience and outcomes might have been affected for some people with mental health conditions for which remote consultation is less suitable. However, the full impact of IT on the quality and efficiency of mental health care provision along with the systemic and sociotechnical determinants requires more sustained and longitudinal research.

Association of environmental and socioeconomic indicators with serious mental illness diagnoses identified from general practitioner practice data in England: A spatial Bayesian modelling study.

BACKGROUND: The evidence is sparse regarding the associations between serious mental illnesses (SMIs) prevalence and environmental factors in adulthood as well as the geographic distribution and variability of these associations. In this study, we evaluated the association between availability and proximity of green and blue space with SMI prevalence in England as a whole and in its major conurbations (Greater London, Birmingham, Liverpool and Manchester, Leeds, and Newcastle). METHODS AND FINDINGS: We carried out a retrospective analysis of routinely collected adult population (≥18 years) data at General Practitioner Practice (GPP) level. We used data from the Quality and Outcomes Framework (QOF) on the prevalence of a diagnosis of SMI (schizophrenia, bipolar affective disorder and other psychoses, and other patients on lithium therapy) at the level of GPP over the financial year April 2014 to March 2018. The number of GPPs included ranged between 7,492 (April 2017 to March 2018) to 7,997 (April 2014 to March 2015) and the number of patients ranged from 56,413,719 (April 2014 to March 2015) to 58,270,354 (April 2017 to March 2018). Data at GPP level were converted to the geographic hierarchy unit Lower Layer Super Output Area (LSOA) level for analysis. LSOAs are a geographic unit for reporting small area statistics and have an average population of around 1,500 people. We employed a Bayesian spatial regression model to explore the association of SMI prevalence in England and its major conurbations (greater London, Birmingham, Liverpool and Manchester, Leeds, and Newcastle) with environmental characteristics (green and blue space, flood risk areas, and air and noise pollution) and socioeconomic characteristics (age, ethnicity, and index of multiple deprivation (IMD)). We incorporated spatial random effects in our modelling to account for variation at multiple scales. Across England, the environmental characteristics associated with higher SMI prevalence at LSOA level were distance to public green space with a lake (prevalence ratio [95% credible interval]): 1.002 [1.001 to 1.003]), annual mean concentration of PM2.5 (1.014 [1.01 to 1.019]), and closeness to roads with noise levels above 75 dB (0.993 [0.992 to 0.995]). Higher SMI prevalence was also associated with a higher percentage of people above 24 years old (1.002 [1.002 to 1.003]), a higher percentage of ethnic minorities (1.002 [1.001 to 1.002]), and more deprived areas. Mean SMI prevalence at LSOA level in major conurbations mirrored the national associations with a few exceptions. In Birmingham, higher average SMI prevalence at LSOA level was positively associated with proximity to an urban green space with a lake (0.992 [0.99 to 0.998]). In Liverpool and Manchester, lower SMI prevalence was positively associated with road traffic noise ≥75 dB (1.012 [1.003 to 1.022]). In Birmingham, Liverpool, and Manchester, there was a positive association of SMI prevalence with distance to flood zone 3 (land within flood zone 3 has ≥1% chance of flooding annually from rivers or ≥0.5% chance of flooding annually from the sea, when flood defences are ignored): Birmingham: 1.012 [1.000 to 1.023]; Liverpool and Manchester: 1.016 [1.006 to 1.026]. In contrast, in Leeds, there was a negative association between SMI prevalence and distance to flood zone 3 (0.959 [0.944 to 0.975]). A limitation of this study was because we used a cross-sectional approach, we are unable to make causal inferences about our findings or investigate the temporal relationship between outcome and risk factors. Another limitation was that individuals who are exclusively treated under specialist mental health care and not seen in primary care at all were not included in this analysis. CONCLUSIONS: Our study provides further evidence on the significance of socioeconomic associations in patterns of SMI but emphasises the additional importance of considering environmental characteristics alongside socioeconomic variables in understanding these patterns. In this study, we did not observe a significant association between green space and SMI prevalence, but we did identify an apparent association between green spaces with a lake and SMI prevalence. Deprivation, higher concentrations of air pollution, and higher proportion of ethnic minorities were associated with higher SMI prevalence, supporting a social-ecological approach to public health prevention. It also provides evidence of the significance of spatial analysis in revealing the importance of place and context in influencing area-based patterns of SMI.

Valuing quality in mental healthcare: A discrete choice experiment eliciting preferences from mental healthcare service users, mental healthcare professionals and the general population.

High and sustained healthcare quality is important worldwide, though health policy may prioritise the achievement of certain aspects of quality over others. This study determines the relative importance of different aspects of mental healthcare quality to different stakeholders by eliciting preferences in a UK sample using a discrete choice experiment (DCE). DCE attributes were generated using triangulation between policy documents and mental healthcare service user and mental healthcare professional views, whilst ensuring attributes were measurable using available data. Ten attributes were selected: waiting times; ease of access; person-centred care; co-ordinated approach; continuity; communication, capacity and resources; treated with dignity and respect; recovery focus; inappropriate discharge; quality of life (QoL). The DCE was conducted online (December 2018 to February 2019) with mental healthcare service users (n = 331), mental healthcare professionals (n = 510), and members of the general population (n = 1018). Respondents' choices were analysed using conditional logistic regression. Relative preferences for each attribute were generated using the marginal rate of substitution (MRS) with QoL as numeraire. Across all stakeholders, being treated with dignity and respect was of high importance. A coordinated approach was important across all stakeholders, whereas communication had higher relative importance for healthcare professionals and service users and ease of access had higher relative importance for the general population. This implies that policy could be affected by the choice of whose preferences (service users, healthcare professionals or general population) to use, since this impacts on the relative value and implied ranking of different aspects of mental healthcare quality.

Healthcare resource use and costs for people with type 2 diabetes mellitus with and without severe mental illness in England: longitudinal matched-cohort study using the Clinical Practice Research Datalink.

BACKGROUND: Approximately 60 000 people in England have coexisting type 2 diabetes mellitus (T2DM) and severe mental illness (SMI). They are more likely to have poorer health outcomes and require more complex care pathways compared with those with T2DM alone. Despite increasing prevalence, little is known about the healthcare resource use and costs for people with both conditions. AIMS: To assess the impact of SMI on healthcare resource use and service costs for adults with T2DM, and explore the predictors of healthcare costs and lifetime costs for people with both conditions. METHOD: This was a matched-cohort study using data from the Clinical Practice Research Datalink linked to Hospital Episode Statistics for 1620 people with comorbid SMI and T2DM and 4763 people with T2DM alone. Generalised linear models and the Bang and Tsiatis method were used to explore cost predictors and mean lifetime costs respectively. RESULTS: There were higher average annual costs for people with T2DM and SMI (£1930 higher) than people with T2DM alone, driven primarily by mental health and non-mental health-related hospital admissions. Key predictors of higher total costs were older age, comorbid hypertension, use of antidepressants, use of first-generation antipsychotics, and increased duration of living with both conditions. Expected lifetime costs were approximately £35 000 per person with both SMI and T2DM. Extrapolating nationally, this would generate total annual costs to the National Health Service of around £250 m per year. CONCLUSIONS: Our estimates of resource use and costs for people with both T2DM and SMI will aid policymakers and commissioners in service planning and resource allocation.

Economic inequality and depressive symptoms: an individual versus aggregate-level analysis using Mexican survey data.

BACKGROUND: There is a lack of consensus on the relationship between economic inequality and mental health, which may be due to the measures of inequality used in empirical studies. We studied this relationship using individual and aggregate measures of economic inequality, and tested whether there is an interaction between the individual and the aggregate levels. METHODS: We used data from a nationally representative Mexican health survey (Encuesta Nacional de Salud y Nutrición, n=44 324) where depressive symptoms were measured through a validated 7-item version of the Centre for Epidemiologic Studies Depression Scale. We estimated multilevel models employing aggregate inequality measures (Gini coefficient) and the individual-level framework of advantageous and disadvantageous inequality, where economic status comprised absolute wealth, relative deprivation and relative affluence. RESULTS: The three facets of economic status were independently associated with depressive symptoms, while Gini coefficients showed no associations. Absolute wealth and relative affluence were associated with lower depressive symptoms while relative deprivation was associated with higher depressive symptoms. However, interaction models indicated an interplay between the Gini and relative affluence: higher status became a risk factor at high levels of aggregate economic inequality. For those at the top of the economic hierarchy, being in a context of high inequality more than doubles our measure of depressive symptoms-from 2.08 (95% CI 1.28 to 2.87) to 6.29 (95% CI 4.1 to 8.5) for state inequality and from 2.40 (95% CI 1.64 to 3.16) to 6.24 (95% CI 3.87 to 8.62) for municipal inequality. CONCLUSION: We provided a novel perspective on the economic gradient in mental health, and on how high aggregate economic inequality may harm also the better off. Policymakers need to consider the consequences of economic inequalities, which can harm the mental health of both those at the bottom and the top of the socioeconomic ladder.

Exploring the facilitators, barriers, and strategies for self-management in adults living with severe mental illness, with and without long-term conditions: A qualitative evidence synthesis.

BACKGROUND: People living with severe mental illness (SMI) have a reduced life expectancy by around 15-20 years, in part due to higher rates of long-term conditions (LTCs) such as diabetes and heart disease. Evidence suggests that people with SMI experience difficulties managing their physical health. Little is known, however, about the barriers, facilitators and strategies for self-management of LTCs for people with SMI. AIM: To systematically review and synthesise the qualitative evidence exploring facilitators, barriers and strategies for self-management of physical health in adults with SMI, both with and without long-term conditions. METHODS: CINAHL, Conference Proceedings Citation Index- Science, HMIC, Medline, NICE Evidence and PsycInfo were searched to identify qualitative studies that explored barriers, facilitators and strategies for self-management in adults with SMI (with or without co-morbid LTCs). Articles were screened independently by two independent reviewers. Eligible studies were purposively sampled for synthesis according to the richness and relevance of data, and thematically synthesised. RESULTS: Seventy-four articles met the inclusion criteria for the review; 25 articles, reporting findings from 21 studies, were included in the synthesis. Seven studies focused on co-morbid LTC self-management for people with SMI, with the remaining articles exploring self-management in general. Six analytic themes and 28 sub-themes were identified from the synthesis. The themes included: the burden of SMI; living with co-morbidities; beliefs and attitudes about self-management; support from others for self-management; social and environmental factors; and routine, structure and planning. CONCLUSIONS: The synthesis identified a range of barriers and facilitators to self-management, including the burden of living with SMI, social support, attitudes towards self-management and access to resources. To adequately support people with SMI with co-morbid LTCs, healthcare professionals need to account for how barriers and facilitators to self-management are influenced by SMI, and meet the unique needs of this population.

Determinants of Physical Health Self-Management Behaviours in Adults With Serious Mental Illness: A Systematic Review.

Behavioural interventions can support the adoption of healthier lifestyles and improve physical health outcomes, but it is unclear what factors might drive success of such interventions in people with serious mental illness (SMI). We systematically identified and reviewed evidence of the association between determinants of physical health self-management behaviours in adults with SMI. Data about American Association of Diabetes Educator's Self-Care Behaviours (AADE-7) were mapped against the novel Mechanisms of Action (MoA) framework. Twenty-eight studies were included in the review, reporting evidence on 104 determinant-behaviour links. Beliefs about capabilities and beliefs about consequences were the most important determinants of behaviour, especially for being physically active and healthy eating. There was some evidence that emotion and environmental context and resources played a role in determining reducing risks, being active, and taking medications. We found very limited evidence associated with problem solving, and no study assessed links between MoAs and healthy coping. Although the review predominantly identified evidence about associations from cross-sectional studies that lacked validated and objective measures of self-management behaviours, these findings can facilitate the identification of behaviour change techniques with hypothesised links to determinants to support self-management in people with SMI. Systematic Review Registration: PROSPERO, registration CRD42018099553.

Examining equity in the utilisation of psychiatric inpatient care among patients with severe mental illness (SMI) in Ontario, Canada.

BACKGROUND: Severe mental illness (SMI) comprises a range of chronic and disabling conditions, such as schizophrenia, bipolar disorder and other psychoses. Despite affecting a small percentage of the population, these disorders are associated with poor outcomes, further compounded by disparities in access, utilisation, and quality of care. Previous research indicates there is pro-poor inequality in the utilisation of SMI-related psychiatric inpatient care in England (in other words, individuals in more deprived areas have higher utilisation of inpatient care than those in less deprived areas). Our objective was to determine whether there is pro-poor inequality in SMI-related psychiatric admissions in Ontario, and understand whether these inequalities have changed over time. METHODS: We selected all adult psychiatric admissions from April 2006 to March 2011. We identified changes in socio-economic equity over time across deprivation groups and geographic units by modeling, through ordinary least squares, annual need-expected standardised utilisation as a function of material deprivation and other relevant variables. We also tested for changes in socio-economic equity of utilisation over years, where the number of SMI-related psychiatric admissions for each geographic unit was modeled using a negative binomial model. RESULTS: We found pro-poor inequality in SMI-related psychiatric admissions in Ontario. For every one unit increase in deprivation, psychiatric admissions increased by about 8.1%. Pro-poor inequality was particularly present in very urban areas, where many patients with SMI reside, and very rural areas, where access to care is problematic. Our main findings did not change with our sensitivity analyses. Furthermore, this inequality did not change over time. CONCLUSIONS: Individuals with SMI living in more deprived areas of Ontario had higher psychiatric admissions than those living in less deprived areas. Moreover, our findings suggest this inequality has remained unchanged over time. Despite the debate around whether to make more or less use of inpatient versus other care, policy makers should seek to address suboptimal supply of primary, community or social care for SMI patients. This may potentially be achieved through the elimination of barriers to access psychiatrist care and the implementation of universal coverage of psychotherapy.