Search

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.

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.

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.

Introduction Longitudinal cognitive change before and after acetyl cholinesterase inhibitor (AChEI) treatment initiation in Alzheimer's disease has never been described previously in a representative clinical population. Objectives To model longitudinal changes in cognitive function for before and after AChEI prescription. Aims To further investigate differences in response by cognitive function at treatment initiation. Method A retrospective longitudinal analysis was carried out of all 1843 patients from the South London and Maudsley NHS Foundation Trust (a large mental health provider to a catchment population of approximately 1.2 m) who were prescribed AChEIs between 2003–10 and had a minimum of one MMSE score within 1 year before treatment initiation and one MMSE score within 3 years after this. Manually extracted MMSE scores were analyzed over this period using three-piece linear mixed models. Results Rates of MMSE change were −1.9 (95% CI −2.3,−1.4) in the year before treatment initiation, +1.3 (0.9,1.7) in the 6 months after treatment initiation, and −2.4 (−2.6,−2.3) from 6 months to 3 years. The difference between pre-treatment and 6-month-post-treatment slopes was −0.6 (−1.8,0.6) at baseline (treatment initiation) MMSE of 25 or over, +2.7 (1.7,3.7) at MMSE 21–24, and +4.6 (3.6,5.7) at MMSE 10–20. Conclusion In this naturalistic sample, a clear cognitive response to AChEI treatment was observed over the first six months followed by an unchanged decline. Response was substantially higher for patients with lower MMSE scores at treatment initiation.