A needs index for mental health care in England based on updatable data

Psychosis prevalence in London neighbourhoods; A case study in spatial confounding

Analysis of impacts of neighbourhood risk factors on mental health outcomes frequently adopts a disease mapping approach, with unknown neighbourhood influences summarised by random effects. However, such effects may show confounding with observed predictors, especially when such predictors have a clear spatial pattern. Here, the standard disease mapping model is compared to methods which account and adjust for spatial confounding in an analysis of psychosis prevalence in London neighbourhoods. Established area risk factors such as area deprivation, non-white ethnicity, greenspace access and social fragmentation are considered as influences on psychosis. The results show evidence of spatial confounding in the standard disease mapping model. Impacts expected on substantive grounds and available evidence are either nullified or reversed in direction. It is argued that the potential for spatial confounding to affect inferences about geographic disease patterns and risk factors should be routinely considered in ecological studies of health based on disease mapping.

A diabetes risk index for small areas in England

UK and international studies point to significant area variation in diabetes risk, and summary indices of diabetic risk are potentially of value in effective targeting of health interventions and healthcare resources. This paper aims to develop a summary measure of the diabetic risk environment which can act as an index for targeting health care resources. The diabetes risk index is for 6791 English small areas (which provide entire coverage of England) and has advantages in incorporating evidence from both diabetes outcomes and area risk factors, and in including spatial correlation in its construction. The analysis underlying the risk index shows that area socio-economic status, social fragmentation and south Asian ethnic concentration are all positive risk factors for diabetes risk. However, urban-rural and regional differences in risk intersect with these socio-demographic influences.

Factors associated with quality of services for marginalized groups with mental health problems in 14 European countries

BACKGROUND

Different service characteristics are known to influence mental health care delivery. Much less is known about the impact of contextual factors, such as the socioeconomic circumstances, on the provision of care to socially marginalized groups.The objectives of this work were to assess the organisational characteristics of services providing mental health care for marginalized groups in 14 European capital cities and to explore the associations between organisational quality, service features and country-level characteristics.

METHODS

617 services were assessed in two highly deprived areas in 14 European capital cities. A Quality Index of Service Organisation (QISO) was developed and applied across all sites. Service characteristics and country level socioeconomic indicators were tested and related with the Index using linear regressions and random intercept linear models.

RESULTS

The mean (standard deviation) of the QISO score (minimum = 0; maximum = 15) varied from 8.63 (2.23) in Ireland to 12.40 (2.07) in Hungary. The number of different programmes provided was the only service characteristic significantly correlated with the QISO (p < 0.05). The national Gross Domestic Product (GDP) was inversely associated with the QISO. Nearly 15% of the variance of the QISO was attributed to country-level variables, with GDP explaining 12% of this variance.

CONCLUSIONS

Socioeconomic contextual factors, in particular the national GDP are likely to influence the organisational quality of services providing mental health care for marginalized groups. Such factors should be considered in international comparative studies. Their significance for different types of services should be explored in further research.

A population-level prediction tool for the incidence of first-episode psychosis: translational epidemiology based on cross-sectional data

OBJECTIVES

Specialist early intervention services (EIS) for people aged 14-35 years with first episodes of psychosis (FEP) have been commissioned throughout England since 2001. A single estimate of population need was used everywhere, but true incidence varies enormously according to sociodemographic factors. We sought to develop a realistically complex, population-based prediction tool for FEP, based on precise estimates of epidemiological risk.

DESIGN AND PARTICIPANTS

Data from 1037 participants in two cross-sectional population-based FEP studies were fitted to several negative binomial regression models to estimate risk coefficients across combinations of different sociodemographic and socioenvironmental factors. We applied these coefficients to the population at-risk of a third, socioeconomically different region to predict expected caseload over 2.5 years, where the observed rates of ICD-10 F10-39 FEP had been concurrently ascertained via EIS.

SETTING

Empirical population-based epidemiological data from London, Nottingham and Bristol predicted counts in the population at-risk in the East Anglia region of England.

MAIN OUTCOME MEASURES

Observed counts were compared with predicted counts (with 95% prediction intervals (PI)) at EIS and local authority district (LAD) levels in East Anglia to establish the predictive validity of each model.

RESULTS

A model with age, sex, ethnicity and population density performed most strongly, predicting 508 FEP participants in EIS in East Anglia (95% PI 459, 559), compared with 522 observed participants. This model predicted correctly in 5/6 EIS and 19/21 LADs. All models performed better than the current gold standard for EIS commissioning in England (716 cases; 95% PI 664-769).

CONCLUSIONS

We have developed a prediction tool for the incidence of psychotic disorders in England and Wales, made freely available online (http://www.psymaptic.org), to provide healthcare commissioners with accurate forecasts of FEP based on robust epidemiology and anticipated local population need. The initial assessment of some people who do not require subsequent EIS care means additional service resources, not addressed here, will be required.

Importance of thinking locally for mental health: data from cross-sectional surveys representing South East London and England

BACKGROUND

Reliance on national figures may be underestimating the extent of mental ill health in urban communities. This study demonstrates the necessity for local information on common mental disorder (CMD) and substance use by comparing data from the South East London Community Health (SELCoH) study with those from a national study, the 2007 English Adult Psychiatric Morbidity Study (APMS).

METHODOLOGY/PRINCIPAL FINDINGS

Data were used from two cross-sectional surveys, 1698 men and women residing in south London and 7403 men and women in England. The main outcome, CMD, was indicated by a score of 12 or above on the Revised Clinical Interview Schedule. Secondary outcomes included hazardous alcohol use and illicit drug use. SELCoH sample prevalence estimates of CMD were nearly twice that of the APMS England sample estimates. There was a four-fold greater proportion of depressive episode in the SELCoH sample than the APMS sample. The prevalence of hazardous alcohol use was higher in the national sample. Illicit drug use in the past year was higher in the SELCoH sample, with cannabis and cocaine the illicit drugs reported most frequently in both samples. In comparisons of the SELCoH sample with the APMS England sample and the APMS sample from the Greater London area in combined datasets, these differences remained after adjusting for socio-demographic and socioeconomic indicators for all outcomes.

CONCLUSIONS/SIGNIFICANCE

Local information for estimating the prevalence of CMD and substance use is essential for surveillance and service planning. There were similarities in the demographic and socioeconomic factors related to CMD and substance use across samples.

Cohort profile: the Caerphilly health and social needs electronic cohort study (E-CATALyST)

The Caerphilly Health and Social Needs study was established to inform and support collaborative multiagency working on reducing inequalities in health and to investigate neighbourhood influences on mental health. Initially, we collated a robust small-area multiagency dataset of contextual health determinants and outcomes from routine sources and sharing of data between the National Health Service and Caerphilly county borough council. These data were widely used in local joint planning to improve health and reduce health inequalities. Secondly, we carried out a baseline population questionnaire survey, collecting data from 10 892 (60.6%) respondents aged 18-74 years on a wide range of socio-economic, lifestyle, health and housing factors and perceptions of the local neighbourhood, including access to services, social cohesion and neighbourhood quality. We carried out wave 2 of the survey after 7 years with responses from 4558 (50.2%) participants to the same range of questions. We developed the study into an electronic cohort, linking all 17 979 sampled participants aged 18-74 years to mortality and hospital admission records with 10-year follow-up and full recording of migration both within and out of the borough. Readers with an interest in collaborative use of the data should contact Professor David Fone, Principal Investigator.

Generating small-area prevalence of psychological distress and alcohol consumption: validation of a spatial microsimulation method

PURPOSE

Public mental health surveillance data are rarely available at a fine geographic scale. This study applies a spatial microsimulation procedure to generate small-area (lower super outputs areas [LSOA]) estimates of psychological distress and alcohol consumption. The validity of LSOA estimates and their associations with proximal and broader socioeconomic conditions are examined.

METHODS

A deterministic reweighting methodology assigns prevalence estimates for psychological distress and heavy alcohol consumption through a process of matching individuals from a large, population-representative dataset (Health Survey for England) to known LSOA populations (from the 2001 population Census). 'goodness-of-fit' of LSOA estimates is assessed by their comparison to observed prevalence of these health indicators at higher levels of aggregation (local authority districts [LAD]). Population prevalence estimates are correlated to the mental health needs index (MINI) and other health indicators; ordered logistic regression is applied to investigate their associations with proximal and broader socioeconomic conditions.

RESULTS

Performance of microsimulation models is high with no more than 10% errors in at least 90% of LAD for psychological distress and moderate and heavy alcohol consumption. The MINI is strongly correlated with psychological distress (r = 0.910; p value < 0.001) and moderately with heavy drinking (r = 0.389; p value < 0.001). Psychological distress and heavy alcohol consumption are differently associated with socioeconomic and rurality indicators at the LSOA level. Associations further vary at the LAD level and regional variations are apparent.

CONCLUSION

Spatial microsimulation may be an appropriate methodological approach for replicating social and demographic health patterns at the local level.

Identifying socio-demographic and socioeconomic determinants of health inequalities in a diverse London community: the South East London Community Health (SELCoH) study

Background

Responses to public health need require information on the distribution of mental and physical ill health by demographic and socioeconomic factors at the local community level.

Methods

The South East London Community Health (SELCoH) study is a community psychiatric and physical morbidity survey. Trained interviewers conducted face-to-face computer assisted interviews with 1698 adults aged 16 years and over, from 1076 randomly selected private households in two south London boroughs. We compared the prevalence of common mental disorders, hazardous alcohol use, long standing illness and general physical health by demographic and socioeconomic indicators. Unadjusted and models adjusted for demographic and socioeconomic indicators are presented for all logistic regression models.

Results

Of those in the sample, 24.2% reported common mental disorder and 44.9% reported having a long standing illness, with 15.7% reporting hazardous alcohol consumption and 19.2% rating their health as fair or poor. The pattern of indicators identifying health inequalities for common mental disorder, poor general health and having a long term illness is similar; individuals who are socioeconomically disadvantaged have poorer health and physical health worsens as age increases for all groups. The prevalence of poor health outcomes by ethnic group suggests that there are important differences between groups, particularly for common mental disorder and poor general health. Higher socioeconomic status was protective for common mental disorder, fair or poor health and long standing illness, but those with higher socioeconomic status reported higher levels of hazardous alcohol use. The proportion of participants who met the criteria for common mental disorder with co-occurring functional limitations was similar or greater to those with poor physical health.

Conclusions

Health service providers and policy makers should prioritise high risk, socially defined groups in combating inequalities in individual and co-occurring poor mental and physical problems. In population terms, poor mental health has a similar or greater burden on functional impairment than long term conditions and perceived health.

Detecting referral and selection bias by the anonymous linkage of practice, hospital and clinic data using Secure and Private Record Linkage (SAPREL): case study from the evaluation of the Improved Access to Psychological Therapy (IAPT) service

Background

The evaluation of demonstration sites set up to provide improved access to psychological therapies (IAPT) comprised the study of all people identified as having common mental health problems (CMHP), those referred to the IAPT service, and a sample of attenders studied in-depth. Information technology makes it feasible to link practice, hospital and IAPT clinic data to evaluate the representativeness of these samples. However, researchers do not have permission to browse and link these data without the patients' consent.

Objective

To demonstrate the use of a mixed deterministic-probabilistic method of secure and private record linkage (SAPREL) - to describe selection bias in subjects chosen for in-depth evaluation.

Method

We extracted, pseudonymised and used fuzzy logic to link multiple health records without the researcher knowing the patient's identity. The method can be characterised as a three party protocol mainly using deterministic algorithms with dynamic linking strategies; though incorporating some elements of probabilistic linkage. Within the data providers' safe haven we extracted: Demographic data, hospital utilisation and IAPT clinic data; converted post code to index of multiple deprivation (IMD); and identified people with CMHP. We contrasted the age, gender, ethnicity and IMD for the in-depth evaluation sample with people referred to IAPT, use hospital services, and the population as a whole.

Results

The in IAPT-in-depth group had a mean age of 43.1 years; CI: 41.0 - 45.2 (n = 166); the IAPT-referred 40.2 years; CI: 39.4 - 40.9 (n = 1118); and those with CMHP 43.6 years SEM 0.15. (n = 12210). Whilst around 67% of those with a CMHP were women, compared to 70% of those referred to IAPT, and 75% of those subject to in-depth evaluation (Chi square p < 0.001). The mean IMD score for the in-depth evaluation group was 36.6; CI: 34.2 - 38.9; (n = 166); of those referred to IAPT 38.7; CI: 37.9 - 39.6; (n = 1117); and of people with CMHP 37.6; CI 37.3-37.9; (n = 12143).

Conclusions

The sample studied in-depth were older, more likely female, and less deprived than people with CMHP, and fewer had recorded ethnic minority status. Anonymous linkage using SAPREL provides insight into the representativeness of a study population and possible adjustment for selection bias.

Socio-economic status and geographies of psychiatric inpatient service use. Places, provision, power and wellbeing

This editorial briefly summarises some aspects of research on socio-economic status and use of mental health services that have particular relevance for the theme of this issue of Epidemiologia e Psichiatria Sociale. This discussion takes a view from the perspective of health geography, which examines how the relationships between individuals and their social and physical environment result in variations in health and health care use. Three particular issues are considered here. First, the geographical distribution and organisation of psychiatric services may interact with social and economic factors in ways that are important for service use. Second, increasingly sophisticated ecological modelling strategies have elucidated the associations between socio-economic factors and service use at the population level. Third, more intensive, qualitative research complements these statistical analyses and encouraged reflection on the socio-economic processes, within psychiatric care settings, as well as in wider society, which influence service use.

Outcomes of referrals over a six-month period to a mental health gateway team

Mental health policy in recent years has prescribed the role, function and form for services in England. Evidence of their effectiveness post-policy implementation has been limited to date and minimal guidance has been available on how services should operate together as whole systems. This paper reports findings from a study of referrals and their outcomes in respect of specialist community mental health services following implementation of national policy and its interpretation and configuration at a local level. Findings highlight that gateway workers configured as a team operating between primary and secondary care can effectively shield community mental health teams from high numbers of referrals that they would deem inappropriate. The study also identified the triage role of this service as being crucial to the effectiveness of developing and maintaining care pathways and also in potentially supporting the mental health capability of primary care.

Associations between common mental disorders and the Mental Illness Needs Index in community settings. Multilevel analysis

BACKGROUND

The relationship between the Mental Illness Needs Index (MINI) and the common mental disorders is not known.

AIMS

To investigate associations between the small-area MINI score and common mental disorder at individual level.

METHOD

Mental health status was measured using the Mental Health Inventory of the Short Form 36 instrument (SF-36). Data from the Caerphilly Health and Social Needs population survey were analysed in multilevel models of 10 653 individuals aged 18-74 years nested within the 2001 UK census geographies of 110 lower super output areas and 33 wards.

RESULTS

The MINI score was significantly associated with common mental disorder after adjusting for individual risk factors. This association was stronger at the smaller spatial scale of the lower super output area and for individuals who were permanently sick or disabled.

CONCLUSIONS

The MINI is potentially useful for small-area needs assessment and service planning for common mental disorder in community settings.

The bed requirement inventory: a simple measure to estimate the need for a psychiatric bed

OBJECTIVE

To develop an assessment of bed need that was as little affected by personal bias as possible.

METHOD

The Bed Requirement Inventory (BRI) is an eight-point scale designed to identify the appropriate use of an acute psychiatric bed. This is completed by a member of the ward staff, usually a nurse, and takes 5 minutes to fill in. The reliability, validity and feasibility of using the scale in normal practice were tested in a one-year study, and variations in inappropriate bed use described.

RESULTS

The inter-rater reliability of the scale was good (intra-class correlation coefficient = 0.63) and a comparison of the need for a psychiatric bed (comparing the BRI score with the judgement of an independent multidisciplinary group of professionals) also showed good agreement (k = 0.69), suggesting reasonable validity (although when the assessment was made by the named nurse agreement was less good). Results from a year-long survey in two West London hospitals showed that 17% of admissions were inappropriate and 32% had delayed discharge, black Caribbean patients had a significantly higher proportion (25%) of inappropriate admission than others (11%) and those referred from housing charities and hostels had a higher proportion (50%) of inappropriate bed use at some time than other groups (33%).

CONCLUSIONS

The Bed Requirement Inventory is a quick and reliable method of determining the appropriate use of a psychiatric bed and could be of use in estimating local bed needs. Delayed discharge remains a serious reason for inappropriate bed use in London.

Access to mental health supports in England: crisis resolution teams and day services

Access to health care is a complex issue with multiple supply and demand side facets. Here just two issues are explored; the potential for access through availability and the actual access made as indicated by utilisation rates. These perspectives are explored for two mental health services, crisis resolution teams and day hospitals, both of which are recommended components for a comprehensive local mental health care service in England. The geographical spread of these services is considered alongside the level of provision and the extent of their use. Associations between availability and needs, and between use and needs are tested. Tracking resources from funding allocations to provision is also complex and issues around resource allocation are discussed.