Variation in compulsory psychiatric inpatient admission in England:a cross-sectional, multilevel analysis

Background: Rates of compulsory admission have increased in England in recent decades, and this trend is accelerating. Studying variation in rates between people and places can help identify modifiable causes. Objectives: To quantify and model variances in the rate of compulsory admission in England at different spatial levels and to assess the extent to which this was explained by characteristics of people and places. Design: Cross-sectional analysis using multilevel statistical modelling. Setting: England, including 98% of Census lower layer super output areas (LSOAs), 95% of primary care trusts (PCTs), 93% of general practices and all 69 NHS providers of specialist mental health services. Participants: 1,287,730 patients. Main outcome measure: The study outcome was compulsory admission, defined as time spent in an inpatient mental illness bed subject to the Mental Health Act (2007) in 2010/11. We excluded patients detained under sections applying to emergency assessment only (including those in places of safety), guardianship or supervision of community treatment. The control group comprised all other users of specialist mental health services during the same period. Data sources: The Mental Health Minimum Data Set (MHMDS). Data on explanatory variables, characterising each of the spatial levels in the data set, were obtained from a wide range of sources, and were linked using MHMDS identifiers. Results: A total of 3.5% of patients had at least one compulsory admission in 2010/11. Of (unexplained) variance in the null model, 84.5% occurred between individuals. Statistically significant variance occurred between LSOAs [6.7%, 95% confidence interval (CI) 6.2% to 7.2%] and provider trusts (6.9%, 95% CI 4.3% to 9.5%). Variances at these higher levels remained statistically significant even after adjusting for a large number of explanatory variables, which together explained only 10.2% of variance in the study outcome. The number of provider trusts whose observed rate of compulsory admission differed from the model average to a statistically significant extent fell from 45 in the null model to 20 in the fully adjusted model. We found statistically significant associations between compulsory admission and age, gender, ethnicity, local area deprivation and ethnic density. There was a small but statistically significant association between (higher) bed occupancy and compulsory admission, but this was subsequently confounded by other covariates. Adjusting for PCT investment in mental health services did not improve model fit in the fully adjusted models. Conclusions: This was the largest study of compulsory admissions in England. While 85% of the variance in this outcome occurred between individuals, statistically significant variance (around 7% each) occurred between places (LSOAs) and provider trusts. This higher-level variance in compulsory admission remained largely unchanged even after adjusting for a large number of explanatory variables. We were constrained by data available to us, and therefore our results must be interpreted with caution. We were also unable to consider many hypotheses suggested by the service users, carers and professionals who we consulted. There is an imperative to develop and evaluate interventions to reduce compulsory admission rates. This requires further research to extend our understanding of the reasons why these rates remain so high. Funding: The National Institute for Health Research Health Services and Delivery Research programme

Authors' Response to Peer Reviews of “Using Structural Equation Modelling in Routine Clinical Data on Diabetes and Depression: Observational Cohort Study”

Background: Large data sets comprising routine clinical data are becoming increasingly available for use in health research. These data sets contain many clinical variables that might not lend themselves to use in research. Structural equation modelling (SEM) is a statistical technique that might allow for the creation of “research-friendly” clinical constructs from these routine clinical variables and therefore could be an appropriate analytic method to apply more widely to routine clinical data. Objective: SEM was applied to a large data set of routine clinical data developed in East London to model well-established clinical associations. Depression is common among patients with type 2 diabetes, and is associated with poor diabetic control, increased diabetic complications, increased health service utilization, and increased health care costs. Evidence from trial data suggests that integrating psychological treatment into diabetes care can improve health status and reduce costs. Attempting to model these known associations using SEM will test the utility of this technique in routine clinical data sets. Methods: Data were cleaned extensively prior to analysis. SEM was used to investigate associations between depression, diabetic control, diabetic care, mental health treatment, and Accident & Emergency (A&E) use in patients with type 2 diabetes. The creation of the latent variables and the direction of association between latent variables in the model was based upon established clinical knowledge. Results: The results provided partial support for the application of SEM to routine clinical data. Overall, 19% (3106/16,353) of patients with type 2 diabetes had received a diagnosis of depression. In line with known clinical associations, depression was associated with worse diabetic control (β=.034, P<.001) and increased A&E use (β=.071, P<.001). However, contrary to expectation, worse diabetic control was associated with lower A&E use (β=–.055, P<.001) and receipt of mental health treatment did not impact upon diabetic control (P=.39). Receipt of diabetes care was associated with better diabetic control (β=–.072, P<.001), having depression (β=.018, P=.007), and receiving mental health treatment (β=.046, P<.001), which might suggest that comprehensive integrated care packages are being delivered in East London. Conclusions: Some established clinical associations were successfully modelled in a sample of patients with type 2 diabetes in a way that made clinical sense, providing partial evidence for the utility of SEM in routine clinical data. Several issues relating to data quality emerged. Data improvement would have likely enhanced the utility of SEM in this data set

Size and clustering of ethnic groups and rates of psychiatric admission in England

Aims and method To compare rates of admission for different types of severe mental illness between ethnic groups, and to test the hypothesis that larger and more clustered ethnic groups will have lower admission rates. This was a descriptive study of routinely collected data from the National Health Service in England. Results There was an eightfold difference in admission rates between ethnic groups for schizophreniform and mania admissions, and a fivefold variation in depression admissions. On average, Black and minority ethnic (BME) groups had higher rates of admission for schizophreniform and mania admissions but not for depression. This increased rate was greatest in the teenage years and early adulthood. Larger ethnic group size was associated with lower admission rates. However, greater clustering was associated with higher admission rates. Clinical implications Our findings support the hypothesis that larger ethnic groups have lower rates of admission. This was a between-group comparison rather than within each group. Our findings do not support the hypothesis that more clustered groups have lower rates of admission. In fact, they suggest the opposite: groups with low clustering had lower admission rates. The BME population in the UK is increasing in size and becoming less clustered. Our results suggest that both of these factors should ameliorate the overrepresentation of BME groups among psychiatric in-patients. However, this overrepresentation continues, and our results suggest a possible explanation, namely, changes in the delivery of mental health services, particularly the marked reduction in admissions for depression

Use of community treatment orders and their outcomes: an observational study

Background Community treatment orders are widely used in England. It is unclear whether their use varies between patients, places and services, or if they are associated with better patient outcomes. Objectives To examine variation in the use of community treatment orders and their associations with patient outcomes and health-care costs. Design Secondary analysis using multilevel statistical modelling. Setting England, including 61 NHS mental health provider trusts. Participants A total of 69,832 patients eligible to be subject to a community treatment order. Main outcome measures Use of community treatment orders and time subject to community treatment order; re-admission and total time in hospital after the start of a community treatment order; and mortality. Data sources The primary data source was the Mental Health Services Data Set. Mental Health Services Data Set data were linked to mortality records and local area deprivation statistics for England. Results There was significant variation in community treatment order use between patients, provider trusts and local areas. Most variation arose from substantially different practice in a small number of providers. Community treatment order patients were more likely to be in the ‘severe psychotic’ care cluster grouping, male or black. There was also significant variation between service providers and local areas in the time patients remained on community treatment orders. Although slightly more community treatment order patients were re-admitted than non-community treatment order patients during the study period (36.9% vs. 35.6%), there was no significant difference in time to first re-admission (around 32 months on average for both). There was some evidence that the rate of re-admission differed between community treatment order and non-community treatment order patients according to care cluster grouping. Community treatment order patients spent 7.5 days longer, on average, in admission than non-community treatment order patients over the study period. This difference remained when other patient and local area characteristics were taken into account. There was no evidence of significant variation between service providers in the effect of community treatment order on total time in admission. Community treatment order patients were less likely to die than non-community treatment order patients, after taking account of other patient and local area characteristics (odds ratio 0.69, 95% credible interval 0.60 to 0.81). Limitations Confounding by indication and potential bias arising from missing data within the Mental Health Services Data Set. Data quality issues precluded inclusion of patients who were subject to community treatment orders more than once. Conclusions Community treatment order use varied between patients, provider trusts and local areas. Community treatment order use was not associated with shorter time to re-admission or reduced time in hospital to a statistically significant degree. We found no evidence that the effectiveness of community treatment orders varied to a significant degree between provider trusts, nor that community treatment orders were associated with reduced mental health treatment costs. Our findings support the view that community treatment orders in England are not effective in reducing future admissions or time spent in hospital. We provide preliminary evidence of an association between community treatment order use and reduced rate of death. Future work These findings need to be replicated among patients who are subject to community treatment order more than once. The association between community treatment order use and reduced mortality requires further investigation. Study registration The study was approved by the University of Warwick’s Biomedical and Scientific Research Ethics Committee (REGO-2015-1623). Funding This project was funded by the National Institute for Health Research (NIHR) Health Services and Delivery Research programme and will be published in full in Health Services and Delivery Research; Vol. 8, No. 9. See the NIHR Journals Library website for further project information

Pathways to Care: Duration of Untreated Psychosis from Karachi, Pakistan

Background: Substantial amount of time is lost before initiation of treatment in Schizophrenia. The delay in treatment is labelled as Duration of Untreated Psychosis (DUP). Most of these estimates come from western countries, where health systems are relatively better developed. There is dearth of information on pathway to care from developing countries. Methods And Results: Patients with ICD-10 based diagnosis of Schizophrenia were enrolled by convenient method of sampling. The pathway to care was explored through a semi-structured questionnaire. Onset, course and symptoms of psychosis were assessed using Interview for the Retrospective Assessment of the Onset of Schizophrenia (IRAOS). Ethical approval of the project was taken from The Aga Khan University, Ethics Review Committee. Of the enrolled 93 subjects, 55 (59%) were males and 38 (41%) were females. In our sample, 1.56 mean (median, 2) attempts were made prior to successful help seeking. The duration of untreated psychosis was 14.8 months (St. Deviation, 29.4). DUP was 16.8 months (St. Deviation, 34.9) for males and 11.8 months (St. Deviation, 18.9) for females. In the pathway to care, psychiatrists featured prominently as initial care providers. In the first attempt at help-seeking, 43% Patients were initially taken to psychiatrists. After the initial consultation, 45% were prescribed psychotropic medication while 7% were hospitalized. Only 9% subjects were given the diagnosis of schizophrenia initially. When participants were inquired about the reasons for delay, 29% reported financial difficulties as the barrier to care. Positive symptoms of psychosis were present in 57% subjects while negative symptoms were present in 30% subjects. There was a statistically significant difference (Chi-square, 7.928, df: 1, Sig 0.005) between DUP and the positive and negative symptoms category. Conclusion: In the absence of well developed primary care health system in Pakistan, majority of Patients present to psychiatrists as a first contact. DUP, as a measurement of help seeking behaviour, tends to be shorter with positive symptoms of Schizophrenia. Substantial amount of time is lost due to non recognition of disease and subsequently, inadequate treatment. Secondary prevention strategies should focus on families, which play an important role in the treatment-seeking process of psychotic Patients

Service provision and barriers to care for homeless people with mental health problems across 14 European capital cities

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Ethnic inequities in multimorbidity among people with psychosis: a retrospective cohort study

Aims: Research shows persistent ethnic inequities in mental health experiences and outcomes, with a higher incidence of illnesses among minoritised ethnic groups. People with psychosis have an increased risk of multiple long-term conditions (MLTC; multimorbidity). However, there is limited research regarding ethnic inequities in multimorbidity in people with psychosis. This study investigates ethnic inequities in physical health multimorbidity in a cohort of people with psychosis. Methods: In this retrospective cohort study, using the Clinical Records Interactive Search (CRIS) system, we identified service-users of the South London and Maudsley NHS Trust with a schizophrenia spectrum disorder, and then additional diagnoses of diabetes, hypertension, low blood pressure, overweight or obesity and rheumatoid arthritis. Logistic and multinomial logistic regressions were used to investigate ethnic inequities in odds of multimorbidity (psychosis plus one physical health condition), and multimorbidity severity (having one or two physical health conditions, or three or more conditions), compared with no additional health conditions (no multimorbidity), respectively. The regression models adjusted for age and duration of care and investigated the influence of gender and area-level deprivation. Results: On a sample of 20 800 service-users with psychosis, aged 13–65, ethnic differences were observed in the odds for multimorbidity. Controlling for sociodemographic factors and duration of care, compared to White British people, higher odds of multimorbidity were found for people of Black African [adjusted Odds Ratio = 1.41, 95% Confidence Intervals (1.23–1.56)], Black Caribbean [aOR = 1.79, 95% CI (1.58–2.03)] and Black British [aOR = 1.64, 95% CI (1.49–1.81)] ethnicity. Reduced odds were observed among people of Chinese [aOR = 0.61, 95% CI (0.43–0.88)] and Other ethnic [aOR = 0.67, 95% CI (0.59–0.76)] backgrounds. Increased odds of severe multimorbidity (three or more physical health conditions) were also observed for people of any Black background. Conclusions: Ethnic inequities are observed for multimorbidity among people with psychosis. Further research is needed to understand the aetiology and impact of these inequities. These findings support the provision of integrated health care interventions and public health preventive policies and actions

A public health approach to understanding and preventing violent radicalization

<p>Abstract</p> <p>Background</p> <p>Very recent acts of terrorism in the UK were perpetrated by 'homegrown', well educated young people, rather than by foreign Islamist groups; consequently, a process of violent radicalization was proposed to explain how ordinary people were recruited and persuaded to sacrifice their lives.</p> <p>Discussion</p> <p>Counterterrorism approaches grounded in the criminal justice system have not prevented violent radicalization. Indeed there is some evidence that these approaches may have encouraged membership of radical groups by not recognizing Muslim communities as allies, citizens, victims of terrorism, and victims of discrimination, but only as suspect communities who were then further alienated. Informed by public health research and practice, a new approach is proposed to target populations vulnerable to recruitment, rather than rely only on research of well known terrorist groups and individual perpetrators of terrorist acts.</p> <p>Conclusions</p> <p>This paper proposes public health research and practice to guard against violent radicalization.</p

Do 'alternative' help-seeking strategies affect primary care service use? A survey of help-seeking for mental distress

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Immigration and recommended care after a suicide attempt in Europe: equity or bias?

This report describes the investigation of care recommendations in the medical system across European countries to immigrants who attempted suicide. Data from seven European countries with 8865 local and 2921 immigrant person-cases were derived from the WHO/EURO Multicentre Study on Suicidal Behaviour and ensuing MONSUE (Monitoring Suicidal Behaviour in Europe) project. The relationship between immigrant status and type of aftercare recommended was analysed with binary logistic regression, adjusting for gender, age, method of attempt and the Centre collecting the data. Clear disparities were identified in the care recommendation practices toward immigrants, compared with hosts, over and above differing policies by the European Centres