Association between depression diagnosis and educational attainment trajectories: an historical cohort study using linked data.

BACKGROUND: Depression symptoms are thought to be associated with lower educational attainment, but patterns of change in attainment among those who receive a clinical diagnosis of depression at any point during childhood and adolescence remain unclear. METHODS: We conducted a secondary analysis of an existing data linkage between a national educational dataset (National Pupil Database) and pseudonymised electronic health records (Clinical Record Interactive Search) from a large mental healthcare provider in London, United Kingdom (2007 to 2013). A cohort of 222,027 pupils were included. We used Growth Mixture Modelling (GMM) and stakeholder input to estimate trajectories of standardised educational attainment over School Years 2, 6 and 11. Multinomial logistic regression analyses were then used to investigate the association between resulting educational attainment trajectory membership (outcome) and depression diagnosis any time before age 18 (exposure). RESULTS: A five-trajectory GMM solution for attainment was derived: (1) average/high-stable, (2) average-modest declining, (3) average-steep declining, (4) low-improving and (5) low-stable. After adjusting for clinical and sociodemographic covariates, having a depression diagnosis before age 18 was associated with occupying the average-modest declining trajectory (RRR = 2.80, 95% CI 2.36-3.32, p < .001) or the average-steep declining trajectory (RRR = 3.54, 95% CI 3.10-4.04, p < .001), as compared to the average/high-stable trajectory. CONCLUSIONS: Receiving a diagnosis of depression before age 18 was associated with a relative decline in attainment throughout school. While these findings cannot support a causal direction, they nonetheless suggest a need for timely mental health and educational support among pupils struggling with depression.

Autism spectrum disorders as a risk factor for adolescent self-harm: a retrospective cohort study of 113,286 young people in the UK.

BACKGROUND: Individuals with autism spectrum disorder (ASD) are at particularly high risk of suicide and suicide attempts. Presentation to a hospital with self-harm is one of the strongest risk factors for later suicide. We describe the use of a novel data linkage between routinely collected education data and child and adolescent mental health data to examine whether adolescents with ASD are at higher risk than the general population of presenting to emergency care with self-harm. METHODS: A retrospective cohort study was conducted on the population aged 11-17 resident in four South London boroughs between January 2009 and March 2013, attending state secondary schools, identified in the National Pupil Database (NPD). Exposure data on ASD status were derived from the NPD. We used Cox regression to model time to first self-harm presentation to the Emergency Department (ED). RESULTS: One thousand twenty adolescents presented to the ED with self-harm, and 763 matched to the NPD. The sample for analysis included 113,286 adolescents (2.2% with ASD). For boys only, there was an increased risk of self-harm associated with ASD (adjusted hazard ratio 2·79, 95% CI 1·40-5·57, P<0·01). Several other factors including school absence, exclusion from school and having been in foster care were also associated with a higher risk of self-harm. CONCLUSIONS: This study provides evidence that ASD in boys, and other educational, social and clinical factors, are risk factors for emergency presentation with self-harm in adolescents. These findings are an important step in developing early recognition and prevention programmes.

Clinical Neuroimaging Findings in Catatonia: Neuroradiological Reports of MRI Scans of Psychiatric Inpatients With and Without Catatonia.

OBJECTIVE: Catatonia is a debilitating psychomotor disorder. Previous neuroimaging studies have used small samples with inconsistent results. The authors aimed to describe the structural neuroradiological abnormalities in clinical magnetic resonance imaging (MRI) brain scans of patients with catatonia, comparing them with scans of psychiatric inpatients without catatonia. They report the largest study of catatonia neuroimaging to date. METHODS: In this retrospective case-control study, neuroradiological reports of psychiatric inpatients who had undergone MRI brain scans for clinical reasons were examined. Abnormalities were classified by lateralization, localization, and pathology. The primary analysis was prediction of catatonia by presence of an abnormal MRI scan, adjusted for age, sex, Black race-ethnicity, and psychiatric diagnosis. RESULTS: Scan reports from 79 patients with catatonia and 711 other psychiatric inpatients were obtained. Mean age was 36.4 (SD=17.3) for the cases and 44.5 (SD=19.9) for the comparison group. Radiological abnormalities were reported in 27 of 79 cases (34.2%) and in 338 of 711 in the comparison group (47.5%) (odds ratio [OR]=0.57, 95% confidence interval [CI]=0.35, 0.93; adjusted OR=1.11, 95% CI=0.58, 2.14). Among the cases, most abnormal scans had bilateral abnormalities (N=23, 29.1%) and involved the forebrain (N=25, 31.6%) and atrophy (N=17, 21.5%). CONCLUSIONS: Patients with catatonia were commonly reported to have brain MRI abnormalities, which largely consisted of diffuse cerebral atrophy rather than focal lesions. No evidence was found that these abnormalities were more common than in other psychiatric inpatients undergoing neuroimaging, after adjustment for demographic variables. Study limitations included a heterogeneous control group and selection bias in requesting scans.

Predictors of Mental Health Review Tribunal (MHRT) outcome in a forensic inpatient population: a prospective cohort study.

BACKGROUND: Previous studies have investigated factors associated with outcome at Mental Health Review Tribunals (MHRTs) in forensic psychiatric patients; however, dynamic variables such as treatment compliance and substance misuse have scarcely been examined, particularly in UK samples. We aimed to determine whether dynamic factors related to behaviour, cooperation with treatment, and activities on the ward were prospectively associated with outcome at MHRT. METHODS: At baseline, demographic, clinical, behavioural, and treatment-related factors were ascertained via electronic medical records and census forms completed by the patient's clinical team. Data on MHRTs (i.e., number attended, responsible clinician's recommendation, and outcome) were collected at a 2-year follow-up. Logistic regression analyses were performed to determine factors associated with outcome among those who attended a MHRT within the follow-up period. Of the 135 forensic inpatients examined at baseline, 79 patients (59%) attended a MHRT during the 2-year follow-up period and therefore comprised the study sample. Of these 79 patients included in the current study, 28 (35%) were subsequently discharged. RESULTS: In univariable analyses, unescorted community leave, responsible clinician's recommendation of discharge, and restricted Mental Health Act section were associated with a greater likelihood of discharge at MHRT; whilst inpatient aggression, a recent episode of acute illness, higher total score on the Historical Clinical Risk - 20 (HCR-20), higher HCR-20 clinical and risk scores, and agitated behaviour were negatively associated with discharge (p < 0.05). In multivariable analyses, HCR-20 clinical scale scores and physical violence independently predicted outcome at tribunal after controlling for other dynamic variables. CONCLUSION: By identifying dynamic factors associated with discharge at tribunal, the results have important implications for forensic psychiatric patients and their clinical teams. Our findings suggest that by reducing levels of agitated behaviour, verbal aggression, and physical violence on the ward, achieving unescorted community leave, and targeting specific items on the HCR-20 risk assessment tool, patients may be able to improve their changes of discharge at a MHRT.

Impact of inconsistent ethnicity recordings on estimates of inequality in child health and education data: a data linkage study of Child and Adolescent Mental Health Services in South London.

OBJECTIVES: Ethnicity data are critical for identifying inequalities, but previous studies suggest that ethnicity is not consistently recorded between different administrative datasets. With researchers increasingly leveraging cross-domain data linkages, we investigated the completeness and consistency of ethnicity data in two linked health and education datasets. DESIGN: Cohort study. SETTING: South London and Maudsley NHS Foundation Trust deidentified electronic health records, accessed via Clinical Record Interactive Search (CRIS) and the National Pupil Database (NPD) (2007-2013). PARTICIPANTS: N=30 426 children and adolescents referred to local Child and Adolescent Mental Health Services. PRIMARY AND SECONDARY OUTCOME MEASURES: Ethnicity data were compared between CRIS and the NPD. Associations between ethnicity as recorded from each source and key educational and clinical outcomes were explored with risk ratios. RESULTS: Ethnicity data were available for 79.3% from the NPD, 87.0% from CRIS, 97.3% from either source and 69.0% from both sources. Among those who had ethnicity data from both, the two data sources agreed on 87.0% of aggregate ethnicity categorisations overall, but with high levels of disagreement in Mixed and Other ethnic groups. Strengths of associations between ethnicity, educational attainment and neurodevelopmental disorder varied according to which data source was used to code ethnicity. For example, as compared with White pupils, a significantly higher proportion of Asian pupils achieved expected educational attainment thresholds only if ethnicity was coded from the NPD (RR=1.46, 95% CI 1.29 to 1.64), not if ethnicity was coded from CRIS (RR=1.11, 0.98 to 1.26). CONCLUSIONS: Data linkage has the potential to minimise missing ethnicity data, and overlap in ethnicity categorisations between CRIS and the NPD was generally high. However, choosing which data source to primarily code ethnicity from can have implications for analyses of ethnicity, mental health and educational outcomes. Users of linked data should exercise caution in combining and comparing ethnicity between different data sources.

Improving our understanding of the social determinants of mental health: a data linkage study of mental health records and the 2011 UK census.

OBJECTIVES: To address the lack of individual-level socioeconomic information in electronic healthcare records, we linked the 2011 census of England and Wales to patient records from a large mental healthcare provider. This paper describes the linkage process and methods for mitigating bias due to non-matching. SETTING: South London and Maudsley NHS Foundation Trust (SLaM), a mental healthcare provider in Southeast London. DESIGN: Clinical records from SLaM were supplied to the Office of National Statistics for linkage to the census through a deterministic matching algorithm. We examined clinical (International Classification of Disease-10 diagnosis, history of hospitalisation, frequency of service contact) and socio-demographic (age, gender, ethnicity, deprivation) information recorded in Clinical Record Interactive Search (CRIS) as predictors of linkage success with the 2011 census. To assess and adjust for potential biases caused by non-matching, we evaluated inverse probability weighting for mortality associations. PARTICIPANTS: Individuals of all ages in contact with SLaM up until December 2019 (N=459 374). OUTCOME MEASURES: Likelihood of mental health records' linkage to census. RESULTS: 220 864 (50.4%) records from CRIS linked to the 2011 census. Young adults (prevalence ratio (PR) 0.80, 95% CI 0.80 to 0.81), individuals living in more deprived areas (PR 0.78, 95% CI 0.78 to 0.79) and minority ethnic groups (eg, Black African, PR 0.67, 0.66 to 0.68) were less likely to match to census. After implementing inverse probability weighting, we observed little change in the strength of association between clinical/demographic characteristics and mortality (eg, presence of any psychiatric disorder: unweighted PR 2.66, 95% CI 2.52 to 2.80; weighted PR 2.70, 95% CI 2.56 to 2.84). CONCLUSIONS: Lower response rates to the 2011 census among people with psychiatric disorders may have contributed to lower match rates, a potential concern as the census informs service planning and allocation of resources. Due to its size and unique characteristics, the linked data set will enable novel investigations into the relationship between socioeconomic factors and psychiatric disorders.

Linking electronic mental healthcare and benefits records in South London: design, procedure and descriptive outcomes.

OBJECTIVES: To describe the process and outcomes of a data linkage between electronic secondary mental healthcare records from the South London and Maudsley (SLaM) NHS Foundation Trust with benefits records from the Department for Work and Pensions (DWP). We also describe the mental health and benefit profile of patients who were successfully linked. DESIGN: A deterministic linkage of routine records from health and welfare government service providers within a secure environment. SETTING AND PARTICIPANTS: Adults aged≥18 years who were referred to or accessed treatment at SLaM services between January 2007 and June 2019, including those who were treated as part of Improving Access to Psychological Therapies (IAPT) services between January 2008 and June 2019 (n=448 404). Benefits data from the DWP from January 2005 to June 2020. OUTCOME MEASURES: The linkage rate and associated sociodemographic, diagnostic and treatment factors. Recorded primary psychiatric diagnosis based on International Classification of Diseases (ICD)-10 codes and type of benefit receipt. RESULTS: A linkage rate of 92.3% was achieved. Women, younger patients and those from ethnic minority groups were less likely to be successfully linked. Patients who had subsequently died, had a recorded primary psychiatric diagnosis, had also engaged with IAPT and had a higher number of historical postcodes available were more likely to be linked. Overall, 83% of patients received benefits at some point between 2005 and 2020. Benefit receipt across the psychiatric diagnosis spectrum was high, over 80% across most ICD-10 codes. CONCLUSIONS: This data linkage is the first of its kind in the UK demonstrating the use of routinely collected mental health and benefits data. Benefit receipt was high among patients accessing SLaM services and varied by psychiatric diagnosis. Future areas of research are discussed, including exploring the effectiveness of interventions for helping people into work and the impact of benefit reforms.

Prevalence of HIV in mental health service users: a retrospective cohort study.

OBJECTIVE: To examine the prevalence of HIV in a cohort of people who have used secondary mental health services in the UK. DESIGN: Retrospective cohort study. SETTING: Routinely collected clinical data from secondary mental health services in South London, UK available for research through the Clinical Record Interactive Search tool at the National Institute for Health and Care Research Maudsley Biomedical Research Centre were matched with pseudonymised national HIV surveillance data held by the UK Health Security Agency using a deterministic matching algorithm. PARTICIPANTS: All adults aged 16+ who presented for the first time to mental health services in the South London and Maudsley (SLaM) National Health Service Trust between 1 January 2007 and 31 December 2018 were included. PRIMARY OUTCOME: Point prevalence of HIV. RESULTS: There were 181 177 people who had contact with mental health services for the first time between 2007 and 2018 in SLaM. Overall, 2.47% (n=4481) of those had a recorded HIV diagnosis in national HIV surveillance data at any time (before, during or after contact with mental health services), 24.73 people per 1000. HIV point prevalence was highest in people with a diagnosed substance use disorder at 3.77% (n=784). A substantial percentage of the sample did not have a formal mental health diagnosis (27%), but even with those excluded, the point prevalence remained high at 2.31%. Around two-thirds of people had their diagnosis of HIV before contact with mental health services (67%; n=1495). CONCLUSIONS: The prevalence of HIV in people who have had contact with mental health services was approximately 2.5 times higher than the general population in the same geographical area. Future work should investigate risk factors and disparities in HIV outcomes between those with and without mental health service contact.

Ethnic inequalities in mental and physical multimorbidity in women of reproductive age: a data linkage cohort study.

OBJECTIVES: Explore inequalities in risk factors, mental and physical health morbidity in non-pregnant women of reproductive age in contact with mental health services and how these vary per ethnicity. DESIGN: Retrospective cohort study. SETTING: Data from Lambeth DataNet, anonymised primary care records of this ethnically diverse London borough, linked to anonymised electronic mental health records ('CRIS secondary care database'). PARTICIPANTS: Women aged 15-40 years with an episode of secondary mental health care between January 2008 and December 2018 and no antenatal or postnatal Read codes (n=3817) and a 4:1 age-matched comparison cohort (n=14 532). MAIN OUTCOME MEASURES: Preconception risk factors including low/high body mass index, smoking, alcohol, substance misuse, micronutrient deficiencies and physical diagnoses. RESULTS: Women in contact with mental health services (whether with or without severe mental illness (SMI)) had a higher prevalence of all risk factors and physical health diagnoses studied. Women from minority ethnic groups were less likely to be diagnosed with depression in primary care compared with white British women (adjusted OR 0.66 (0.55-0.79) p<0.001), and black women were more likely to have a SMI (adjusted OR 2.79 (2.13-3.64) p<0.001). Black and Asian women were less likely to smoke or misuse substances and more likely to be vitamin D deficient. Black women were significantly more likely to be overweight (adjusted OR 3.47 (3.00-4.01) p<0.001), be diagnosed with hypertension (adjusted OR 3.95 (2.67-5.85) p<0.00) and have two or more physical health conditions (adj OR 1.94 (1.41-2.68) p<0.001) than white British women. CONCLUSIONS: Our results challenge the perspective that regular monitoring of physical health in primary care should be exclusively encouraged in people with a l diagnosis. The striking differences in multimorbidity for women in contact with mental health services and those of ethnic minority groups emphasise a need of integrative models of care.

Brain-age is associated with progression to dementia in memory clinic patients.

BACKGROUND: Biomarkers for the early detection of dementia risk hold promise for better disease monitoring and targeted interventions. However, most biomarker studies, particularly in neuroimaging, have analysed artificially 'clean' research groups, free from comorbidities, erroneous referrals, contraindications and from a narrow sociodemographic pool. Such biases mean that neuroimaging samples are often unrepresentative of the target population for dementia risk (e.g., people referred to a memory clinic), limiting the generalisation of these studies to real-world clinical settings. To facilitate better translation from research to the clinic, datasets that are more representative of dementia patient groups are warranted. METHODS: We analysed T1-weighted MRI scans from a real-world setting of patients referred to UK memory clinic services (n = 1140; 60.2 % female and mean [SD] age of 70.0[10.8] years) to derive 'brain-age'. Brain-age is an index of age-related brain health based on quantitative analysis of structural neuroimaging, largely reflecting brain atrophy. Brain-predicted age difference (brain-PAD) was calculated as brain-age minus chronological age. We determined which patients went on to develop dementia between three months and 7.8 years after neuroimaging assessment (n = 476) using linkage to electronic health records. RESULTS: Survival analysis, using Cox regression, indicated a 3 % increased risk of dementia per brain-PAD year (hazard ratio [95 % CI] = 1.03 [1.02,1.04], p < 0.0001), adjusted for baseline age, age2, sex, Mini Mental State Examination (MMSE) score and normalised brain volume. In sensitivity analyses, brain-PAD remained significant when time-to-dementia was at least 3 years (hazard ratio [95 % CI] = 1.06 [1.02, 1.09], p = 0.0006), or when baseline MMSE score ≥ 27 (hazard ratio [95 % CI] = 1.03 [1.01, 1.05], p = 0.0006). CONCLUSIONS: Memory clinic patients with older-appearing brains are more likely to receive a subsequent dementia diagnosis. Potentially, brain-age could aid decision-making during initial memory clinic assessment to improve early detection of dementia. Even when neuroimaging assessment was more than 3 years prior to diagnosis and when cognitive functioning was not clearly impaired, brain-age still proved informative. These real-world results support the use of quantitative neuroimaging biomarkers like brain-age in memory clinics.

Impact of matching error on linked mortality outcome in a data linkage of secondary mental health data with Hospital Episode Statistics (HES) and mortality records in South East London: a cross-sectional study.

OBJECTIVES: Linkage of electronic health records (EHRs) to Hospital Episode Statistics (HES)-Office for National Statistics (ONS) mortality data has provided compelling evidence for lower life expectancy in people with severe mental illness. However, linkage error may underestimate these estimates. Using a clinical sample (n=265 300) of individuals accessing mental health services, we examined potential biases introduced through missed matching and examined the impact on the association between clinical disorders and mortality. SETTING: The South London and Maudsley NHS Foundation Trust (SLaM) is a secondary mental healthcare provider in London. A deidentified version of SLaM's EHR was available via the Clinical Record Interactive Search system linked to HES-ONS mortality records. PARTICIPANTS: Records from SLaM for patients active between January 2006 and December 2016. OUTCOME MEASURES: Two sources of death data were available for SLaM participants: accurate and contemporaneous date of death via local batch tracing (gold standard) and date of death via linked HES-ONS mortality data. The effect of linkage error on mortality estimates was evaluated by comparing sociodemographic and clinical risk factor analyses using gold standard death data against HES-ONS mortality records. RESULTS: Of the total sample, 93.74% were successfully matched to HES-ONS records. We found a number of statistically significant administrative, sociodemographic and clinical differences between matched and unmatched records. Of note, schizophrenia diagnosis showed a significant association with higher mortality using gold standard data (OR 1.08; 95% CI 1.01 to 1.15; p=0.02) but not in HES-ONS data (OR 1.05; 95% CI 0.98 to 1.13; p=0.16). Otherwise, little change was found in the strength of associated risk factors and mortality after accounting for missed matching bias. CONCLUSIONS: Despite significant clinical and sociodemographic differences between matched and unmatched records, changes in mortality estimates were minimal. However, researchers and policy analysts using HES-ONS linked resources should be aware that administrative linkage processes can introduce error.

Guidance for researchers wanting to link NHS data using non-consent approaches: a thematic analysis of feedback from the Health Research Authority Confidentiality Advisory Group.

INTRODUCTION: The use of linked data and non-consent methodologies is a rapidly growing area of health research due to the increasing detail, availability and scope of routinely collected electronic health records data. However, gaining the necessary legal and governance approvals to undertake data linkage is a complex process in England. OBJECTIVES: We reflect on our own experience of establishing lawful basis for data linkage through Section 251 approval, with the intention to build a knowledgebase of practical advice for future applicants. METHODS: Thematic analysis was conducted on a corpus of Section 251 feedback reports from the NHS Health Research Authority Confidentiality Advisory Group. RESULTS: Four themes emerged from the feedback. These were: (a) Patient and Public Involvement, (b) Establishing Rationale, (c) Data maintenance and contingency, and the need to gain (d) Further Permissions from external authorities prior to full approval. CONCLUSIONS: Securing Section 251 approval poses ethical, practical and governance challenges. However, through a comprehensive, planned approach Section 251 approval is possible, enabling researchers to unlock the potential of linked data for the purposes of health research.

Incidence and treatment costs of severe bacterial infections among people who inject heroin: A cohort study in South London, England.

BACKGROUND: People who inject drugs often get bacterial infections. Few longitudinal studies have reported the incidence and treatment costs of these infections. METHODS: For a cohort of 2335 people who inject heroin entering treatment for drug dependence between 2006 and 2017 in London, England, we reported the rates of hospitalisation or death with primary causes of cutaneous abscess, cellulitis, phlebitis, septicaemia, osteomyelitis, septic arthritis, endocarditis, or necrotising fasciitis. We compared these rates to the general population. We also used NHS reference costs to calculate the cost of admissions. RESULTS: During a median of 8.0 years of follow-up, 24 % of patients (570/2335) had a severe bacterial infection, most commonly presenting with cutaneous abscesses or cellulitis. Bacterial infections accounted for 13 % of all hospital admissions. The rate was 73 per 1000 person-years (95 % CI 69-77); 50 times the general population, and the rate remained high throughout follow-up. The rate of severe bacterial infections for women was 1.50 (95 % CI 1.32-1.69) times the rate for men. The mean cost per admission was £4980, and we estimate that the annual cost of hospital treatment for people who inject heroin in London is £4.5 million. CONCLUSIONS: People who inject heroin have extreme and long-term risk of severe bacterial infections.

Cohort profile: the eLIXIR Partnership-a maternity-child data linkage for life course research in South London, UK.

PURPOSE: Linked maternity, neonatal and maternal mental health records were created to support research into the early life origins of physical and mental health, in mothers and children. The Early Life Cross Linkage in Research (eLIXIR) Partnership was developed in 2018, generating a repository of real-time, pseudonymised, structured data derived from the electronic health record systems of two acute and one Mental Health Care National Health Service (NHS) Provider in South London. We present early descriptive data for the linkage database and the robust data security and governance structures, and describe the intended expansion of the database from its original development. Additionally, we report details of the accompanying eLIXIR Research Tissue Bank of maternal and neonatal blood samples. PARTICIPANTS: Descriptive data were generated from the eLIXIR database from 1 October 2018 to 30 June 2019. Over 17 000 electronic patient records were included. FINDINGS TO DATE: 10 207 women accessed antenatal care from the 2 NHS maternity services, with 8405 deliveries (8772 infants). This diverse, inner-city maternity service population was born in over 170 countries with an ethnic profile of 46.1% white, 19.1% black, 7.0% Asian, 4.1% mixed and 4.1% other. Of the 10 207 women, 11.6% had a clinical record in mental health services with 3.0% being treated during their pregnancy. This first data extract included 947 infants treated in the neonatal intensive care unit, of whom 19.1% were postnatal transfers from external healthcare providers. FUTURE PLANS: Electronic health records provide potentially transformative information for life course research, integrating physical and mental health disorders and outcomes in routine clinical care. The eLIXIR database will grow by ~14 000 new maternity cases annually, in addition to providing child follow-up data. Additional datasets will supplement the current linkage from other local and national resources, including primary care and hospital inpatient data for mothers and their children.

The Maudsley Biomedical Research Centre (BRC) data linkage service user and carer advisory group: creating and sustaining a successful patient and public involvement group to guide research in a complex area.

BACKGROUND: Patient and Public Involvement (PPI) in health and social care research has been shown to improve the quality and relevance of research. PPI in data linkage research is important in ensuring the legitimacy of future health informatics initiatives, but remains sparse and under-developed. This article describes the setting up and evaluation of a service user and carer advisory group with the aim of providing feedback and advice to researchers developing or making use of database linkages in the field of mental health. AIM: The aim of this study is to describe the creation and formative evaluation of the service user and carer advisory group after a trial period of 12 months. METHOD: Six individuals were recruited to the group all of whom had personal experience of mental illness. A formative evaluation was conducted after a trial period of 12 months. RESULTS: Evaluation revealed that the group succeeded in promoting dialogue between service users/carers and researchers. Factors that contributed to the success of the group's first year included the opportunity it provided for researchers to involve service users and carers in their projects, the training provided to group members, and the openness of researchers to receiving feedback from the group. CONCLUSION: The group encourages the incorporation of PPI in data linkage research which helps to ensure the legitimacy of data linkage practices and governance systems whilst also improving the quality and relevance of the research being conducted using linked data.

An approach to linking education, social care and electronic health records for children and young people in South London: a linkage study of child and adolescent mental health service data.

OBJECTIVES: Creation of linked mental health, social and education records for research to support evidence-based practice for regional mental health services. SETTING: The Clinical Record Interactive Search (CRIS) system was used to extract personal identifiers who accessed psychiatric services between September 2007 and August 2013. PARTICIPANTS: A clinical cohort of 35 509 children and young people (aged 4-17 years). DESIGN: Multiple government and ethical committees approved the link of clinical mental health service data to Department for Education (DfE) data on education and social care services. Under robust governance protocols, fuzzy and deterministic approaches were used by the DfE to match personal identifiers (names, date of birth and postcode) from National Pupil Database (NPD) and CRIS data sources. OUTCOME MEASURES: Risk factors for non-matching to NPD were identified, and the potential impact of non-match biases on International Statistical Classification of Diseases, 10th Revision (ICD-10) classifications of mental disorder, and persistent school absence (<80% attendance) were examined. Probability weighting and adjustment methods were explored as methods to mitigate the impact of non-match biases. RESULTS: Governance challenges included developing a research protocol for data linkage, which met the legislative requirements for both National Health Service and DfE. From CRIS, 29 278 (82.5%) were matched to NPD school attendance records. Presenting to services in late adolescence (adjusted OR (aOR) 0.67, 95% CI 0.59 to 0.75) or outside of school census timeframes (aOR 0.15, 95% CI 0.14 to 0.17) reduced likelihood of matching. After adjustments for linkage error, ICD-10 mental disorder remained significantly associated with persistent school absence (aOR 1.13, 95% CI 1.07 to 1.22). CONCLUSIONS: The work described sets a precedent for education data being used for medical benefit in England. Linkage between health and education records offers a powerful tool for evaluating the impact of mental health on school function, but biases due to linkage error may produce misleading results. Collaborative research with data providers is needed to develop linkage methods that minimise potential biases in analyses of linked data.

Predicting time to recall in patients conditionally released from a secure forensic hospital: A survival analysis.

BACKGROUND: The recall of conditionally discharged forensic patients in England is a formal order from the Ministry of Justice under the Mental Health Act (1983) which has the power to revoke conditional release and direct readmission to hospital. Recall has significant implications for the individual and for hospital services, but despite this, little is known about predictors of recall for forensic patients. METHODS: We examined the rate of recall for 101 patients conditionally discharged from medium secure forensic inpatient services between 2007 and 2013. Demographic, clinical, and forensic factors were examined as possible predictors of time to recall using Cox regression survival techniques. RESULTS: Conditionally discharged patients were followed for an average of 811 days, during which 45 (44.5%) were recalled to hospital. Younger age (HR 1.89; 95% CI 1.02-3.49; p = 0.04), non-white ethnicity (HR 3.44; 95% CI 1.45-8.13), substance abuse history (HR 2.52; 95% CI 1.17-5.43), early violence (HR 1.90; 95% CI 1.03-3.50), early childhood maladjustment (HR 1.92; 95% CI 1.01-3.68), treatment with a depot medication (HR 2.17; 95% CI 1.14-4.11), being known to mental health services (HR 3.44; 95% CI 1.06-11.16), and a psychiatric admission prior to the index admission (HR 2.44; 95% CI 1.08-5.52) were significantly associated with a shorter time to recall. Treatment with clozapine reduced the risk of recall to hospital (HR 0.40; 95% CI 0.20-0.79). CONCLUSIONS: Time to recall can be predicted by a range of factors that are readily available to clinical teams. Further research is required to determine if targeted interventions can modify the likelihood or time to recall for conditionally released forensic patients.

Using data linkage to electronic patient records to assess the validity of selected mental health diagnoses in English Hospital Episode Statistics (HES).

BACKGROUND: Administrative data can be used to support research, such as in the UK Biobank. Hospital Episode Statistics (HES) are national data for England that include contain ICD-10 diagnoses for inpatient mental healthcare episodes, but the validity of these diagnoses for research purposes has not been assessed. METHODS: 250 peoples' HES records were selected based on a HES recorded inpatient stay at the South London and Maudsley NHS Foundation Trust with a diagnosis of schizophrenia, a wider schizophrenia spectrum disorder, bipolar affective disorder or unipolar depression. A gold-standard research diagnosis was made using Clinical Records Interactive Search pseudonymised electronic patient records using, and the OPCRIT+ algorithm. RESULTS: Positive predictive value at the level of lifetime psychiatric disorder was 100%, and at the level of lifetime diagnosis in the four categories of schizophrenia, wider schizophrenia spectrum, bipolar or unipolar depression was 73% (68-79). Agreement varied by diagnosis, with schizophrenia having the highest PPV at 90% (80-96). Each person had an average of five psychiatric HES records. An algorithm that looked at the last recorded psychiatric diagnosis led to greatest overall agreement with the research diagnosis. DISCUSSION: For people who have a HES record from a psychiatric admission with a diagnosis of schizophrenia spectrum disorder, bipolar affective disorder or unipolar depression, HES records appear to be a good indicator of a mental disorder, and can provide a diagnostic category with reasonable certainty. For these diagnoses, HES records can be an effective way of ascertaining psychiatric diagnosis.

Cohort profile of the South London and Maudsley NHS Foundation Trust Biomedical Research Centre (SLaM BRC) Case Register: current status and recent enhancement of an Electronic Mental Health Record-derived data resource.

PURPOSE: The South London and Maudsley National Health Service (NHS) Foundation Trust Biomedical Research Centre (SLaM BRC) Case Register and its Clinical Record Interactive Search (CRIS) application were developed in 2008, generating a research repository of real-time, anonymised, structured and open-text data derived from the electronic health record system used by SLaM, a large mental healthcare provider in southeast London. In this paper, we update this register's descriptive data, and describe the substantial expansion and extension of the data resource since its original development. PARTICIPANTS: Descriptive data were generated from the SLaM BRC Case Register on 31 December 2014. Currently, there are over 250,000 patient records accessed through CRIS. FINDINGS TO DATE: Since 2008, the most significant developments in the SLaM BRC Case Register have been the introduction of natural language processing to extract structured data from open-text fields, linkages to external sources of data, and the addition of a parallel relational database (Structured Query Language) output. Natural language processing applications to date have brought in new and hitherto inaccessible data on cognitive function, education, social care receipt, smoking, diagnostic statements and pharmacotherapy. In addition, through external data linkages, large volumes of supplementary information have been accessed on mortality, hospital attendances and cancer registrations. FUTURE PLANS: Coupled with robust data security and governance structures, electronic health records provide potentially transformative information on mental disorders and outcomes in routine clinical care. The SLaM BRC Case Register continues to grow as a database, with approximately 20,000 new cases added each year, in addition to extension of follow-up for existing cases. Data linkages and natural language processing present important opportunities to enhance this type of research resource further, achieving both volume and depth of data. However, research projects still need to be carefully tailored, so that they take into account the nature and quality of the source information.