Variations by ethnicity in referral and treatment pathways for IAPT service users in South London.

BACKGROUND: The Improving Access to Psychological Therapies (IAPT) programme aims to provide equitable access to therapy for common mental disorders. In the UK, inequalities by ethnicity exist in accessing and receiving mental health treatment. However, limited research examines IAPT pathways to understand whether and at which points such inequalities may arise. METHODS: This study examined variation by ethnicity in (i) source of referral to IAPT services, (ii) receipt of assessment session, (iii) receipt of at least one treatment session. Routine data were collected on service user characteristics, referral source, assessment and treatment receipt from 85 800 individuals referred to South London and Maudsley NHS Foundation Trust IAPT services between 1st January 2013 and 31st December 2016. Multinomial and logistic regression analysis was used to assess associations between ethnicity and referral source, assessment and treatment receipt. Missing ethnicity data (18.5%) were imputed using census data and reported alongside a complete case analysis. RESULTS: Compared to the White British group, Black African, Asian and Mixed ethnic groups were less likely to self-refer to IAPT services. Black Caribbean, Black Other and White Other groups are more likely to be referred through community services. Almost all racial and minority ethnic groups were less likely to receive an assessment compared to the White British group, and of those who were assessed, all racial and ethnic minority groups were less likely to be treated. CONCLUSIONS: Racial and ethnic minority service users appear to experience barriers to IAPT care at different pathway stages. Services should address potential cultural, practical and structural barriers.

Text mining occupations from the mental health electronic health record: a natural language processing approach using records from the Clinical Record Interactive Search (CRIS) platform in south London, UK.

OBJECTIVES: We set out to develop, evaluate and implement a novel application using natural language processing to text mine occupations from the free-text of psychiatric clinical notes. DESIGN: Development and validation of a natural language processing application using General Architecture for Text Engineering software to extract occupations from de-identified clinical records. SETTING AND PARTICIPANTS: Electronic health records from a large secondary mental healthcare provider in south London, accessed through the Clinical Record Interactive Search platform. The text mining application was run over the free-text fields in the electronic health records of 341 720 patients (all aged ≥16 years). OUTCOMES: Precision and recall estimates of the application performance; occupation retrieval using the application compared with structured fields; most common patient occupations; and analysis of key sociodemographic and clinical indicators for occupation recording. RESULTS: Using the structured fields alone, only 14% of patients had occupation recorded. By implementing the text mining application in addition to the structured fields, occupations were identified in 57% of patients. The application performed on gold-standard human-annotated clinical text at a precision level of 0.79 and recall level of 0.77. The most common patient occupations recorded were 'student' and 'unemployed'. Patients with more service contact were more likely to have an occupation recorded, as were patients of a male gender, older age and those living in areas of lower deprivation. CONCLUSION: This is the first time a natural language processing application has been used to successfully derive patient-level occupations from the free-text of electronic mental health records, performing with good levels of precision and recall, and applied at scale. This may be used to inform clinical studies relating to the broader social determinants of health using electronic health records.

Inequalities in referral pathways for young people accessing secondary mental health services in south east London.

Differences in health service use between ethnic groups have been well documented, but little research has been conducted on inequalities in access to mental health services among young people. This study examines inequalities in pathways into care by ethnicity and migration status in 12-29 years old accessing health services in south east London. This study analyses anonymized electronic patient record data for patients aged 12-29 referred to a south east London mental health trust between 2008 and 2016 for an anxiety or non-psychotic depressive disorder (n = 18,931). Multinomial regression was used to examine associations between ethnicity, migration status, and both referral source and destination, stratified by age group. Young people in the Black African ethnic group were more likely to be referred from secondary health or social/criminal justice services compared to those in the White British ethnic group; the effect was most pronounced for those aged 16-17 years. Young people in the Black African ethnic group were also significantly more likely to be referred to inpatient and emergency services compared to those in the White British ethnic group. Black individuals living in south east London, particularly those who identify as Black African, are referred to mental health services via more adverse pathways than White individuals. Our findings suggest that inequalities in referral destination may be perpetuated by inequalities generated at the point of access.

Barrier or stressor? The role of discrimination experiences in health service use.

BACKGROUND: Discrimination is a well-established stressor that is substantially associated with poor health and a known contributor to health inequalities. However, the role of discrimination in health service use is less explored. This study will take an intersectional approach to investigate differences in health service use and examine the role of discrimination experiences. METHODS: Data on health service use were assessed in a diverse inner London sample of 1052 participants in the South East London Community Health (SELCoH) Study. Latent class analysis (LCA) was used to define classes of intersectional social status using multiple indicators of socioeconomic status (SES), ethnicity and migration status. Adjusted associations between intersectional social status and discrimination experiences with health service use indicators are presented. RESULTS: Using latent class analysis allowed us to identify an intersectional social status characterized by multiple disadvantage that was associated with decreased secondary physical health service use and a class characterized by both privilege and disadvantage that was associated with increased health service use for mental disorder after controlling for age, gender and health status. Anticipated discrimination was also associated with increased service use for mental disorder in adjusted models. There was no evidence to suggest that discrimination experiences were acting as a barrier to health service use. CONCLUSIONS: This study highlights the complex ways in which discrimination experiences may increase the need for health services whilst also highlighting differences in health service use at the intersection of ethnicity, migration status and SES. Findings from this study illustrate the importance of measuring multiple levels of discrimination and taking an intersectional approach for health service use research.

Debt, common mental disorders and mental health service use.

BACKGROUND: Uncertainty remains as to whether the effects of debt on common mental disorder (CMD) are persistent over time and what impact it has on mental health service use (MHSU). AIMS: To determine the distribution of debt across sociodemographic and socioeconomic statuses; to examine whether debt influences CMD recovery over time; and to determine the effects of episodic and/or long-term debt and CMD on MHSU outcomes. METHODS: Data were collected from phase 1 (N = 1698) and phase 2 (N = 1052) of the South East London Community Health (SELCoH) study, a population-based survey. RESULTS: 37.2% of participants who reported debt at SELCoH 1 and 46.6% at SELCoH 2 experienced concurrent CMD. Those with concurrent exposure to debt and CMD at SELCoH 1 were at greater risk of CMD at SELCoH 2. Debt accumulation was strongly associated with CMD cross-sectionally; however, this somewhat dissipated over time. Reporting any debt at SELCoH 2 or debt at both time-points were strongly associated with MHSU in the past year in the fully adjusted model adjusting for prior mental health. CONCLUSIONS: More focus is needed on concurrent exposure to debt and CMD with regards to subsequent psychological impact and consequences for MHSU.

Challenges in researching migration status, health and health service use: an intersectional analysis of a South London community.

OBJECTIVES: This study aimed to investigate the associations between migration status and health-related outcomes and to examine whether and how the effect of migration status changes when it is disaggregated by length of residence, first language, reason for migration and combined with ethnicity. DESIGN: A total of 1698 adults were interviewed from 1076 randomly selected households in two South London boroughs. We described the socio-demographic and socio-economic differences between migrants and non-migrants and compared the prevalence of health-related outcomes by migration status, length of residence, first language, reason for migration and migration status within ethnic groups. Unadjusted models and models adjusted for socio-demographic and socio-economic indicators are presented. RESULTS: Migrants were disadvantaged in terms of socio-economic status but few differences were found between migrant and non-migrants regarding health or health service use indicators; migration status was associated with decreased hazardous alcohol use, functional limitations due to poor mental health and not being registered with a general practitioner. Important differences emerged when migration status was disaggregated by length of residence in the UK, first language, reason for migration and intersected with ethnicity. The association between migration status and functional limitations due to poor mental health was only seen in White migrants, migrants whose first language was not English and migrants who had moved to the UK for work or a better life or for asylum or political reasons. There was no association between migration status and self-rated health overall, but Black African migrants had decreased odds for reporting poor health compared to their non-migrant counterparts [odds ratio = 0.15 (0.05-0.48), p < 0.01]. CONCLUSIONS: Disaggregating migration status by length of residence, first language and reason for migration as well as intersecting it with ethnicity leads to better understanding of the effect migration status has on health and health service use.

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.