Search

Background The current study used data from an ethnically diverse population from South London to examine ethnic differences in physical and mental multimorbidity among working age (18–64 years) adults in the context of depression and anxiety. Method The study included 44 506 patients who had previously attended Improving Access to Psychological Therapies services in the London Borough of Lambeth. Multinomial logistic regression examined cross-sectional associations between ethnicity with physical and mental multimorbidity. Patterns of multimorbidity were identified using hierarchical cluster analysis. Results Within 44 056 working age adults with a history of depression or anxiety from South London there were notable ethnic differences in physical multimorbidity. Adults of Black Caribbean ethnicity were more likely to have physical multimorbidity [adjusted relative risk ratio (aRRR) = 1.25, 95% confidence interval (CI) 1.15–1.36] compared to adults of White ethnicity. Relative to adults of White ethnicity, adults of Asian ethnicity were more likely to have physical multimorbidity at higher thresholds only (e.g. 4 + conditions; aRRR = 1.53, 95% CI 1.17–2.00). Three physical (atopic, cardiometabolic, mixed) and three mental (alcohol/substance use, common/severe mental illnesses, personality disorder) multimorbidity clusters emerged. Ethnic minority groups with multimorbidity had a higher probability of belonging to the cardiometabolic cluster. Conclusion In an ethnically diverse population with a history of common mental health disorders, we found substantial between- and within-ethnicity variation in rates of physical, but not mental, multimorbidity. The findings emphasised the value of more granular definitions of ethnicity when examining the burden of physical and mental multimorbidity.

PurposeThere is a dearth of literature examining the impact of the COVID-19 pandemic on older people with dual diagnosis referred to mental health services. The purpose of this study was to compare dual diagnosis before and after lockdown in people aged between 55 and 74 with alcohol use.Design/methodology/approachData were collected for people referred to mental health services using an anonymised database of de-identified records to identify people with both substance use disorder alone, or accompanied by co-existing mental disorders.FindingsIn total, 366 older people were assessed with the Alcohol Use Disorders Identification Test (AUDIT), 185 before and 181 after lockdown. People with dual diagnosis were more likely to be referred than those without, after compared to before lockdown (13 and 6%, respectively, p < 0.05). People with any substance use disorder with and without dual diagnosis showed an even greater likelihood of referral after, compared with before, lockdown (61 and 34%, respectively, p < 0.0001). Opioid use more than once a month was more likely to be reported after, compared with before, lockdown (66 and 36%, respectively, p < 0.005).Research limitations/implicationsThe finding of a higher likelihood of opioid use after compared with before lockdown during the COVID-19 pandemic warrants further exploration. There is also further scope for further studies that involve older non-drinkers.Originality/valueA greater likelihood of both dual diagnosis and substance use disorder alone after, compared with before lockdown has implications for both mental health and addiction service provision during a pandemic.

Background Risk estimation models integrated into Electronic Health Records (EHRs) can deliver innovative approaches in psychiatry, but clinicians' endorsement and their real-world usability are unknown. This study aimed to investigate the real-world feasibility of implementing an individualised, transdiagnostic risk calculator to automatically screen EHRs and detect individuals at-risk for psychosis. Methods Feasibility implementation study encompassing an in-vitro phase (March 2018 to May 2018) and in-vivo phase (May 2018 to April 2019). The in-vitro phase addressed implementation barriers and embedded the risk calculator (predictors: age, gender, ethnicity, index cluster diagnosis, age*gender) into the local EHR. The in-vivo phase investigated the real-world feasibility of screening individuals accessing secondary mental healthcare at the South London and Maudsley NHS Trust. The primary outcome was adherence of clinicians to automatic EHR screening, defined by the proportion of clinicians who responded to alerts from the risk calculator, over those contacted. Results In-vitro phase: implementation barriers were identified/overcome with clinician and service user engagement, and the calculator was successfully integrated into the local EHR through the CogStack platform. In-vivo phase: 3722 individuals were automatically screened and 115 were detected. Clinician adherence was 74% without outreach and 85% with outreach. One-third of clinicians responded to the first email (37.1%) or phone calls (33.7%). Among those detected, cumulative risk of developing psychosis was 12% at six-month follow-up. Conclusion This is the first implementation study suggesting that combining precision psychiatry and EHR methods to improve detection of individuals with emerging psychosis is feasible. Future psychiatric implementation research is urgently needed.

Purpose The World Health Organisation (WHO) recently ranked air pollution as the major environmental cause of premature death. However, the significant potential health and societal costs of poor mental health in relation to air quality are not represented in the WHO report due to limited evidence. We aimed to test the hypothesis that long-term exposure to air pollution is associated with poor mental health. Methods A prospective longitudinal population-based mental health survey was conducted of 1698 adults living in 1075 households in South East London, from 2008 to 2013. High-resolution quarterly average air pollution concentrations of nitrogen dioxide (NO2) and oxides (NOx), ozone (O3), particulate matter with an aerodynamic diameter 10) and 2.5) were linked to the home addresses of the study participants. Associations with mental health were analysed with the use of multilevel generalised linear models, after adjusting for large number of confounders, including the individuals’ socioeconomic position and exposure to road-traffic noise. Results We found robust evidence for interquartile range increases in PM2.5, NOx and NO2 to be associated with 18–39% increased odds of common mental disorders, 19–30% increased odds of poor physical symptoms and 33% of psychotic experiences only for PM10. These longitudinal associations were more pronounced in the subset of non-movers for NO2 and NOx. Conclusions The findings suggest that traffic-related air pollution is adversely affecting mental health. Whilst causation cannot be proved, this work suggests substantial morbidity from mental disorders could be avoided with improved air quality.

BackgroundCatatonia, a severe neuropsychiatric syndrome, has few studies of sufficient scale to clarify its epidemiology or pathophysiology. We aimed to characterise demographic associations, peripheral inflammatory markers and outcome of catatonia.MethodsElectronic healthcare records were searched for validated clinical diagnoses of catatonia. In a case–control study, demographics and inflammatory markers were compared in psychiatric inpatients with and without catatonia. In a cohort study, the two groups were compared in terms of their duration of admission and mortality.ResultsWe identified 1456 patients with catatonia (of whom 25.1% had two or more episodes) and 24 956 psychiatric inpatients without catatonia. Incidence was 10.6 episodes of catatonia per 100 000 person-years. Patients with and without catatonia were similar in sex, younger and more likely to be of Black ethnicity. Serum iron was reduced in patients with catatonia [11.6 v. 14.2 μmol/L, odds ratio (OR) 0.65 (95% confidence interval (CI) 0.45–0.95), p = 0.03] and creatine kinase was raised [2545 v. 459 IU/L, OR 1.53 (95% CI 1.29–1.81), p < 0.001], but there was no difference in C-reactive protein or white cell count. N-Methyl-d-aspartate receptor antibodies were significantly associated with catatonia, but there were small numbers of positive results. Duration of hospitalisation was greater in the catatonia group (median: 43 v. 25 days), but there was no difference in mortality after adjustment.ConclusionsIn the largest clinical study of catatonia, we found catatonia occurred in approximately 1 per 10 000 person-years. Evidence for a proinflammatory state was mixed. Catatonia was associated with prolonged inpatient admission but not with increased mortality.

BackgroundGrowing evidence suggests that air pollution exposure may adversely affect the brain and increase risk for psychiatric disorders such as schizophrenia and depression. However, little is known about the potential role of air pollution in severity and relapse following illness onset.AimsTo examine the longitudinal association between residential air pollution exposure and mental health service use (an indicator of illness severity and relapse) among individuals with first presentations of psychotic and mood disorders.MethodWe identified individuals aged ≥15 years who had first contact with the South London and Maudsley NHS Foundation Trust for psychotic and mood disorders in 2008–2012 (n = 13 887). High-resolution (20 × 20 m) estimates of nitrogen dioxide (NO2), nitrogen oxides (NOx) and particulate matter (PM2.5 and PM10) levels in ambient air were linked to residential addresses. In-patient days and community mental health service (CMHS) events were recorded over 1-year and 7-year follow-up periods.ResultsFollowing covariate adjustment, interquartile range increases in NO2, NOx and PM2.5 were associated with 18% (95% CI 5–34%), 18% (95% CI 5–34%) and 11% (95% CI 3–19%) increased risk for in-patient days after 1 year. Similarly, interquartile range increases in NO2, NOx, PM2.5 and PM10 were associated with 32% (95% CI 25–38%), 31% (95% CI 24–37%), 7% (95% CI 4–11%) and 9% (95% CI 5–14%) increased risk for CMHS events after 1 year. Associations persisted after 7 years.ConclusionsResidential air pollution exposure is associated with increased mental health service use among people recently diagnosed with psychotic and mood disorders. Assuming causality, interventions to reduce air pollution exposure could improve mental health prognoses and reduce healthcare costs.

BackgroundPeople with schizophrenia have a high premature mortality risk. Obesity is a key potential underlying risk factor that is relatively unevaluated to date.AimsIn this study, we investigated the associations of routinely recorded body size with all-cause mortality and deaths from common causes in a large cohort of people with schizophrenia spectrum disorders.MethodsWe assembled a retrospective observational cohort using data from a large mental health service in South London. We followed all patients over the age of 18 years with a clinical diagnosis of schizophrenia spectrum disorders from the date of their first recorded body mass index (BMI) between 1 January 2007 and 31 March 2018.ResultsOf 11 900 patients with a BMI recording, 1566 died. The Cox proportional hazards regression models, after adjusting for sociodemographic, socioeconomic variables and comorbidities, indicated that all-cause mortality was only associated with underweight status compared with healthy weight status (hazard ratio (HR): 1.33, 95% confidence interval (CI): 1.01 to 1.76). Obesity (HR: 1.24, 95% CI: 1.01 to 1.52) and morbid obesity (HR: 1.54, 95% CI: 1.03 to 2.42) were associated with all-cause mortality in the 18–45 years age range, and obesity was associated with lower risk (HR: 0.66, 95% CI: 0.50 to 0.87) in those aged 65+ years. Cancer mortality was raised in underweight individuals (HR: 1.93, 95% CI: 1.03 to 4.10) and respiratory disease mortality raised in those with morbid obesity (HR: 2.17, 95% CI: 1.02 to 5.22).ConclusionsOverall, being underweight was associated with higher mortality in this disorder group; however, this was potentially accounted for by frailty in older age groups, and obesity was a risk factor for premature mortality in younger ages. The impact of obesity on life expectancy for people with schizophrenia spectrum disorders is clear from our findings. A deeper biological understanding of the relationship between these diseases and schizophrenia will help improve clinical practice.

Background People with schizophrenia have shortened lives. This excess mortality seems to be related to physical health conditions that may be amenable to better primary and secondary prevention. Better continuity of care may enhance such interventions as well as help prevent death by self-injury. Aims We set out to examine the relationship between the continuity of care of patients with schizophrenia, their mortality and cause of death. Method Pseudoanonymised community data from 5551 people with schizophrenia presenting over 11 years were examined for changes in continuity of care using the numbers of community teams caring for them and the Modified Modified Continuity Index. These and demographic variables were related to death certifications of physical illness from the Office of National Statistics and mortal self-injury from clinical data. Data were analysed using generalised estimating equations. Results We found no independent relationship between levels of continuity of care and overall mortality. However, lower levels of relationship continuity were significantly and independently related to death by self-injury. Conclusions We found no evidence that continuity of care is important in the prevention of physical causes of death in schizophrenia. However, there is evidence that declining relationship continuity of care has an independent effect on deaths as a result of self-injury. We suggest that there should be more attention focused on the improvement of continuity of care for these patients.

OBJECTIVES Evidence in mouse models has found that the antidepressant trazodone may be protective against neurodegeneration. We therefore aimed to compare cognitive decline of people with dementia taking trazodone with those taking other antidepressants. METHODS Three identical naturalistic cohort studies using UK clinical registers. We included all people with dementia assessed during 2008-16 who were recorded taking trazodone, citalopram or mirtazapine for at least 6 weeks. Linear mixed models examined age, time and sex-adjusted Mini-mental state examination (MMSE) change in people with all-cause dementia taking trazodone compared with those taking citalopram and mirtazapine. In secondary analyses, we examined those with non-vascular dementia; mild dementia; and adjusted results for neuropsychiatric symptoms. We combined results from the three study sites using random-effects meta-analysis. RESULTS We included 2,199 people with dementia, including 406 taking trazodone, with mean 2.2 years follow-up. There was no difference in adjusted cognitive decline in people with all-cause or non-vascular dementia taking trazodone, citalopram or mirtazapine in any of the three study sites. When data from the three sites were combined in meta-analysis, we found greater mean MMSE decline in people with all-cause dementia taking trazodone compared to those taking citalopram (0·26 points per successive MMSE measurement, 95% CI 0·03-0·49; p = 0·03). Results in sensitivity analyses were consistent with primary analyses. CONCLUSIONS There was no evidence of cognitive benefit from trazodone compared to other antidepressants in people with dementia in three naturalistic cohort studies. Despite preclinical evidence, trazodone should not be advocated for cognition in dementia.

Background Gender disparities in treatment are apparent across many areas of healthcare. There has been little research into whether clozapine prescription, the first-line treatment for treatment-resistant schizophrenia (TRS), is affected by patient gender. Methods This retrospective cohort study identified 2244 patients with TRS within the South London and Maudsley NHS Trust, by using a bespoke method validated against a gold-standard, manually coded, dataset of TRS cases. The outcome and exposures were identified from the free-text using natural language processing applications (including machine learning and rules-based approaches) and from information entered in structured fields. Multivariable logistic regression was carried out to calculate the odds ratios for clozapine prescription according to patients' gender, and adjusting for numerous potential confounders including sociodemographic, clinical (e.g., psychiatric comorbidities and substance use), neutropenia, functional factors (e.g., problems with occupation), and clinical monitoring. Results Clozapine was prescribed to 77% of the women and 85% of the men with TRS. Women had reduced odds of being prescribed clozapine as compared to men after adjusting for all factors included in the present study (adjusted OR: 0.66; 95% CI 0.44–0.97; p = 0.037). Conclusion Women with TRS are less likely to be prescribed clozapine than men with TRS, even when considering the effects of multiple clinical and functional factors. This finding suggests there could be gender bias in clozapine prescription, which carries ramifications for the relatively poorer care of women with TRS regarding many outcomes such as increased hospitalisation, mortality, and poorer quality of life.

Background 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. Method 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. Results 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. Conclusions 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.

BackgroundResearch on sickness absence has typically focussed on single diagnoses, despite increasing recognition that long-term health conditions are highly multimorbid and clusters comprising coexisting mental and physical conditions are associated with poorer clinical and functional outcomes. The digitisation of sickness certification in the UK offers an opportunity to address sickness absence in a large primary care population.MethodsLambeth Datanet is a primary care database which collects individual-level data on general practitioner consultations, prescriptions, Quality and Outcomes Framework diagnostic data, sickness certification (fit note receipt) and demographic information (including age, gender, self-identified ethnicity, and truncated postcode). We analysed 326 415 people's records covering a 40-month period from January 2014 to April 2017.ResultsWe found significant variation in multimorbidity by demographic variables, most notably by self-defined ethnicity. Multimorbid health conditions were associated with increased fit note receipt. Comorbid depression had the largest impact on first fit note receipt, more than any other comorbid diagnoses. Highest rates of first fit note receipt after adjustment for demographics were for comorbid epilepsy and rheumatoid arthritis (HR 4.69; 95% CI 1.73–12.68), followed by epilepsy and depression (HR 4.19; 95% CI 3.60–4.87), chronic pain and depression (HR 4.14; 95% CI 3.69–4.65), cardiac condition and depression (HR 4.08; 95% CI 3.36–4.95).ConclusionsOur results show striking variation in multimorbid conditions by gender, deprivation and ethnicity, and highlight the importance of multimorbidity, in particular comorbid depression, as a leading cause of disability among working-age adults.

Background How neighbourhood characteristics affect the physical safety of people with mental illness is unclear. Aims To examine neighbourhood effects on physical victimisation towards people using mental health services. Method We developed and evaluated a machine-learning-derived free-text-based natural language processing (NLP) algorithm to ascertain clinical text referring to physical victimisation. This was applied to records on all patients attending National Health Service mental health services in Southeast London. Sociodemographic and clinical data, and diagnostic information on use of acute hospital care (from Hospital Episode Statistics, linked to Clinical Record Interactive Search), were collected in this group, defined as ‘cases’ and concurrently sampled controls. Multilevel logistic regression models estimated associations (odds ratios, ORs) between neighbourhood-level fragmentation, crime, income deprivation, and population density and physical victimisation. Results Based on a human-rated gold standard, the NLP algorithm had a positive predictive value of 0.92 and sensitivity of 0.98 for (clinically recorded) physical victimisation. A 1 s.d. increase in neighbourhood crime was accompanied by a 7% increase in odds of physical victimisation in women and an 13% increase in men (adjusted OR (aOR) for women: 1.07, 95% CI 1.01–1.14, aOR for men: 1.13, 95% CI 1.06–1.21, P for gender interaction, 0.218). Although small, adjusted associations for neighbourhood fragmentation appeared greater in magnitude for women (aOR = 1.05, 95% CI 1.01–1.11) than men, where this association was not statistically significant (aOR = 1.00, 95% CI 0.95–1.04, P for gender interaction, 0.096). Neighbourhood income deprivation was associated with victimisation in men and women with similar magnitudes of association. Conclusions Neighbourhood factors influencing safety, as well as individual characteristics including gender, may be relevant to understanding pathways to physical victimisation towards people with mental illness.

BackgroundRemote consultation technology has been rapidly adopted due to the COVID-19 pandemic. However, some healthcare settings have faced barriers in implementation. We present a study to investigate changes in rates of remote consultation during the pandemic using a large electronic health record (EHR) dataset.MethodsThe Clinical Record Interactive Search tool (CRIS) was used to examine de-identified EHR data of people receiving mental healthcare in South London, UK. Data from around 37,500 patients were analysed for each week from 7th January 2019 and 20th September 2020 using linear regression and locally estimated scatterplot smoothing (LOESS) to investigate changes in the number of clinical contacts (in-person, remote or non-attended) with mental healthcare professionals and prescribing of antipsychotics and mood stabilisers. The data are presented in an interactive dashboard: http://rpatel.co.uk/TelepsychiatryDashboard.ResultsThe frequency of in-person contacts was substantially reduced following the onset of the pandemic (β coefficient: -5829.6 contacts, 95% CI -6919.5 to -4739.6, pConclusionsThe COVID-19 pandemic has been associated with a marked increase in remote consultation, particularly among younger patients. However, there was no evidence that this has led to changes in prescribing. Further work is needed to support older patients in accessing remote mental healthcare.DisclosureAll authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf and declare: RS has received funding from Janssen, GSK and Takeda outside the submitted work. RP has received funding from Janssen, Induction Healthcare and H

Background. Mood instability and sleep disturbance are common symptoms in people with mental illness. Both features are clinically important and associated with poorer illness trajectories. We compared clinical outcomes in people presenting to secondary mental health care with mood instability and/or sleep disturbance with outcomes in people without either mood instability or sleep disturbance. Methods. Data were from electronic health records of 31,391 patients ages 16–65 years presenting to secondary mental health services between 2008 and 2016. Mood instability and sleep disturbance were identified using natural language processing. Prevalence of mood instability and sleep disturbance were estimated at baseline. Incidence rate ratios were estimates for clinical outcomes including psychiatric diagnoses, prescribed medication, and hospitalization within 2-years of presentation in persons with mood instability and/or sleep disturbance compared to individuals without either symptom. Results. Mood instability was present in 9.58%, and sleep disturbance in 26.26% of patients within 1-month of presenting to secondary mental health services. Compared with individuals without either symptom, those with mood instability and sleep disturbance showed significantly increased incidence of prescription of any psychotropic medication (incidence rate ratios [IRR] = 7.04, 95% confidence intervals [CI] 6.53–7.59), and hospitalization (IRR = 5.32, 95% CI 5.32, 4.67–6.07) within 2-years of presentation. Incidence rates of most clinical outcomes were considerably increased among persons with both mood instability and sleep disturbance, relative to persons with only one symptom. Conclusions. Mood instability and sleep disturbance are present in a wide range of mental disorders, beyond those in which they are conventionally considered to be symptoms. They are associated with poor outcomes, particularly when they occur together. The poor prognosis associated with mood instability and sleep disorder may be, in part, because they are often treated as secondary symptoms. Mood instability and sleep disturbance need better recognition as clinical targets for treatment in their own right.

Obsessive–compulsive disorder (OCD) and autism spectrum disorders (ASD) commonly co-occur and are considered challenging to manage when they co-occur in youth. However, clinical characteristics and prognosis of this group remain poorly understood. This study examined the prevalence, clinical correlates and outcomes of paediatric OCD co-occurring with ASD (OCD + ASD) in a large clinical cohort. Data were extracted from electronic clinical records of young people aged 4–17 years who had attended a mental health trust in South London, United Kingdom. We identified young people with diagnoses of OCD + ASD (n = 335), OCD without ASD (n = 1010), and ASD without OCD (n = 6577). 25% of youth with OCD had a diagnosis of ASD, while 5% of those with ASD had a diagnosis of OCD. At diagnosis, youth with OCD + ASD had lower psychosocial functioning scores on the clinician-rated Child Global Assessment Scale (CGAS) compared to those with either OCD or ASD. Youth with OCD + ASD were equally likely to receive CBT compared to those with OCD but were more likely to be prescribed medication and use services for longer than either comparison group. Youth with OCD + ASD showed significant improvements in functioning (CGAS scores) after service utilisation but their gains were smaller than those with OCD. OCD + ASD commonly co-occur, conferring substantial impairment, although OCD may be underdiagnosed in youth with ASD. Young people with co-occurring OCD + ASD can make significant improvements in functioning with routine clinical care but are likely to remain more impaired than typically developing youth with OCD, indicating a need for longer-term support for these young people. Electronic supplementary material The online version of this article (10.1007/s00787-020-01478-8) contains supplementary material, which is available to authorized users.

Background The density of information in digital health records offers new potential opportunities for automated prediction of cost-relevant outcomes. Aims We investigated the extent to which routinely recorded data held in the electronic health record (EHR) predict priority service outcomes and whether natural language processing tools enhance the predictions. We evaluated three high priority outcomes: in-patient duration, readmission following in-patient care and high service cost after first presentation. Method We used data obtained from a clinical database derived from the EHR of a large mental healthcare provider within the UK. We combined structured data with text-derived data relating to diagnosis statements, medication and psychiatric symptomatology. Predictors of the three different clinical outcomes were modelled using logistic regression with performance evaluated against a validation set to derive areas under receiver operating characteristic curves. Results In validation samples, the full models (using all available data) achieved areas under receiver operating characteristic curves between 0.59 and 0.85 (in-patient duration 0.63, readmission 0.59, high service use 0.85). Adding natural language processing-derived data to the models increased the variance explained across all clinical scenarios (observed increase in r2 = 12–46%). Conclusions EHR data offer the potential to improve routine clinical predictions by utilising previously inaccessible data. Of our scenarios, prediction of high service use after initial presentation achieved the highest performance.

BACKGROUND: Treatment with paliperidone palmitate (PP) has been shown to reduce hospitalisation, however its effect on broader service use remains unknown. Our objectives were to describe and compare the health care professional (HCP) use of patients treated with 1-monthly PP before and after its initiation. METHODS: Data were sourced from South London and Maudsley (SLAM) electronic health records on patients diagnosed with schizophrenia, who had received 1-monthly PP for at least 365 days. We employed two mirrored image analyses to determine the number and frequency of HCP contacts in the 12 months before and after PP initiation: 1) excluding all inpatient days at the time of initiation; 2) excluding only the post-initiation days for that stay. More specifically, we looked at face-to-face, telephone contacts, days spent as an inpatient and number of active days in the service. RESULTS: Of 664 patients who had received PP (mean age 42 years), 60.1% were male, 60.1% of black ethnicity, 78.5% single, and 82.7% unemployed; 56.5% of initiations occurred during inpatient episodes. The two mirror image analyses yielded similar RESULTS: following PP initiation, inpatient bed-days were lower (mean (SD)) with the number of bed-days before and after initiation respectively: 31.6 (52.0) and 21.1 (52.9) in model 1; 45.1 (64.0) and 21.1 (52.9) in model 2; both p

Summary Background Crisis resolution and home treatment teams (CRTs) offer an alternative to hospital admission for patients undergoing mental health crises in the UK. Few studies have been done to examine predictors of relapse and readmission after contact with CRTs. Methods We used the Clinical Record Interactive Search to identify all patients receiving care from CRTs in two National Health Service (NHS) mental health trusts in London: Camden and Islington NHS Foundation Trust and South London and Maudsley NHS Foundation Trust. We used Cox regression models to examine rates and predictors of admission to acute mental health services within 1 year of contact with CRTs. Sex, age, ethnicity, marital status, social deprivation, severity of psychopathology, duration of index CRT episode, first contact with services, and diagnosis were extracted and examined as predictors of admission. Findings Between Jan 1, 2008, and Aug 31, 2014, 17 666 patients were treated by CRTs—8759 patients in the Camden and Islington trust and 8907 patients in the South London and Maudsley trust. 53·9 patients per 100 person-years (95% CI 52·1–55·8) in Camden and Islington and 51·3 patients per 100 person-years (95% CI 49·6–53·1) in South London and Maudsley were admitted to acute services within 1 year of seeing the CRT. In both cohorts, non-affective psychotic disorders (adjusted hazard ratio [HR] 1·25, 95% CI 1·09–1·44 in Camden and Islington; 1·27, 1·17–1·38 in South London and Maudsley) and age older than 65 years (1·18, 1·01–1·37 in Camden and Islington; 1·32, 1·12–1·56 in South London and Maudsley) were associated with increased risk of admission, whereas first contact with services (0·57, 0·52–0·62 in Camden and Islington; 0·69, 0·63–0·75 in South London and Maudsley), anxiety disorders (0·81, 0·69–0·96 in Camden and Islington; 0·77, 0·67–0·87 in South London and Maudsley), and longer index CRT episodes (adjusted HR per day 0·996, 0·994–0·998 in Camden and Islington; 0·989, 0·987–0·991 in South London and Maudsley) were associated with reduced risk of admission. Interpretation Past use of mental health services and a diagnosis of non-affective psychosis, which are markers of severity of mental illness, and older age, which is a marker of chronicity, are all risk factors for future relapse after interactions with CRTs. These findings might help clinicians and policy makers to offer more targeted and cost-effective services to reduce relapse rates. Funding None.

BackgroundIn cases of non-fatal self-harm, suicide notes are a major risk factor for repeated self-harm and suicide. Suicide notes can now be left on new media services, emails or text messages, as well as on paper.AimsIn a group of people who had harmed themselves, we aimed to compare new media note-leavers with paper note-leavers and characterise these groups demographically and by risk factors.MethodClinical notes of patients who presented with non-fatal self-harm to two London emergency departments were anonymously searched for mentions of new media use. These were categorised and risk factors were compared for those who had left a new media note, a paper note, or no note to establish differences in risk of note-leaving.ResultsNew media note-leaving was associated with younger age and substance use; both risk factors for repeated self-harm. However, suicidal intent remained highest in paper note-leavers.ConclusionsPaper note-leavers remain at greatest risk, however new media note leaving is still correlated with risk factors related to repeated self-harm and suicide. Clinicians should enquire about new media use during emergency department assessments of self-harm.

Objectives/AimsCatatonia is an important neuropsychiatric disorder with a high morbidity and mortality. However, due to a perception that it is very infrequent and because of the acuity of the patients, it has remained poorly studied and research has often been confined to small groups.We hypothesised that: catatonia would remain a significant clinical problem; catatonic patients would have a longer duration of admission and higher mortality; serum iron would be reduced, reflecting a systemic inflammatory response, and high rates of NMDA receptor antibody serum positivity would be observed.MethodsThis was a prospective cohort study that included patients in a large mental health trust who were diagnosed with catatonia between 2007 and 2016. We used the Clinical Records Interactive Search (CRIS) system hosted at the NIHR Maudsley Biomedical Research Centre to search the clinical records for patients with catatonia. An initial free-text search was refined by use of a natural language processing app. The results of the app were validated by three of the authors, who included patients in the analysis only if a clinician had made a diagnosis of catatonia and two or more items of the Bush-Francis Catatonia Screening Instrument were in evidence.Demographic, clinical and blood-based markers could then be extracted for these patients and compared, where relevant, to non-catatonic psychiatric patients.Results1,456 patients with catatonia (of whom 787 were psychiatric inpatients) and 37,456 psychiatric inpatient controls were identified. There was no evidence for a reduction in the rate of catatonia over time. Patients with catatonia were younger than the controls by 2.52 years (95% CI 1.30 to 3.73) and similar in gender composition. Patients with catatonia were more likely to be black (53.5% vs 24.5%, pConclusionsThis is the largest study of catatonia to date. There is evidence that catatonia is not dying out and confers high morbidity but without affecting mortality. The innate immune system does not seem to be activated, but NMDA receptor antibodies are present at higher rates than in psychiatric controls. We demonstrate that catatonia remains an important clinical problem and may be associated with neuroimmunological dysfunction.

Objective: To determine the frequency of all-cause general hospital admissions for individuals with personality disorder (PD) in a large clinical population using linked secondary mental healthcare and hospitalisation data.Method: A retrospective cohort study, using anonymised electronic mental health records from South London and Maudsley NHS Foundation Trust (SLaM), linked to Hospital Episodes Statistics in England. People with PD aged 15 years or older, receiving care within SLaM between April 2007 and March 2013, were identified and compared to residents from the local catchment area. Standardised admission ratios (SARs) were calculated for all major categories of causes of general hospital admission for this defined group, with local residents in 2011 UK Census as the standard population.Results: For the 7,677 people identified with PD, SAR for all causes of admission was 2.75 (95% CI: 2.70, 2.81). Both men and women with PD had increased SARs across multiple ICD-10 categories, including circulatory, respiratory, digestive, nervous, and musculoskeletal system disorders, and endocrine, blood and infectious disorders. Sensitivity analysis (removing the impact of repeated admissions by same individual for same diagnosis in the same year) yielded similar findings.Conclusions: By comparison with members of the general population, individuals with a diagnosis of personality disorder are at significantly higher risk of hospital admission resulting from a wide range of physical health problems.

Pregnancy in women with severe mental illness is associated with adverse outcomes for mother and infant. There are limited data on prevalence and predictors of relapse in pregnancy. A historical cohort study using anonymised comprehensive electronic health records from secondary mental health care linked with national maternity data was carried out. Women with a history of serious mental illness who were pregnant (2007–2011), and in remission at the start of pregnancy, were studied; severe relapse was defined as admission to acute care or self-harm. Predictors of relapse were analysed using random effects logistic regression to account for repeated measures in women with more than one pregnancy in the study period. In 454 pregnancies (389 women) there were 58 (24%) relapses in women with non-affective psychoses and 25 (12%) in women with affective psychotic or bipolar disorders. Independent predictors of relapse included non-affective psychosis (adjusted OR = 2.03; 95% CI = 1.16–3.54), number of recent admissions (1.37; 1.03–1.84), recent self-harm (2.24; 1.15–4.34), substance use (2.15; 1.13–4.08), smoking (2.52; 1.26–5.02) and non-white ethnicity (black ethnicity: 2.37; 1.23-4.57, mixed/other ethnicity: 2.94; 1.32-6.56). Women on no regular medication throughout first trimester were also at greater risk of relapse in pregnancy (1.99; 1.05–3.75). There was no interaction between severity of illness and medication status as relapse predictors. Therefore, women with non-affective psychosis and higher number of recent acute admissions are at significant risk of severe relapse in pregnancy. Continuation of medication in women with severe mental illness who become pregnant may be protective.

Summary Background Evidence regarding the mental health needs of trafficked people is limited; however, prevalence of depression and post-traumatic stress disorder is high among trafficked people who are in contact with shelter services. We aimed to investigate the sociodemographic and clinical characteristics of trafficked people with severe mental illness. Methods We did a historical cohort study of trafficked people in contact with secondary mental health services in South London, UK, between Jan 1, 2006, and July 31, 2012. We searched and retrieved comprehensive clinical electronic health records for over 200 000 patients from the Case Register Interactive Search database to identify trafficked patients. A matched cohort of non-trafficked adults was generated by simple computer-generated random selection of potential controls for each case within the parameters of matching criteria. We extracted data on sociodemographic and clinical characteristics and abuse history, and used multiple imputation to deal with missing data. We fitted logistic regression models to compare trafficked and non-trafficked patients. Findings We identified 133 trafficked patients, including 37 children. 78 (81%) of 96 adults and 25 (68%) of 37 children were female. 19 (51%) of 37 children were trafficked for sexual exploitation. Among both adults and children, the most commonly recorded diagnoses were post-traumatic stress disorder, severe stress, or adjustment disorder (27 adults [28%] and ten children [27%]) and affective disorders (33 adults [34%] and ten children [27%]). Records documented childhood physical or sexual abuse among trafficked adults (41 [43%]) and children (28 [76%]), and adulthood abuse among trafficked adults (58 [60%]). Trafficked adults were more likely to be compulsorily admitted as a psychiatric inpatient than non-trafficked adults (adjusted odds ratio 7·61, 95% CI 2·18–26·60; p=0·002) and had longer admissions (1·48, 1·01–2·15; p=0·045). No association was found between trafficking status and either adverse pathway into care (adjusted odds ratio 0·91, 95% CI 0·40–2·05; p=0·82) or substance misuse problems (0·55, 0·27–1·17; p=0·12). Interpretation Severe mental illness in trafficked people is associated with longer admissions and high levels of abuse before and after trafficking. Evidence is needed on the effectiveness of interventions to promote recovery for this vulnerable group. Funding Department of Health Policy Research Programme.

BACKGROUND: Opioid misusers have recognized high mortality but the influence of psychiatric comorbidity in excess cause-specific mortality is unclear.METHODS: Opioid use disorder (OUD) patients were identified in the South London and Maudsley Case Register. Deaths were identified through database linkage to the national mortality dataset. Standard mortality ratios were calculated to compare mortality risk with the general population. Cox and competing risk regression models were used to investigate the effect of psychiatric comorbidity and psychological health on all-cause and cause-specific mortality (respectively) in OUD patients.RESULTS: Of 4837 OUD patients, 176 had died. Mortality rates were substantially higher than the general population (SMR 4.23; 95%CI 3.63-4.90). Among those with OUD, comorbid personality disorder (PD) and comorbid alcohol use disorder (AUD) was associated with increased all-cause mortality in all models, including the fully adjusted model, controlling for socio-demographic factors, severity of drug use, risk behaviours and physical health (HR2.15, 95%CI 1.17-3.95; HR2.28, 95%CI 1.54-3.36). AUD was associated with increased risk of fatal overdose (HR2.57, 95%CI 1.26-5.26) and hepatic-related deaths (HR7.26, 95%CI 2.79-18.86). Individuals with OUD and comorbid PD had almost four times greater risk of liver related deaths compared to those without PD (HR3.76, 95%CI 1.21-11.74). Comorbid severe mental illness and poor psychological health were not associated with increased mortality.CONCLUSIONS: This study highlights the importance of assessment for PD and AUD in OUD patients in order to identify individuals at substantially elevated mortality risk to enable a more personalized approach to their medical care.

Aims and methodTo assess the usefulness of the electronic patient record, we used the search engine Clinical Record Interactive Search (CRIS) to scan all acute admissions during 2008 for possible substance use disorders. In addition, screening interviews were undertaken with 75 in-patients, and documentation in their files was compared with results of screening interviews.ResultsOf 839 acute admissions during 2008, 47% of males and 29% of females had reference to a substance misuse problem in their file. Documentation was unsystematic and inconsistent and mostly occurred in progress notes rather than in structured questionnaires. Screening interviews and manual review of files of 75 current in-patients confirmed that substance use disorders were common, but poorly documented.Clinical implicationsThe study highlights the power of search engines in scanning electronic clinical records, but also identified the limitations of unsystematic documentation in research and practice. Mental health staff were reluctant to diagnose or rate severity of substance misuse problems.

Background: Understanding the drivers of heterogeneous progression in dementia has huge implications for recruitment to clinical trails and care planning. One way to investigate the factors contributing to this heterogeneity is to stratify subjects by similar patterns of change and compare the characteristics of the sub-populations identified. We applied this approach to routinely collected electronic health records from the South London and Maudesly NHS Foundation Trust (SLAM). Methods: This retrospective study includes 3441 patients with at least three MMSE scores recorded and available for research through the SLAM clinical record interactive search system (CRIS). A Latent Class Growth Analysis was used to identify key trajectories of decline. Information on age, gender, ethnicity, qualification levels, cohabiting status, retirement status, Health of Nation Outcome Scales (HoNOS) and medications were obtained to describe characteristics of the identified trajectory sub-populations in a multivariable multinomial regression analysis. Results: We identified six trajectories of cognitive decline. Four of these trajectories differed in initial MMSE score, and showed increased rate of decline with lower initial MMSE. Two trajectories had very similar initial MMSE scores but differed in the rate of decline. Exploring these trajectories further, the severity of cognitive problems at baseline and prescription of Donepezil and Amlodipine was significantly higher in the slower declining trajectory. In the faster declining trajectory, severity of behavioral problems and prescription of sertraline was significantly higher. Conclusions: Most of the trajectories differed by initial MMSE and thus likely represented patients at different disease stages, however differences in behavioral problems, antihypertensive, antidepressant and dementia medication prescription may be indicators of future rate of cognitive decline. Further information is required on depression and hypertensive comorbidities to explore these findings in greater detail.

Objective To determine if aggression, hallucinations or delusions, and depression contribute to excess mortality risk observed in individuals with serious mental illness (SMI). Methods We identified SMI cases (schizophrenia, schizoaffective and bipolar disorder) aged ≥ 15 years in a large secondary mental healthcare case register linked to national mortality tracing. We modelled the effect of specific symptoms (HoNOS subscales) on all-cause mortality using Cox regression. Results We identified 6880 SMI cases (242 deaths) occurring 2007–2010. Bipolar disorder was associated with reduced mortality risk compared to schizophrenia (HR 0.7; 95% CI 0.4–0.96; p = 0.028). Mortality was not significantly associated with hallucinations and delusions or overactive–aggressive behaviour, but was associated with physical illness/disability. There was a positive association between mortality and subclinical depression among individuals with schizophrenia (HR 1.5; 1.1–2.2; p = 0.019) but a negative association with subclinical and more severe depression among those with schizoaffective disorder (HR 0.1; 0.02–0.4; p = 0.001 and 0.3; 0.1–0.8; p = 0.021, respectively). Conclusions The recognised increased risk of mortality in SMI did not appear to be influenced by severity of hallucinations, delusions, or overactive–aggressive behaviour. Physical illness and lifestyle may need to be addressed and the relationship between depression and mortality requires further investigation.

Background People with substance use disorders (SUDs) have increased risk of mortality but risk in sub-groups is poorly understood. Methods SUD cases, aged 15 years or older, were identified in the South London and Maudsley Case Register which contains over 150,000 specialist mental healthcare and addictions service users linked to regular national mortality tracing. Standardized mortality ratios (SMRs) for the period 2007–2009 were calculated based on expected numbers of deaths for England and Wales in 2008 then stratified by gender, age, ethnicity, and type of substance use disorder. Life expectancies at birth were estimated. Results We detected 10,927 cases with a primary substance use disorder diagnosis prior to 2010, who were active to South London and Maudsley NHS Foundation Trust services between 2007 and 2009. Alcohol and opioid use disorders were the most common disorders (45.4% and 44.2% of the SUD cohort respectively) and were associated with increased mortality (SMRs 4.04 and 4.85 respectively). Subgroups at particularly high risk were women with opioid use disorder (SMR 7.32) and those under the age of 45 years with alcohol use disorder (SMR 9.25). SMRs associated with alcohol and opioid use disorders diminished with age. Life expectancies of individuals with alcohol and opioid use disorders were reduced by 9–17 years compared to national norms. Conclusions Those under 45 years with alcohol use disorder and women with opioid use disorder are at particularly high risk of mortality. More targeted health care is required to address the specific needs of these vulnerable subgroups.

BackgroundThe increasingly large sample size requirements of modern adult mental health research suggests the need for a data collection and diagnostic application that can be used across a broad range of clinical and research populations.AimsTo develop a data collection and diagnostic application that can be used across a broad range of clinical and research settings.MethodWe expanded and redeveloped the OPCRIT system into a broadly applicable diagnostic and data-collection package and carried out an interrater reliability study of this new tool.ResultsOPCRIT+ performed well in an interrater reliability study with relatively inexperienced clinicians, giving a combined, weighted kappa of 0.70 for diagnostic reliability.ConclusionsOPCRIT+ showed good overall interrater reliability scores for diagnoses. It is now incorporated in the electronic patient record of the Maudsley and associated hospitals. OPCRIT+ can be downloaded free of charge at http://sgdp.iop.kcl.ac.uk/opcritplus.

Background Human trafficking is a global crime and human rights violation. Although research has demonstrated a high prevalence of mental disorder among trafficked people and that trafficked people are in contact with mental health services, little is known about mental health professionals’ experiences of identifying and providing care for trafficked people. This study aimed to understand how people are identified as trafficked within mental health services and the challenges professionals experience in responding to trafficked people’s mental health needs. Method Qualitative study of electronic health records of trafficked people in contact with secondary mental health services in South East London, England. Comprehensive clinical electronic health records for over 200,000 patients in contact with secondary mental health services in South London were searched and retrieved to identify trafficked patients. Content analysis was used to establish how people were identified as trafficked, and thematic analysis was used to explore the challenges experienced in responding to mental health needs. Results The sample included 130 trafficked patients, 95 adults and 35 children. In 43 % (41/95) of adult cases and 63 % (22/35) child cases, mental health professionals were informed that their patient was a potential victim of trafficking by another service involved in their patient’s care. Cases were also identified through patients disclosing their experiences of exploitation and abuse. Key challenges faced by staff included social and legal instability, difficulties ascertaining history, patients’ lack of engagement, availability of services, and inter-agency working. Conclusions Training to increase awareness, encourage helpful responses, and inform staff about the available support options would help to ensure the mental health needs of trafficked people are met. Further research is needed to establish if these challenges are similar in other health settings. Electronic supplementary material The online version of this article (doi:10.1186/s12888-015-0679-3) contains supplementary material, which is available to authorized users.

Clozapine can cause severe adverse effects yet it is associated with reduced mortality risk. We test the hypothesis this association is due to increased clinical monitoring and investigate risk of premature mortality from natural causes. We identified 14 754 individuals (879 deaths) with serious mental illness (SMI) including schizophrenia, schizoaffective and bipolar disorders aged ≥ 15 years in a large specialist mental healthcare case register linked to national mortality tracing. In this cohort study we modeled the effect of clozapine on mortality over a 5-year period (2007–2011) using Cox regression. Individuals prescribed clozapine had more severe psychopathology and poorer functional status. Many of the exposures associated with clozapine use were themselves risk factors for increased mortality. However, we identified a strong association between being prescribed clozapine and lower mortality which persisted after controlling for a broad range of potential confounders including clinical monitoring and markers of disease severity (adjusted hazard ratio 0.4; 95% CI 0.2–0.7; p = .001). This association remained after restricting the sample to those with a diagnosis of schizophrenia or those taking antipsychotics and after using propensity scores to reduce the impact of confounding by indication. Among individuals with SMI, those prescribed clozapine had a reduced risk of mortality due to both natural and unnatural causes. We found no evidence to indicate that lower mortality associated with clozapine in SMI was due to increased clinical monitoring or confounding factors. This is the first study to report an association between clozapine and reduced risk of mortality from natural causes.

ObjectiveStandardised mortality ratios are twice the population average in the year following a mental health admission, yet there is a relative paucity of research on uptake of general medical care in psychiatric inpatients.MethodsA retrospective database analysis was performed to ascertain the frequency of acute medical care usage by psychiatric inpatients. Data was gathered through a static linkage between anonymised clinical records in a large UK Mental Health Provider and the national hospital activity database (Hospital Episode Statistics (HES)) over one year from 2010 to 2011.ResultsOver the year, 10.4% of the 8023 psychiatric admission episodes included at least one night in a general hospital during that psychiatric inpatient stay, while 12.0% of psychiatry admission episodes entailed an Emergency Department (ED) visit. Over the course of the full year, of the 4,674 people admitted to the Mental Health Provider at least once, 16.0% were admitted to a general hospital while registered as a mental health inpatient and 18.0% were seen in the Emergency Department (ED). Patients were simultaneously registered as occupying beds in both general and psychiatric hospitals for a total of 5163 bed days at a cost of £2.4 million over the year.ConclusionThis large population based linkage study indicates a high rate of general hospital utilisation by psychiatric inpatients in an independent mental health provider. The need for combined, flexible and practical approaches to the medical care of psychiatric inpatients is highlighted, to reduce unplanned care and provide treatment in the site best suited to the patient’s needs.

Background Most women with psychotic disorders and bipolar disorders have children but their pregnancies are at risk of adverse psychiatric and fetal outcome. The extent of modifiable risk factors – both clinical and socio-demographic – is unclear as most studies have used administrative data or recruited from specialist tertiary referral clinics. We therefore aimed to investigate the socio-demographic and clinical characteristics of an epidemiologically representative cohort of pregnant women with affective and non-affective severe mental illness. Methods Women with severe mental illness were identified from a large electronic mental health case register in south London, and a data linkage with national maternity Hospital Episode Statistics identified pregnancies in 2007–2011. Data were extracted using structured fields, text searching and natural language processing applications. Results Of 456 pregnant women identified, 236 (51.7%) had schizophrenia and related disorders, 220 (48.3%) had affective psychosis or bipolar disorder. Women with schizophrenia and related disorders were younger, less likely to have a partner in pregnancy, more likely to be black, to smoke or misuse substances and had significantly more time in the two years before pregnancy in acute care (inpatient or intensive home treatment) compared with women with affective disorders. Both groups had high levels of domestic abuse in pregnancy (recorded in 18.9%), were from relatively deprived backgrounds and had impaired functioning measured by the Health of the Nation Outcome Scale. Women in the affective group were more likely to stop medication in the first trimester (39% versus 25%) whereas women with non-affective psychoses were more likely to switch medication. Conclusions A significant proportion of women, particularly those with non-affective psychoses, have modifiable risk factors requiring tailored care to optimize pregnancy outcomes. Mental health professionals need to be mindful of the possibility of pregnancy in women of childbearing age and prescribe and address modifiable risk factors accordingly. Electronic supplementary material The online version of this article (doi:10.1186/s12888-015-0451-8) contains supplementary material, which is available to authorized users.

IntroductionThe symptoms of bipolar disorder are sometimes misrecognised for unipolar depression and inappropriately treated with antidepressants. This may be associated with increased risk of developing mania. However, the extent to which this depends on what type of antidepressant is prescribed remains unclear.AimsTo investigate the association between different classes of antidepressants and subsequent onset of mania/bipolar disorder in a real-world clinical setting.MethodsData on prior antidepressant therapy were extracted from 21,012 adults with unipolar depression receiving care from the South London and Maudsley NHS Foundation Trust (SLaM). multivariable Cox regression analysis (with age and gender as covariates) was used to investigate the association of antidepressant therapy with risk of developing mania/bipolar disorder.ResultsIn total, 91,110 person-years of follow-up data were analysed (mean follow-up: 4.3 years). The overall incidence rate of mania/bipolar disorder was 10.9 per 1000 person-years. The peak incidence of mania/bipolar disorder was seen in patients aged between 26 and 35 years (12.3 per 1000 person-years). The most frequently prescribed antidepressants were SSRIs (35.5%), mirtazapine (9.4%), venlafaxine (5.6%) and TCAs (4.7%). Prior antidepressant treatment was associated with an increased incidence of mania/bipolar disorder ranging from 13.1 to 19.1 per 1000 person-years. Multivariable analysis indicated a significant association with SSRIs (hazard ratio 1.34, 95% CI 1.18–1.52) and venlafaxine (1.35, 1.07–1.70).ConclusionsIn people with unipolar depression, antidepressant treatment is associated with an increased risk of subsequent mania/bipolar disorder. These findings highlight the importance of considering risk factors for mania when treating people with depression.Disclosure of interestThe authors have not supplied their declaration of competing interest.

IntroductionThere are often substantial delays before diagnosis and initiation of treatment in people bipolar disorder. Increased delays are a source of considerable morbidity among affected individuals.AimsTo investigate the factors associated with delays to diagnosis and treatment in people with bipolar disorder.MethodsRetrospective cohort study using electronic health record data from the South London and Maudsley NHS Foundation Trust (SLaM) from 1364 adults diagnosed with bipolar disorder. The following predictor variables were analysed in a multivariable Cox regression analysis on diagnostic delay and treatment delay from first presentation to SLaM: age, gender, ethnicity, compulsory admission to hospital under the UK Mental Health Act, marital status and other diagnoses prior to bipolar disorder.ResultsThe median diagnostic delay was 62 days (interquartile range: 17–243) and median treatment delay was 31 days (4–122). Compulsory hospital admission was associated with a significant reduction in both diagnostic delay (hazard ratio 2.58, 95% CI 2.18–3.06) and treatment delay (4.40, 3.63–5.62). Prior diagnoses of other psychiatric disorders were associated with increased diagnostic delay, particularly alcohol (0.48, 0.33–0.41) and substance misuse disorders (0.44, 0.31–0.61). Prior diagnosis of schizophrenia and psychotic depression were associated with reduced treatment delay.ConclusionsSome individuals experience a significant delay in diagnosis and treatment of bipolar disorder, particularly those with alcohol/substance misuse disorders. These findings highlight a need to better identify the symptoms of bipolar disorder and offer appropriate treatment sooner in order to facilitate improved clinical outcomes. This may include the development of specialist early intervention services.Disclosure of interestThe authors have not supplied their declaration of competing interest.

IntroductionMood instability is an important problem but has received relatively little research attention. Natural language processing (NLP) is a novel method, which can used to automatically extract clinical data from electronic health records (EHRs).AimsTo extract mood instability data from EHRs and investigate its impact on people with mental health disorders.MethodsData on mood instability were extracted using NLP from 27,704 adults receiving care from the South London and Maudsley NHS Foundation Trust (SLaM) for affective, personality or psychotic disorders. These data were used to investigate the association of mood instability with different mental disorders and with hospitalisation and treatment outcomes.ResultsMood instability was documented in 12.1% of people included in the study. It was most frequently documented in people with bipolar disorder (22.6%), but was also common in personality disorder (17.8%) and schizophrenia (15.5%). It was associated with a greater number of days spent in hospital (B coefficient 18.5, 95% CI 12.1–24.8), greater frequency of hospitalisation (incidence rate ratio 1.95, 1.75–2.17), and an increased likelihood of prescription of antipsychotics (2.03, 1.75–2.35).ConclusionsUsing NLP, it was possible to identify mood instability in a large number of people, which would otherwise not have been possible by manually reading clinical records. Mood instability occurs in a wide range of mental disorders. It is generally associated with poor clinical outcomes. These findings suggest that clinicians should screen for mood instability across all common mental health disorders. The data also highlight the utility of NLP for clinical research.Disclosure of interestThe authors have not supplied their declaration of competing interest.

Aims and MethodClinicians are often required, by managers, to provide information that does not appear relevant to clinical practice. Rooted in compromise, an outcome-based information model that supports practice and also provides information for managers was developed. A 9–month pilot project at three sites in South-East London took place to test the feasibility of this model in real clinical settings.ResultsAccurate data were reliably collected. Clinicians at participating sites agreed the model produced potentially useful information and, on condition that support is provided, continue to collect data voluntarily.Clinical ImplicationsThis is not an exclusively clinical model. However, because it also fulfils management needs there is a better chance that clinicians will get the support they need.

Background Higher mortality has been found for people with serious mental illness (SMI, including schizophrenia, schizoaffective disorders, and bipolar affective disorder) at all age groups. Our aim was to characterize vulnerable groups for excess mortality among people with SMI, substance use disorders, depressive episode, and recurrent depressive disorder. Methods A case register was developed at the South London and Maudsley National Health Services Foundation Trust (NHS SLAM), accessing full electronic clinical records on over 150,000 mental health service users as a well-defined cohort since 2006. The Case Register Interactive Search (CRIS) system enabled searching and retrieval of anonymised information since 2008. Deaths were identified by regular national tracing returns after 2006. Standardized mortality ratios (SMRs) were calculated for the period 2007 to 2009 using SLAM records for this period and the expected number of deaths from age-specific mortality statistics for the England and Wales population in 2008. Data were stratified by gender, ethnicity, and specific mental disorders. Results A total of 31,719 cases, aged 15 years old or more, active between 2007-2009 and with mental disorders of interest prior to 2009 were detected in the SLAM case register. SMRs were 2.15 (95% CI: 1.95-2.36) for all SMI with genders combined, 1.89 (1.64-2.17) for women and 2.47 (2.17-2.80) for men. In addition, highest mortality risk was found for substance use disorders (SMR = 4.17; 95% CI: 3.75-4.64). Age- and gender-standardised mortality ratios by ethnic group revealed huge fluctuations, and SMRs for all disorders diminished in strength with age. The main limitation was the setting of secondary mental health care provider in SLAM. Conclusions Substantially higher mortality persists in people with serious mental illness, substance use disorders and depressive disorders. Furthermore, mortality risk differs substantially with age, diagnosis, gender and ethnicity. Further research into specific risk groups is required.

Background Case registers have been used extensively in mental health research. Recent developments in electronic medical records, and in computer software to search and analyse these in anonymised format, have the potential to revolutionise this research tool. Methods We describe the development of the South London and Maudsley NHS Foundation Trust (SLAM) Biomedical Research Centre (BRC) Case Register Interactive Search tool (CRIS) which allows research-accessible datasets to be derived from SLAM, the largest provider of secondary mental healthcare in Europe. All clinical data, including free text, are available for analysis in the form of anonymised datasets. Development involved both the building of the system and setting in place the necessary security (with both functional and procedural elements). Results Descriptive data are presented for the Register database as of October 2008. The database at that point included 122,440 cases, 35,396 of whom were receiving active case management under the Care Programme Approach. In terms of gender and ethnicity, the database was reasonably representative of the source population. The most common assigned primary diagnoses were within the ICD mood disorders (n = 12,756) category followed by schizophrenia and related disorders (8158), substance misuse (7749), neuroses (7105) and organic disorders (6414). Conclusion The SLAM BRC Case Register represents a 'new generation' of this research design, built on a long-running system of fully electronic clinical records and allowing in-depth secondary analysis of both numerical, string and free text data, whilst preserving anonymity through technical and procedural safeguards.

Introduction Higher all-cause mortality and shorter life expectancies for people with severe mental illness (SMI, including schizophrenia, schizoaffective disorder, and bipolar disorder) have been frequently reported. Cancer contributes a substantial proportion of mortality (20 to 30%) as the second or third leading cause of death among people with SMI. Outcomes of cancer incidence studies in SMI were considerably heterogeneous, varying by cancer types and mental disorders. Objectives/Aims To compare the incidence of overall and each type of cancer between people with SMI in southeast London and general population in UK. Methods Using the anonymised linkage between a regional monopoly secondary mental health service provider covering four southeast London boroughs and a population-based cancer register, we carried out the comparisons of cancer incidences between people with SMI and general population by age- and gender-standardisation in 2011. Results Among SMI subjects with cancer (N=105), the most common cancer types were lung and colorectal cancer followed by breast cancer for women and prostate cancer for men in this area. Standardised incidence ratios (SIRs) for all cancers in SMI were 1.19 (95% CI: 0.97-1.44) overall, 2.43 (95% CI: 1.98-2.94) in men (n=61), and 0.98 (95% CI: 0.71-1.31) in women (n=44). Based on relatively small case numbers, raised SIRs were found for lung cancer in men (SIR=7.57, 95% CI: 3.04-15.6) and women (SIR=7.61, 95% CI: 2.79-16.6), and in women for colorectal (SIR=7.85, 95%CI: 2.55-18.32) and breast cancer (SIR=7.86, 95% CI: 4.58-12.59). Conclusions Specific pattern of elevated risks of cancer incidence were found for people with SMI.

Introduction A recent systematic review found a high prevalence of violence and mental distress among women trafficked for sexual exploitation; no data were identified for trafficked men and children. Objectives To describe the clinical characteristics of trafficked people in contact with a large inner city mental health service compared with a non-trafficked cohort. Aims To investigate whether, compared with a non-trafficked cohort, trafficked people would be significantly more likely to have co-morbid disorders and have significantly smaller improvements in functioning at the end of an episode of care. Methods Study population: mental health service users who had been trafficked for exploitation and a non-trafficked service user cohort matched for gender and age. Data source: The South London and Maudsley NHS Trust (SLaM) Biomedical Research Centre Case Register Interactive Search (CRIS) database of anonymised full patient records (2006–2012). Results We identified case records of 135 people who had been trafficked. 104 (77%) were female; age at first SLaM contact ranged from 8 to 49 years (mean 23.6, SD 8.0). 38 (28%) of the trafficked service users received psychiatric care from an emergency department. Depression (28.1%, n = 38), PTSD (19.3%, n = 26), non-affective psychoses (12.6%, n = 17) were the most frequently recorded diagnoses among trafficked service users. Further analysis is in progress and scheduled for completion by March 2013. Conclusions Significant numbers of trafficked people were seen in an inner-city mental health service; services therefore need to understand their complex needs.

Background Compared to the general population, people with schizophrenia have a substantially higher risk of premature mortality which translates into a 10–15 year reduction in life expectancy. The aim of this investigation was to determine if symptoms (including aggression, hallucinations or delusions, and depression) or the environmental and functional status of people with schizophrenia contribute to the high mortality risk observed in this patient group. Methods We identified cases of schizophrenia, aged ≥15 years in a large secondary mental healthcare case register linked to national mortality tracing. We modelled the effect of specific symptoms, activities of daily living (ADLs), living conditions, occupational and recreational activities (Health of the Nation Outcome Scale [HoNOS] subscales) on all-cause mortality over a 4-year observation period (2007-10) using Cox regression. Results We identified 4270 schizophrenia cases (170 deaths) in the observation period. After controlling for a broad range of covariates, mortality was not significantly associated with hallucinations and delusions or overactive-aggressive behaviour, but was associated with subclinical depression (adjusted HR 1.5; 95% CI 1.1-2.2) and ADL impairment (adjusted HR 1.8; 95% CI 1.2-2.9). Conclusions Severity of symptoms, such as delusions and hallucinations, was less important in predicting mortality than subclinical depression and difficulties carrying out activities of daily living. The overall picture appears to be one where the highest all-cause mortality risk is in service users who are least visible to clinical teams.