South London And Maudsley Research Articles

Treatment with medication for patients with psychosis within 2 days during waiting in the accident and emergency department and its correlation with length of in-patient stay: retrospective database study.

One of the 'critical goals' for psychiatric liaison services is reducing hospitalisation. Psychotropic medication is a treatment for psychosis, although research determining the efficacy of early medication administration is lacking. To determine whether commencing psychotropic medication within 2 days of psychiatric liaison input in the accident and emergency (A&E) department is correlated with length of in-patient psychiatric admissions for patients with psychosis. We gathered data on patients presenting to A&E sites covered by South London and Maudsley (SLaM) National Health Service Trust, who were subsequently admitted to and discharged from SLaM psychiatric in-patient wards with discharge diagnosis of psychosis between 2015 and 2020. The analysis set comprised 228 patients waiting in the A&E department under psychiatric liaison care for ≥2 days, of which 140 were started on medication within those 2 days (group A) and 88 were not (group B). Group A was divided into A1 (patients restarted on previous psychotropic medication taken within 1 week) and A2 (others, including those new to psychotropic medication or with past usage). Although Kaplan-Meier survival curves with log-rank tests demonstrated no statistically significant difference of in-patient admission duration between groups A and B or groups B1 and B2, further analysis revealed that subgroup A1 had statistically significant shorter admissions than group B (P = 0.05). Restarting patients with psychosis on medication they were taking within the week before A&E department attendance, within 2 days of arrival at the A&E department, is associated with statistically significant shorter admissions. The limitation is a relatively small sample size.

Cohort profile: working age adults accessing secondary mental health services in South London (UK) and benefits – a data linkage of electronic mental health records and benefits data.

IntroductionIn the UK, mental disorders are one of the most common reasons for claiming a benefit relating to unemployment, income, sickness and disability. Limited information exists regarding the demographic characteristics and psychiatric profiles of working age individuals claiming benefits in London. Until recently, detailed data on both mental disorders and benefit receipt were unavailable. ObjectivesTo establish and describe a cohort of working age adults accessing secondary mental health services and benefits related to unemployment, income, sickness, and disability. MethodsUsing a novel data linkage containing electronic secondary mental health records from the South London and Maudsley (SLaM) NHS Foundation Trust and benefits data from the Department for Work and Pensions (DWP), we present descriptive statistics on sociodemographics, psychiatric diagnoses, and benefits received among a cohort of working age adults. The DWP benefits data window covers the period January 2007-June 2020, the SLaM data window covers the period January 2007-June 2019. ResultsWe identified n = 150,348 patients (18-65 years), who had attended SLaM secondary mental health services, 78.3% of which had received a benefit relating to unemployment, income, sickness and disability. Of this group, 68% had a recorded primary psychiatric diagnosis. We found that a much higher percentage of those with a primary psychiatric diagnosis received more than one benefit (69.4%) compared to those who had not received a primary psychiatric diagnosis (30.6%). Almost 70% of claimants who obtained more than one benefit were identified as living within the two quintiles representing the highest levels of deprivation in the South-east London boroughs served by SLaM. ConclusionsWe showed types of benefits received among working age adults accessing secondary mental health services. This cohort will be further examined to explore trajectories of mental health care and benefit receipt and provide evidence that will help to inform both DWP policies and mental health care delivery.

Physical Health and Transition to Psychosis in People at Clinical High Risk.

The clinical high risk for psychosis (CHR-P) construct represents an opportunity for prevention and early intervention in young adults, but the relationship between risk for psychosis and physical health in these patients remains unclear. We conducted a RECORD-compliant clinical register-based cohort study, selecting the long-term cumulative risk of developing a persistent psychotic disorder as the primary outcome. We investigated associations between primary outcome and physical health data with Electronic Health Records at the South London and Maudsley (SLaM) NHS Trust, UK (January 2013-October 2020). We performed survival analyses using Kaplan-Meier curves, log-rank tests, and Cox proportional hazard models. The database included 137 CHR-P subjects; 21 CHR-P developed psychosis during follow-up, and the cumulative incidence of psychosis risk was 4.9% at 1 year and 56.3% at 7 years. Log-rank tests suggested that psychosis risk might change between different levels of nicotine and alcohol dependence. Kaplan-Meier curve analyses indicated that non-hazardous drinkers may have a lower psychosis risk than non-drinkers. In the Cox proportional hazard model, nicotine dependence presented a hazard ratio of 1.34 (95% CI: 1.1-1.64) (p = 0.01), indicating a 34% increase in psychosis risk for every additional point on the Fagerström Test for Nicotine Dependence. Our findings suggest that a comprehensive assessment of tobacco and alcohol use, diet, and physical activity in CHR-P subjects is key to understanding how physical health contributes to psychosis risk.

Risk factors for involvement in care proceedings for mothers receiving treatment for substance use: A cohort study using linked and administrative data in South London

BackgroundMaternal substance use is considered a significant risk for child maltreatment and neglect, and thus, a common feature in care proceedings (Family Courts). It is important to better understand how the complex needs of these mothers impact on care proceedings’ outcomes. The present study explored individual and clinical characteristics of mothers receiving treatment for substance use to describe who the mothers involved in care proceedings are, and explore what factors are associated with out-of-home placement of their children. MethodsData were extracted from electronic health records (EHRs) of 1587 mothers of dependent children (age < 18 years old) who attended South London and Maudsley (SLaM) National Health Services (NHS) Foundation Trust addiction services between 2007 and 2019. Clinical service records of 480 mothers (30 %) were linked to family court records. ResultsThe number of care proceeding cases decreased during the study period. Most mothers involved in care proceedings (79 %) were known to SLaM before care proceedings began. Compared to mothers who were not involved in care proceedings, mothers who were involved, were more likely to be younger, from a non-white background, to be socially deprived, to experience housing problems, to be pregnant, to have a longer duration of treatment for substance use, to use opioids and/or crack-cocaine and to report lifetime domestic violence victimisation, be at risk of suicide, and report poorer quality of life and psychological health. The median length of care proceeding cases was 37 weeks. Eighty-two percent of mothers had care for their child terminated by the court. Mothers’ younger age, housing problems, use of opiate and/or cocaine/crack-cocaine and poorer quality of life increased the odds of out-of-home placement of the children. The participation of the child’s father in the proceedings was a protective factor for maintaining care of the child for those mothers that were receiving substance use treatment at the time of the proceedings. Attending treatment for substance use during the proceedings was not associated with the child placement outcome. ConclusionFindings highlight that current substance use treatment services are not designed to support mothers retain the care of their children. Understanding and addressing the range of needs of these mothers has implications for both substance use treatment and child welfare.

Mental health, welfare and state support: Findings from a novel data linkage

ObjectivesTo describe the process and outcomes of establishing a unique data linkage between mental healthcare records from the South London and Maudsley (SLaM) NHS Foundation Trust with benefits records from the Department for Work and Pensions.&#x0D; Methods448,404 IDs of patients who accessed secondary mental healthcare services at SLaM were sent to the DWP, including personal identifiers. Data from SLaM covered years 2007-2019, whereas data from DWP covered years 2005-2020. A deterministic data linkage approach was used.&#x0D; ResultsA linkage rate of 93% was achieved. Patient groups who were less likely to be linked were women, those from a racial and ethnic minority background and younger patients. Benefit receipt was high among patients, with 83% of patients having received benefits during the 15-year follow-up period. Benefits most frequently received included unemployment related or income replacing disability benefits.&#x0D; ConclusionThis data linkage is the first of its kind in the UK to demonstrate the use of routinely collected mental health and benefits data. It provides opportunities to generate much needed high-quality evidence that can be used to achieve change, investment in services and translation into policy and practice.

Cohort profile: Working age adults accessing secondary mental healthcare services in South London (UK) and benefits – A data linkage of electronic mental healthcare records and benefits data

ObjectivesTo present an overview of a cohort of working age adults accessing secondary mental healthcare services and benefits related to unemployment, sickness, disability, or income support and describe the different benefit types received across diagnostic and sociodemographic groups.&#x0D; MethodsUsing a novel data linkage containing electronic secondary mental health care records from the South London and Maudsley (SLaM) NHS Foundation Trust and benefits data from the Department for Work and Pensions (DWP), we present descriptive statistics on a cohort of working age adults. The data window covers the period January 2007-June 2020.&#x0D; ResultsWe identified n=150,348 patients of working age (18-65 years), who had attended SLaM secondary mental health care services, 78.3% of which had received a benefit relating to unemployment, sickness, disability, or income support. Of this group, 68% had a recorded primary psychiatric diagnosis. We found that a much higher percentage of those with a primary psychiatric diagnosis received more than one benefit (69.4%) compared to those who had not received a primary psychiatric diagnosis (30.6%).&#x0D; ConclusionsWe showed types of benefits received among working age adults accessing secondary mental health care services. This cohort will be further examined to explore trajectories of mental health care and benefit receipt and provide evidence that will help to inform both DWP policies and mental health care delivery.

Antidepressant drug prescription and incidence of COVID-19 in mental health outpatients: a retrospective cohort study

BackgroundCurrently, the main pharmaceutical intervention for COVID-19 is vaccination. While antidepressant (AD) drugs have shown some efficacy in treatment of symptomatic COVID-19, their preventative potential remains largely unexplored. Analysis of association between prescription of ADs and COVID-19 incidence in the population would be beneficial for assessing the utility of ADs in COVID-19 prevention.MethodsRetrospective study of association between AD prescription and COVID-19 diagnosis was performed in a cohort of community-dwelling adult mental health outpatients during the 1st wave of COVID-19 pandemic in the UK. Clinical record interactive search (CRIS) was performed for mentions of ADs within 3 months preceding admission to inpatient care of the South London and Maudsley (SLaM) NHS Foundation Trust. Incidence of positive COVID-19 tests upon admission and during inpatient treatment was the primary outcome measure.ResultsAD mention was associated with approximately 40% lower incidence of positive COVID-19 test results when adjusted for socioeconomic parameters and physical health. This association was also observed for prescription of ADs of the selective serotonin reuptake inhibitor (SSRI) class.ConclusionsThis preliminary study suggests that ADs, and SSRIs in particular, may be of benefit for preventing COVID-19 infection spread in the community. The key limitations of the study are its retrospective nature and the focus on a mental health patient cohort. A more definitive assessment of AD and SSRI preventative potential warrants prospective studies in the wider demographic.

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

ObjectiveTo examine the prevalence of HIV in a cohort of people who have used secondary mental health services in the UK.DesignRetrospective cohort study.SettingRoutinely collected clinical data from secondary mental health...

Do psychiatric decision units make a difference? An analysis from a liaison psychiatry service in Greater London

IntroductionCAU (Clinical assessment unit) was developed at Croydon University Hospital (CUH) in conjunction with the South London and Maudsley (SLaM) mental health trust in response to the Covid19 pandemic to relieve pressure on services in A&amp;E (Accident and Emergency) and to support the already existing need to provide a more clinically appropriate space for patients presenting to A&amp;E with acute mental health concerns. The clinical model for the unit was developed with input from service users, SLaM, CUH and CCG (Clinical Commissioning Group); and was fully established in October 2021 within a month of conception. CAU is located within close proximity to A&amp;E which is convenient and incurs no transfer cost. Similar units have been developed internationally to address similar concerns (Goldsmith et al 2021, Wiley online library 2021 12849)ObjectivesTo evaluate the financial and clinical impact of the clinical assessment unit after one year in operationMethodsThis is a cross sectional study, data was collected from EPJs Reports (SLaM’s patient data reporting system), excel spread sheet collecting data based on referrals to the service over the one-year period from 8/9/2021 – 5/10/2022. This included a trial period from September 2021 – October 2021 where the service was running at half capacity.CAU is open to capacitous adults aged 18-65 presenting to A&amp;E. Exclusion criteria: individuals conveyed by the police, those under MHA, on-going physical health concerns, diagnosis of learning disability with no primary mental health need, diagnosis of dementia and homelessnessResults3,322 patients were referred to the Liaison service and of those 402 or 12% of those patients to A&amp;E were transferred to CAUThe 402 service users over the period of one year spent a total of 11, 351 hours in CAUThe main diagnosis of patient admitted to CAU fell into the diagnostic categories F30-39 43.5 %, and F60-69 27%.The majority of patients were admitted awaiting informal admission and 1/3 of plans for discharge destination were made on CAU. 10 % of patient were discharged on a least restrictive outcome, which has cost benefits for acute mental health trust. This one-year period showed cost saving of £462,112 for 24 hours stay in ED with support staff.Image:Image 2:ConclusionsCAU offers the opportunity to engage and re-assess service users to allow consideration of least restrictive options for on-going care. CAU has financial benefits in way of saving cost on time spent in ED awaiting review and cost for agency staff to provide 1:1 support.The success of CAU has led to collaboration in the developpment of other acute services in London including that of the Recovery Space which offers community support for service users following discharge from hospital after an acute mental health crisis. Service user feedback has been positive and reflects the importance of the service and its suitability for its target group.Disclosure of InterestNone Declared

The impact of severe mental illness (SMI) on the rate of COVID-19 vaccine uptake and hesitancy

IntroductionThe COVID-19 pandemic has disproportionately affected patients with severe mental illness (SMI), a vulnerable population with high morbidity and mortality. A UK-based study found reduced vaccination rates in patients with SMI; they therefore need to be prioritised for prevention and disease management.ObjectivesThe objectives were to determine risk factors for vaccine hesitancy, and how best to manage those in patients with SMI, as well as whether our intervention of calling patients for their vaccines had a positive outcome.MethodsFollowing approval from the Lambeth Directorate of South London and Maudsley (SLaM) NHS Foundation Trust, we investigated COVID-19 vaccination rates inpatients with SMI from a psychosis community service in South London (n=236). Dates of first and second doses were recorded through audit; reasons for refusal of vaccination were noted. Patients were encouraged to take the vaccine. A re-audit was performed after allowing three months. Chi-squared statistical analysis was performed to determine the value of our intervention.ResultsBefore the intervention, 143 patients (60.6%) received at least one vaccine. 24 patients (10.2%) received one dose, and 77 (32.8%) were yet to receive any. There was no statistical significance (p=0.1509) between the number of patients who received a vaccine before and after intervention, with 33.1% of patients still remaining unvaccinated.Image:Image 2:Image 3:ConclusionsThere is limited research on perceptions of receiving vaccines in patients with SMI, despite their cost-effectiveness in disease prevention. Even after intervention, 33.1% of patients remained unvaccinated, compared to 6.6% nationally. A lack of knowledge and recommendations from care teams are reasons for hesitancy. Misinformation, conspiracy theories and propaganda can drive people towards refusal. Patients with SMI typically have disadvantages of healthcare inequality, lower levels of education and access to inaccurate information. Patients and their healthcare team should be knowledgeable about vaccine efficacy and side effects. Studies have shown low uptake in the Black/African/Caribbean ethnic group (49.3%, table 3). Reasons include general mistrust in institutions and access barriers. For minority communities, vaccination sites in community centres or places of worship have proven to be effective, providing familiarity.Patients taking clozapine may have a weaker immune system due to myelosuppression. 24.3% of our patients take this, with many unsure of interactions or side effects. Poorer prognosis means a focussed approach is needed.Vaccine hesitancy is complex and requires targeted, tailor-made strategies, with consideration for patients who may lack capacity. It is evident from our results that calling patients alone may not be effective. A future multi-modal approach may be necessary to address poor vaccine uptake and opens up avenues to further explore vaccine hesitancy.Disclosure of InterestNone Declared

Associations of remote mental healthcare with clinical outcomes: a natural language processing enriched electronic health record data study protocol

IntroductionPeople often experience significant difficulties in receiving mental healthcare due to insufficient resources, stigma and lack of access to care. Remote care technology has the potential to overcome these barriers...

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

ObjectivesTo 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...

Physical Health in Clinical High Risk for Psychosis Individuals: A Cross-Sectional Study.

The clinical high risk for psychosis (CHR-P) phase represents an opportunity for prevention and early intervention in young adults, which also could focus on improving physical health trajectories. We conducted a RECORD-compliant clinical register-based cohort study. The primary outcome was to describe the physical health of assessed CHR-P individuals, obtained via Electronic Health Records at the South London and Maudsley (SLaM) NHS Foundation Trust, UK (January 2013-October 2020). The final database included 194 CHR-P subjects (46% female). Mean age was 23.70 ± 5.12 years. Percentage of tobacco smokers was 41% (significantly higher than in the age-matched general population [24%]). We found that 49% of subjects who consumed alcohol had an AUDIT-C (Alcohol Use Disorder Identification Test) score above 5 (hazardous drinking), with an average score of 4.94 (significantly higher than in the general population [2.75]). Investigating diet revealed low fiber intake in most subjects and high saturated fat intake in 10% of the individuals. We found that 47% of CHR-P subjects met the UK recommended physical activity guidelines (significantly lower than in the general population [66%]). Physical parameters (e.g., weight, heart rate, blood pressure) were not significantly different from the general population. This evidence corroborates the need for monitoring physical health parameters in CHR-P subjects, to implement tailored interventions that target daily habits.

Using a statistical learning approach to identify sociodemographic and clinical predictors of response to clozapine.

Background:A proportion of people with treatment-resistant schizophrenia fail to show improvement on clozapine treatment. Knowledge of the sociodemographic and clinical factors predicting clozapine response may be useful in developing personalised approaches to treatment.Methods:This retrospective cohort study used data from the electronic health records of the South London and Maudsley (SLaM) hospital between 2007 and 2011. Using the Least Absolute Shrinkage and Selection Operator (LASSO) regression statistical learning approach, we examined 35 sociodemographic and clinical factors’ predictive ability of response to clozapine at 3 months of treatment. Response was assessed by the level of change in the severity of the symptoms using the Clinical Global Impression (CGI) scale.Results:We identified 242 service-users with a treatment-resistant psychotic disorder who had their first trial of clozapine and continued the treatment for at least 3 months. The LASSO regression identified three predictors of response to clozapine: higher severity of illness at baseline, female gender and having a comorbid mood disorder. These factors are estimated to explain 18% of the variance in clozapine response. The model’s optimism-corrected calibration slope was 1.37, suggesting that the model will underfit when applied to new data.Conclusions:These findings suggest that women, people with a comorbid mood disorder and those who are most ill at baseline respond better to clozapine. However, the accuracy of the internally validated and recalibrated model was low. Therefore, future research should indicate whether a prediction model developed by including routinely collected data, in combination with biological information, presents adequate predictive ability to be applied in clinical settings.

Parental status and characteristics of women in substance use treatment services: Analysis of electronic patient records

BackgroundMany women receiving substance use treatment services are mothers. Despite this, research has not proved whether substance use treatment services are addressing the specific needs of mothers. This study explored differences in sociodemographic, psychological, patterns of substance use, and treatment characteristics between mothers and women without children, and between mothers whose children were in alternative care. MethodThe study extracted data from electronic patient records (EPRs) of women who attended South London and Maudsley (SLaM) National Health Services (NHS) Foundation Trust addiction services between 2013 and 2020 (N = 4370). ResultsThe study identified 1730 participants (39.6%) as mothers, of whom 1340 (77.4%) had dependent children. The average number of births was 1.83 (SD = 1.0). Of the participants, 54.3% of mothers did not disclose whether their dependent child(ren) was under their care and 37.5% of mothers indicated that at least one of their child(ren) was in alternative care. Alcohol was the most reported type of substance used in the past 28 days. Mothers also highly reported suicide attempts and hospitalization due to mental health problems. Compared to women without children, mothers were more likely to be young, experience housing problems, use opioids and/or crack-cocaine in the past 28 days and experience lifetime domestic violence victimizations. Mothers were also less likely to have alcohol-related problems, experience overdose, and social isolation than women without children. ConclusionThe study highlights the need for substance use services to invest in approaches to improve mothers' disclosure of parenting and childcare issues. It also demonstrates that EPRs can identify key characteristics of mothers.

Impact of the COVID-19 pandemic on remote mental healthcare and prescribing in psychiatry: an electronic health record study

ObjectivesThe recent COVID-19 pandemic has disrupted mental healthcare delivery, with many services shifting from in-person to remote patient contact. We investigated the impact of the pandemic on the use of...

The case for improved transdiagnostic detection of first-episode psychosis: Electronic health record cohort study

BackgroundImproving outcomes of a First Episode of Psychosis (FEP) relies on the ability to detect most individuals with emerging psychosis and treat them in specialised Early Intervention (EI) services. Efficacy of current detection strategies is undetermined. MethodsRECORD-compliant clinical, 6-year, retrospective, transdiagnostic, lifespan-inclusive, Electronic Health Record (EHR) cohort study, representing real-world secondary mental healthcare in South London and Maudsley (SLaM) NHS. All individuals accessing SLaM in the period 2007–2017 and receiving any ICD-10 diagnosis other than persistent psychosis were included. Descriptive statistics, Kaplan-Meier curves, logistic regression, epidemiological incidence of psychosis in the general population were used to address pathways to care and detection power of EI services for FEP. ResultsA total of 106,706 individuals underwent the 6-year follow-up: they were mostly single (72.57%) males (50.51%) of white ethnicity (60.01%), aged on average 32.96 years, with an average Health Of the Nation Outcome Scale score of 11.12 and mostly affected with F40–48 Neurotic/stress-related/somatoform disorders (27.46%). Their transdiagnostic risk of developing a FEP cumulated to 0.072 (95%CI 0.067–0.077) at 6 years. Those individuals who developed a FEP (n = 1841) entered healthcare mostly (79.02%) through inpatient mental health services (29.76%), community mental health services (29.54%) or accident and emergency departments (19.50%); at the time of FEP onset, most of them (46.43%) were under the acute care pathway. Individuals contacting accident and emergency departments had an increased risk of FEP (OR 2.301, 95%CI 2.095–2.534, P < 0.001). The proportion of SLaM FEP cases that were eligible and under the care of EI services was 0.456 at any time. The epidemiological proportion of FEP cases in the sociodemographically-matched general population that was detected by EI service was 0.373. ConclusionsMore than half of individuals who develop a FEP remain undetected by current pathways to care and EI services. Improving detection strategies should become a mainstream area in the future generation of early psychosis research.

Using Natural Language Processing on Electronic Health Records to Enhance Detection and Prediction of Psychosis Risk.

Using novel data mining methods such as natural language processing (NLP) on electronic health records (EHRs) for screening and detecting individuals at risk for psychosis. The study included all patients receiving a first index diagnosis of nonorganic and nonpsychotic mental disorder within the South London and Maudsley (SLaM) NHS Foundation Trust between January 1, 2008, and July 28, 2018. Least Absolute Shrinkage and Selection Operator (LASSO)-regularized Cox regression was used to refine and externally validate a refined version of a five-item individualized, transdiagnostic, clinically based risk calculator previously developed (Harrell's C = 0.79) and piloted for implementation. The refined version included 14 additional NLP-predictors: tearfulness, poor appetite, weight loss, insomnia, cannabis, cocaine, guilt, irritability, delusions, hopelessness, disturbed sleep, poor insight, agitation, and paranoia. A total of 92 151 patients with a first index diagnosis of nonorganic and nonpsychotic mental disorder within the SLaM Trust were included in the derivation (n = 28 297) or external validation (n = 63 854) data sets. Mean age was 33.6 years, 50.7% were women, and 67.0% were of white race/ethnicity. Mean follow-up was 1590 days. The overall 6-year risk of psychosis in secondary mental health care was 3.4 (95% CI, 3.3-3.6). External validation indicated strong performance on unseen data (Harrell's C 0.85, 95% CI 0.84-0.86), an increase of 0.06 from the original model. Using NLP on EHRs can considerably enhance the prognostic accuracy of psychosis risk calculators. This can help identify patients at risk of psychosis who require assessment and specialized care, facilitating earlier detection and potentially improving patient outcomes.

Outreach and support in South-London (OASIS) 2001—2020: Twenty years of early detection, prognosis and preventive care for young people at risk of psychosis

This study aims to describe twenty years of early detection, prognosis and preventive care in the Outreach and Support In South-London (OASIS) mental health service for individuals at Clinical High risk of psychosis (CHR-P). The study presents a comprehensive analysis of the 2001– 2020 activity of the OASIS team encompassing core domains: (i) service characteristics, (ii) detection, (iii) prognosis, (iv) treatment and (v) clinical research. The analyses employed descriptive statistics, population-level data, the epidemiological incidence of psychosis, Kaplan Meier failure functions and Greenwood 95% CIs and Electronic Health Records. OASIS is part of the South London and Maudsley (SLaM) NHS trust, the largest European mental health provider, serving a total urban population of 1,358,646 individuals (population aged 16-35: 454,525). Incidence of psychosis in OASIS's catchment area ranges from 58.3 to 71.9 cases per 100,000 person-years, and it is higher than the national average of 41.5 cases per 100,000 person-year. OASIS is a standalone, NHS-funded, multidisciplinary (team leader, consultant and junior psychiatrists, clinical psychologists, mental health professionals), transitional (for those aged 14-35 years) community mental health service with a yearly caseload of 140 CHR-P individuals. OASIS regularly delivers a comprehensive service promotion outreach to several local community organisations. Referrals to OASIS (2366) are made by numerous agencies; about one-third of the referrals eventually met CHR-P criteria. Overall, 600 CHR-P individuals (55.33% males, mean age 22.63 years, white ethnicity 46.44%) have been under the care of the OASIS service: 80.43% met attenuated psychotic symptoms, 18.06% brief and limited intermittent psychotic symptoms and 1.51% genetic risk and deterioration CHR-P criteria. All CHR-P individuals were offered cognitive behavioural therapy and psychosocial support; medications were used depending on individual needs. The cumulative risk of psychosis at ten years was 0.365 (95%CI 0.302-0.437). At six years follow-up, across two-third of individuals non-transitioning to psychosis, 79.24% still displayed some mental health problem, and only 20.75% achieved a complete clinical remission. Research conducted at OASIS encompassed clinical, prognostic, neurobiological and interventional studies and leveraged local, national and international infrastructures; over the past ten years, OASIS-related research attracted about £ 50 million of grant income, with 5,922 citations in the international databases. Future developments may include broadening OASIS to prevent other serious mental disorders beyond psychosis and fostering translational risk prediction and interventional research. With a twenty-years activity, OASIS’ cutting-edge quality of preventive care, combined with translational research innovations, consolidated the service as a leading reference model for evidence-based prevention of psychosis worldwide.

The Development of the Military Service Identification Tool: Identifying Military Veterans in a Clinical Research Database Using Natural Language Processing and Machine Learning.

BackgroundElectronic health care records (EHRs) are a rich source of health-related information, with potential for secondary research use. In the United Kingdom, there is no national marker for identifying those who have previously served in the Armed Forces, making analysis of the health and well-being of veterans using EHRs difficult.ObjectiveThis study aimed to develop a tool to identify veterans from free-text clinical documents recorded in a psychiatric EHR database.MethodsVeterans were manually identified using the South London and Maudsley (SLaM) Biomedical Research Centre Clinical Record Interactive Search—a database holding secondary mental health care electronic records for the SLaM National Health Service Foundation Trust. An iterative approach was taken; first, a structured query language (SQL) method was developed, which was then refined using natural language processing and machine learning to create the Military Service Identification Tool (MSIT) to identify if a patient was a civilian or veteran. Performance, defined as correct classification of veterans compared with incorrect classification, was measured using positive predictive value, negative predictive value, sensitivity, F1 score, and accuracy (otherwise termed Youden Index).ResultsA gold standard dataset of 6672 free-text clinical documents was manually annotated by human coders. Of these documents, 66.00% (4470/6672) were then used to train the SQL and MSIT approaches and 34.00% (2202/6672) were used for testing the approaches. To develop the MSIT, an iterative 2-stage approach was undertaken. In the first stage, an SQL method was developed to identify veterans using a keyword rule–based approach. This approach obtained an accuracy of 0.93 in correctly predicting civilians and veterans, a positive predictive value of 0.81, a sensitivity of 0.75, and a negative predictive value of 0.95. This method 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.ConclusionsThe MSIT has the potential to be used in identifying veterans in the United Kingdom from free-text clinical documents, providing new and unique insights into the health and well-being of this population and their use of mental health care services.