Can risk assessment predict suicide in secondary mental healthcare? Findings from the South London and Maudsley NHS Foundation Trust Biomedical Research Centre (SLaM BRC) Case Register.

PURPOSE: The predictive value of suicide risk assessment in secondary mental healthcare remains unclear. This study aimed to investigate the extent to which clinical risk assessment ratings can predict suicide among people receiving secondary mental healthcare. METHODS: Retrospective inception cohort study (n = 13,758) from the South London and Maudsley NHS Foundation Trust (SLaM) (London, UK) linked with national mortality data (n = 81 suicides). Cox regression models assessed survival from the last suicide risk assessment and ROC curves evaluated the performance of risk assessment total scores. RESULTS: Hopelessness (RR = 2.24, 95% CI 1.05-4.80, p = 0.037) and having a significant loss (RR = 1.91, 95% CI 1.03-3.55, p = 0.041) were significantly associated with suicide in the multivariable Cox regression models. However, screening statistics for the best cut-off point (4-5) of the risk assessment total score were: sensitivity 0.65 (95% CI 0.54-0.76), specificity 0.62 (95% CI 0.62-0.63), positive predictive value 0.01 (95% CI 0.01-0.01) and negative predictive value 0.99 (95% CI 0.99-1.00). CONCLUSIONS: Although suicide was linked with hopelessness and having a significant loss, risk assessment performed poorly to predict such an uncommon outcome in a large case register of patients receiving secondary mental healthcare.

Suicide completion in secondary mental healthcare: a comparison study between schizophrenia spectrum disorders and all other diagnoses.

BACKGROUND: Suicide completion is a tragic outcome in secondary mental healthcare. However, the extent to which demographic and clinical characteristics, suicide method and service use-related factors vary across psychiatric diagnoses remains poorly understood, particularly regarding differences between 'schizophrenia spectrum disorders (SSD)' and 'all other diagnoses', which may have implications for suicide prevention in high risk groups. METHODS: 308 patients who died by suicide over 2007-2011 were identified from the South London and Maudsley NHS Foundation Trust Biomedical Research Centre Case Register. Demographic, clinical, services use-related factors, 'full risk assessment' ratings and the Health of the Nation Outcome Scale (HONOS) scores were compared across psychiatric diagnoses. Specifically, differences between patients with and without SSD were investigated. RESULTS: Patients with SSD ended their lives at a younger age, were more frequently of Black ethnicity and had higher levels of social deprivation than other diagnoses. Also, these patients were more likely to have HONOS and 'risk assessment' completed. However, patients who had no SSD scored significantly higher on 'self-injury' and 'depression' HONOS items and they were more likely to have the following 'risk assessment' items: 'suicidal ideation', 'hopelessness', 'feeling no control of life', 'impulsivity' and 'significant loss'. Of note, 'disengagement' was more common in patients with SSD, although they had been seen by the staff closer to the time of suicide than in all-other diagnoses. Whilst 'hanging' was the most common suicide method amongst patients with non-SSD, most service users with a SSD diagnosis used 'jumping' (from heights or in front of a vehicle). CONCLUSIONS: Suicide completion characteristics varied between SSD and other diagnoses in patients receiving secondary mental healthcare. In particular, although clinicians tend to more frequently recognize suicide risk as a focus of concern in patients who have SSD, who are therefore more likely to have a detailed risk assessment documented; 'known' suicide risk factors appear to be more relevant in patients with non-SSD. Hence, the classic suicide prevention model might be of little use for SSD.

Abuse and other correlates of common mental disorders in youth: a cross-sectional study in Goa, India.

PURPOSE: There is a paucity of known correlates of common mental disorders (CMDs) among the youth age group in India. This analysis aims to determine risk factors associated with a probable diagnosis of CMD in a youth sample in India. METHODS: This is a secondary analysis of data collected via a door-to-door (community) survey of 3,662 youth (aged 16-24 years) in selected urban and rural areas in Goa. The urban and rural areas were selected based on their engagement with a Goan-based mental health charity organisation, Sangath. Point prevalence of CMD was estimated using the general health questionnaire-12 (GHQ-12). Multivariate logistic regression analyses determined factors associated with CMD and associations were stratified by gender. RESULTS: In total, 3,649 (1,796 urban; 1,853 rural) youth were assessed for probable diagnosis of CMD. There was an almost equal ratio of males (49 %) to females (51 %) in the sample. During the time of the survey, 91 % of the sample was residing with parents, with 83 % being between the ages of 22 and 24 years living with parents. A small proportion of the sample never attended school (1.1 %) with the rest either educated, employed or unemployed. The point prevalence of probable CMD in the sample was 7.87 %; 95 % CI 7.01-8.80 %. Those living in urban areas had a higher prevalence of CMD (9.12 %; 95 % CI 7.90-10.52 %) compared to those living in rural areas (6.60 %; 95 % CI 5.50-7.82 %). After adjusting for a range of potential confounders, independent risk factors for CMD were being older, i.e., between 22- and 24-years old, (OR 1.60; 95 % CI 1.10-2.24; p = 0.015), residing in urban areas (OR 1.51; 95 % CI 1.12-2.04; p = 0.007), physical abuse (beaten in the last 3 months) by parents, teachers or others (OR 3.10; 95 % CI 2.11-4.51; p < 0.001), sexual harassment (OR 2.01; 95 % CI 1.30-3.20; p = 0.003) and sexual abuse (OR 2.54; 95 % CI 1.94-3.33; p < 0.001). Being able to talk about personal problems (OR 0.52; 95 % CI 0.34-0.80; p = 0.003) was a protective factor. After stratifying by gender, sexual harassment, physical and sexual abuse were associated with a likely CMD diagnosis in females and males. CONCLUSIONS: Sexual and recent physical abuses were independent risk factors for CMD in both genders. In addition, being older and being able to discuss problems were associated with CMD diagnosis in females but not in males.

Development and evaluation of a de-identification procedure for a case register sourced from mental health electronic records.

BACKGROUND: Electronic health records (EHRs) provide enormous potential for health research but also present data governance challenges. Ensuring de-identification is a pre-requisite for use of EHR data without prior consent. The South London and Maudsley NHS Trust (SLaM), one of the largest secondary mental healthcare providers in Europe, has developed, from its EHRs, a de-identified psychiatric case register, the Clinical Record Interactive Search (CRIS), for secondary research. METHODS: We describe development, implementation and evaluation of a bespoke de-identification algorithm used to create the register. It is designed to create dictionaries using patient identifiers (PIs) entered into dedicated source fields and then identify, match and mask them (with ZZZZZ) when they appear in medical texts. We deemed this approach would be effective, given high coverage of PI in the dedicated fields and the effectiveness of the masking combined with elements of a security model. We conducted two separate performance tests i) to test performance of the algorithm in masking individual true PIs entered in dedicated fields and then found in text (using 500 patient notes) and ii) to compare the performance of the CRIS pattern matching algorithm with a machine learning algorithm, called the MITRE Identification Scrubber Toolkit - MIST (using 70 patient notes - 50 notes to train, 20 notes to test on). We also report any incidences of potential breaches, defined by occurrences of 3 or more true or apparent PIs in the same patient's notes (and in an additional set of longitudinal notes for 50 patients); and we consider the possibility of inferring information despite de-identification. RESULTS: True PIs were masked with 98.8% precision and 97.6% recall. As anticipated, potential PIs did appear, owing to misspellings entered within the EHRs. We found one potential breach. In a separate performance test, with a different set of notes, CRIS yielded 100% precision and 88.5% recall, while MIST yielded a 95.1% and 78.1%, respectively. We discuss how we overcome the realistic possibility - albeit of low probability - of potential breaches through implementation of the security model. CONCLUSION: CRIS is a de-identified psychiatric database sourced from EHRs, which protects patient anonymity and maximises data available for research. CRIS demonstrates the advantage of combining an effective de-identification algorithm with a carefully designed security model. The paper advances much needed discussion of EHR de-identification - particularly in relation to criteria to assess de-identification, and considering the contexts of de-identified research databases when assessing the risk of breaches of confidential patient information.

All-cause mortality among people with serious mental illness (SMI), substance use disorders, and depressive disorders in southeast London: a cohort study.

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.

Identifying Suicide Ideation and Suicidal Attempts in a Psychiatric Clinical Research Database using Natural Language Processing.

Research into suicide prevention has been hampered by methodological limitations such as low sample size and recall bias. Recently, Natural Language Processing (NLP) strategies have been used with Electronic Health Records to increase information extraction from free text notes as well as structured fields concerning suicidality and this allows access to much larger cohorts than previously possible. This paper presents two novel NLP approaches - a rule-based approach to classify the presence of suicide ideation and a hybrid machine learning and rule-based approach to identify suicide attempts in a psychiatric clinical database. Good performance of the two classifiers in the evaluation study suggest they can be used to accurately detect mentions of suicide ideation and attempt within free-text documents in this psychiatric database. The novelty of the two approaches lies in the malleability of each classifier if a need to refine performance, or meet alternate classification requirements arises. The algorithms can also be adapted to fit infrastructures of other clinical datasets given sufficient clinical recording practice knowledge, without dependency on medical codes or additional data extraction of known risk factors to predict suicidal behaviour.

Demographic and clinical factors associated with different antidepressant treatments: a retrospective cohort study design in a UK psychiatric healthcare setting.

OBJECTIVE: To investigate the demographic and clinical factors associated with antidepressant use for depressive disorder in a psychiatric healthcare setting using a retrospective cohort study design. SETTING: Data were extracted from a de-identified data resource sourced from the electronic health records of a London mental health service. Relative risk ratios (RRRs) were obtained from multinomial logistic regression analysis to ascertain the probability of receiving common antidepressant treatments relative to sertraline. PARTICIPANTS: Patients were included if they received mental healthcare and a diagnosis of depression with antidepressant treatment between March and August 2015 and exposures were measured over the preceding 12 months. RESULTS: Older age was associated with increased use of all antidepressants compared with sertraline, except for negative associations with fluoxetine (RRR 0.98; 95% CI 0.96 to 0.98) and a combination of two selective serotonin reuptake inhibitors (SSRIs) (0.98; 95% CI 0.96 to 0.99), and no significant association with escitalopram. Male gender was associated with increased use of mirtazapine compared with sertraline (2.57; 95% CI 1.85 to 3.57). Previous antidepressant, antipsychotic and mood stabiliser use were associated with newer antidepressant use (ie, selective norepinephrine reuptake inhibitors, mirtazapine or a combination of both), while affective symptoms were associated with reduced use of citalopram (0.58; 95% CI 0.27 to 0.83) and fluoxetine (0.42; 95% CI 0.22 to 0.72) and somatic symptoms were associated with increased use of mirtazapine (1.60; 95% CI 1.00 to 2.75) relative to sertraline. In patients older than 25 years, past benzodiazepine use was associated with a combination of SSRIs (2.97; 95% CI 1.32 to 6.68), mirtazapine (1.94; 95% CI 1.20 to 3.16) and venlafaxine (1.87; 95% CI 1.04 to 3.34), while past suicide attempts were associated with increased use of fluoxetine (2.06; 95% CI 1.10 to 3.87) relative to sertraline. CONCLUSION: There were several factors associated with different antidepressant receipt in psychiatric healthcare. In patients aged >25, those on fluoxetine were more likely to have past suicide attempt, while past use of antidepressant and non-antidepressant use was also associated with use of new generation antidepressants, potentially reflecting perceived treatment resistance.

Risk assessment and suicide by patients with schizophrenia in secondary mental healthcare: a case-control study.

OBJECTIVES: To investigate the role of risk assessment in predicting suicide in patients with schizophrenia spectrum disorders (SSDs) receiving secondary mental healthcare. We postulated that risk assessment plays a limited role in predicting suicide in these patients. DESIGN: Retrospective case-control study. SETTING: Anonymised electronic mental health record data from the South London and Maudsley National Health Service (NHS) Foundation Trust (SLaM) (London, UK) linked with national mortality data. PARTICIPANTS: In 242 227 SLaM service users up to 31 December 2013, 635 suicides were identified. 96 (15.1%) had a SSD diagnosis. Those who died before 1 January 2007 (n=25) were removed from the analyses. Thus, 71 participants with SSD who died from suicide over the study period (cases) were compared with 355 controls. MAIN OUTCOME MEASURE: Risk of suicide in relation to risk assessment ratings. RESULTS: Cases were younger at first contact with services (mean±SD 34.5±12.6 vs 39.2±15.2) and with a higher preponderance of males (OR=2.07, 95% CI 1.18 to 3.65, p=0.01) than controls. Also, suicide occurred within 10 days after last contact with services in half of cases, with the most common suicide methods being hanging (14) and jumping (13). Cases were more likely to have the following 'risk assessment' items previously recorded: suicidal history (OR=4.42, 95% CI 2.01 to 9.65, p<0.001), use of violent method (OR=3.37, 95% CI 1.47 to 7.74, p=0.01), suicidal ideation (OR=3.57, 95% CI 1.40 to 9.07, p=0.01) and recent hospital discharge (OR=2.71, 95% CI 1.17 to 6.28, p=0.04). Multiple regression models predicted only 21.5% of the suicide outcome variance. CONCLUSIONS: Predicting suicide in schizophrenia is highly challenging due to the high prevalence of risk factors within this diagnostic group irrespective of outcome, including suicide. Nevertheless, older age at first contact with mental health services and lack of suicidal history and suicidal ideation are useful protective markers indicative of those less likely to end their own lives.

Functional status and all-cause mortality in serious mental illness.

BACKGROUND: Serious mental illness can affect many aspects of an individual's ability to function in daily life. The aim of this investigation was to determine if the environmental and functional status of people with serious mental illness contribute to the high mortality risk observed in this patient group. METHODS: We identified cases of 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 activities of daily living (ADLs), living conditions, occupational and recreational activities and relationship factors (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 6,880 SMI cases (242 deaths) in the observation period. ADL impairment was associated with an increased risk of all-cause mortality (adjusted HR 1.9; 95% CI 1.3-2.8; p = 0.001, p for trend across ADL categories = 0.001) after controlling for a broad range of covariates (including demographic factors, physical health, mental health symptoms and behaviours, socio-economic status and mental health service contact). No associations were found for the other three exposures. Stratification by age indicated that ADLs were most strongly associated with mortality in the youngest (15 to <35 years) and oldest (≥ 55 years) groups. CONCLUSIONS: Functional impairment in people with serious mental illness diagnoses is a marker of increased mortality risk, possibly in younger age groups as a marker of negative symptomatology.

Life expectancy at birth for people with serious mental illness and other major disorders from a secondary mental health care case register in London.

OBJECTIVE: Despite improving healthcare, the gap in mortality between people with serious mental illness (SMI) and general population persists, especially for younger age groups. The electronic database from a large and comprehensive secondary mental healthcare provider in London was utilized to assess the impact of SMI diagnoses on life expectancy at birth. METHOD: People who were diagnosed with SMI (schizophrenia, schizoaffective disorder, bipolar disorder), substance use disorder, and depressive episode/disorder before the end of 2009 and under active review by the South London and Maudsley NHS Foundation Trust (SLAM) in southeast London during 2007-09 comprised the sample, retrieved by the SLAM Case Register Interactive Search (CRIS) system. We estimated life expectancy at birth for people with SMI and each diagnosis, from national mortality returns between 2007-09, using a life table method. RESULTS: A total of 31,719 eligible people, aged 15 years or older, with SMI were analyzed. Among them, 1,370 died during 2007-09. Compared to national figures, all disorders were associated with substantially lower life expectancy: 8.0 to 14.6 life years lost for men and 9.8 to 17.5 life years lost for women. Highest reductions were found for men with schizophrenia (14.6 years lost) and women with schizoaffective disorders (17.5 years lost). CONCLUSION: The impact of serious mental illness on life expectancy is marked and generally higher than similarly calculated impacts of well-recognised adverse exposures such as smoking, diabetes and obesity. Strategies to identify and prevent causes of premature death are urgently required.