Universal Credit receipt among working-age patients who are accessing specialist mental health services: results from a novel data linkage study.

BACKGROUND: In 2013, Universal Credit (UC) was introduced by the UK Government. Understanding of how UC provision is allocated among people with mental disorders, and its intersection with protected characteristics is limited. This study aimed to explore (1) how UC receipt, including UC conditionality regime, varied among users of specialist mental health services between 2013 and 2019 and (2) associations between sociodemographic and diagnostic patient characteristics and UC receipt. METHODS: Working-age individuals who had accessed specialist mental health services were included if they had their mental health record data successfully linked with administrative benefits data. Associations between sociodemographic, diagnostic patient characteristics and UC receipt were explored using logistic regression models. RESULTS: Of the 143 715 patients, 26.9% had received UC between 2013 and 2019. Four in five patients were allocated to the searching for work conditionality regime during their time on UC. Females were less likely to have received UC (adjusted OR (AOR) 0.87, 95% CI 0.85 to 0.89) than males, and UC receipt decreased with age. Black patients (AOR 1.39, 95% CI 1.34 to 1.44) and patients from mixed and multiple ethnic backgrounds (AOR 1.27, 95% CI 1.18 to 1.38) had a higher likelihood of UC receipt than White patients. UC receipt was lower among patients diagnosed with severe mental illness compared with other psychiatric diagnoses (AOR 0.74, 95% CI 0.71 to 0.77). CONCLUSION: One in four specialist mental health service users had received UC and a large majority were subject to conditionality. The temporality of UC conditionality and mental health service presentation needs further exploration.

Health and well-being of serving and ex-serving UK Armed Forces personnel: protocol for the fourth phase of a longitudinal cohort study.

INTRODUCTION: This is the fourth phase of a longitudinal cohort study (2022-2023) to investigate the health and well-being of UK serving (Regulars and Reservists) and ex-serving personnel (veterans) who served during the era of the Iraq and Afghanistan conflicts. The cohort was established in 2003 and has collected data over three previous phases including Phase 1 (2004-2006), Phase 2 (2007-2009) and Phase 3 (2014-2016). METHODS AND ANALYSIS: Participants are eligible to take part if they completed the King's Centre for Military Health Research Health and Wellbeing Cohort Study at Phase 3 (2014-2016) and consented to be recontacted (N=7608). Participants will be recruited through email, post and text message to complete an online or paper questionnaire. Data are being collected between January 2022 and September 2023. Health and well-being measures include measures used in previous phases that assess common mental disorders, post-traumatic stress disorder (PTSD) and alcohol misuse. Other areas of interest assess employment, help-seeking and family relationships. New topics include the impact of the British withdrawal from Afghanistan in 2021, complex PTSD (C-PTSD), illicit drug use, gambling and loneliness. Analyses will describe the effect size between groups deployed to Iraq and/or Afghanistan or not deployed, and those who are currently in service versus ex-service personnel, respectively, reporting prevalences with 95% CIs, and ORs with 95% CI. Multivariable logistic and multiple linear regression analyses will be conducted to assess various health and well-being outcomes and associations with risk and protective factors. ETHICS AND DISSEMINATION: Ethical approval has been granted by the Ministry of Defence Research Ethics Committee (Ref: 2061/MODREC/21). Participants are provided with information and agree to a series of consent statements before taking part. Findings will be disseminated to UK Armed Forces stakeholders and international research institutions through stakeholder meetings, project reports and scientific publications.

Identifying Military Service Status in Electronic Healthcare Records from Psychiatric Secondary Healthcare Services: A Validation Exercise Using the Military Service Identification Tool.

Electronic healthcare records (EHRs) are a rich source of information with a range of uses in secondary research. In the United Kingdom, there is no pan-national or nationally accepted marker indicating veteran status across all healthcare services. This presents significant obstacles to determining the healthcare needs of veterans using EHRs. To address this issue, we developed the Military Service Identification Tool (MSIT), using an iterative two-staged approach. In the first stage, a Structured Query Language approach was developed to identify veterans using a keyword rule-based approach. This informed the second stage, which was the development of the MSIT using machine learning, which, when tested, obtained an accuracy of 0.97, a positive predictive value of 0.90, a sensitivity of 0.91, and a negative predictive value of 0.98. To further validate the performance of the MSIT, the present study sought to verify the accuracy of the EHRs that trained the MSIT models. To achieve this, we surveyed 902 patients of a local specialist mental healthcare service, with 146 (16.2%) being asked if they had or had not served in the Armed Forces. In total 112 (76.7%) reported that they had not served, and 34 (23.3%) reported that they had served in the Armed Forces (accuracy: 0.84, sensitivity: 0.82, specificity: 0.91). The MSIT has the potential to be used for identifying veterans in the UK from free-text clinical documents and future use should be explored.

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.

Military veterans and civilians' mental health diagnoses: an analysis of secondary mental health services.

PURPOSE: Healthcare provision in the United Kingdom (UK) falls primarily to the National Health Service (NHS) which is free at the point of access. In the UK, there is currently no national marker to identify military veterans in electronic health records, nor a requirement to record it. This study aimed to compare the sociodemographic characteristics and recorded mental health diagnoses of a sample of veterans and civilians accessing secondary mental health services. METHODS: The Military Service Identification Tool, a machine learning computer tool, was employed to identify veterans and civilians from electronic health records. This study compared the sociodemographic characteristics and recorded mental health diagnoses of veterans and civilians accessing secondary mental health care from South London and Maudsley NHS Foundation Trust, UK. Data from 2,576 patients were analysed; 1288 civilians and 1288 veterans matched on age and gender. RESULTS: Depressive disorder was the most prevalent across both groups in the sample (26.2% veterans, 15.5% civilians). The present sample of veterans accessing support for mental health conditions were significantly more likely to have diagnoses of anxiety, depressive, psychosis, personality, and stress disorders (AORs ranging 1.41-2.84) but less likely to have a drug disorder (AOR = 0.51) than age- and gender-matched civilians. CONCLUSION: Veterans accessing secondary mental health services in South London had higher risks for many mental health problems than civilians accessing the same services. Findings suggest that military career history is a key consideration for probable prognosis and treatment, but this needs corroborating in other geographical areas including national population-based studies in the UK.