Johnny Downs

Cohort profile of the South London and Maudsley NHS Foundation Trust Biomedical Research Centre (SLaM BRC) Case Register : current status and recent enhancement of an Electronic Mental Health Record-derived data resource.

Purpose The South London and Maudsley National Health Service (NHS) Foundation Trust Biomedical Research Centre (SLaM BRC) Case Register and its Clinical Record Interactive Search (CRIS) application were developed in 2008, generating a research repository of real-time, anonymised, structured and open-text data derived from the electronic health record system used by SLaM, a large mental healthcare provider in southeast London. In this paper, we update this registers descriptive data, and describe the substantial expansion and extension of the data resource since its original development. Participants Descriptive data were generated from the SLaM BRC Case Register on 31 December 2014. Currently, there are over 250 000 patient records accessed through CRIS. Findings to date Since 2008, the most significant developments in the SLaM BRC Case Register have been the introduction of natural language processing to extract structured data from open-text fields, linkages to external sources of data, and the addition of a parallel relational database (Structured Query Language) output. Natural language processing applications to date have brought in new and hitherto inaccessible data on cognitive function, education, social care receipt, smoking, diagnostic statements and pharmacotherapy. In addition, through external data linkages, large volumes of supplementary information have been accessed on mortality, hospital attendances and cancer registrations. Future plans Coupled with robust data security and governance structures, electronic health records provide potentially transformative information on mental disorders and outcomes in routine clinical care. The SLaM BRC Case Register continues to grow as a database, with approximately 20 000 new cases added each year, in addition to extension of follow-up for existing cases. Data linkages and natural language processing present important opportunities to enhance this type of research resource further, achieving both volume and depth of data. However, research projects still need to be carefully tailored, so that they take into account the nature and quality of the source information.

The Effect of Clozapine on Premature Mortality: An Assessment of Clinical Monitoring and Other Potential Confounders

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.

Persisting psychotic-like experiences are associated with both externalising and internalising psychopathology in a longitudinal general population child cohort

BACKGROUND Persisting psychotic-like experiences (PLEs) are associated with an increased risk of internalising symptoms in adolescence. Whether this association holds similarly for externalising symptoms, and from mid-childhood, is unclear. This prospective study investigated the extent to which PLE persistence was associated with internalising and externalising psychopathology in a community sample of children aged 9-11years at study commencement. METHODS 8099 children (mean age 10.4years) completed questionnaires assessing PLEs, externalising and internalising symptoms. A subsample of 547 children completed reassessment, on average, two years later. RESULTS Two-thirds (66%) of children reported PLEs at baseline. Approximately two years later, PLEs persisted in 39% of those children. After adjustment for previous psychopathology and other potential confounds, children with persisting PLEs were at higher risk for internalising (odds ratio [OR]=1.94; 95% confidence interval [CI] 1.13-3.34) and externalising (OR=1.97; 95% CI 1.19-3.26) psychopathology than children whose PLEs remitted; and, than children who never presented PLEs. CONCLUSIONS Persistent PLEs from mid-childhood are associated with later internalising and externalising psychopathology in the general population, whereas transitory PLEs may be part of a spectrum of normative childhood development. Interventions that target persistent PLEs may contribute to a reduction in common childhood psychopathology.

Reasons for discontinuing clozapine: A cohort study of patients commencing treatment

Background Clozapine is uniquely effective in the management of treatment-resistant schizophrenia (TRS). However, a substantial proportion of patients discontinue treatment and this carries a poor prognosis. Methods We investigated the risk factors, reasons and timing of clozapine discontinuation in a two-year retrospective cohort study of 316 patients with TRS receiving their first course of clozapine. Reasons for discontinuation of clozapine and duration of treatment were obtained from case notes and Cox regression was employed to test the association of baseline clinical factors with clozapine discontinuation. Results A total of 142 (45%) patients discontinued clozapine within two years. By studying the reasons for discontinuations due to a patient decision, we found that adverse drug reactions (ADRs) accounted for over half of clozapine discontinuations. Sedation was the most common ADR cited as a reason for discontinuation and the risk of discontinuation due to ADRs was highest in the first few months of clozapine treatment. High levels of deprivation in the neighbourhood where the patient lived were associated with increased risk of clozapine discontinuation (HR = 2.12, 95% CI 1.30–3.47). Conclusions Living in a deprived neighbourhood was strongly associated with clozapine discontinuation. Clinical management to reduce the burden of ADRs in the first few months of treatment may have a significant impact and help more patients experience the benefits of clozapine treatment.

Predictors of long-term (≥6 months) antipsychotic polypharmacy prescribing in secondary mental healthcare

Introduction The predictors of long-term antipsychotic polypharmacy (APP) initiation are poorly understood. Existing research has been hampered by residual confounding, failure to exclude cross-titration, and difficulties in separating the timing of predictors and APP administration. Materials and methods Using data from the South London and Maudsley (SLaM) case register, we identified all adult patients with serious mental illness (SMI) who were receiving care between 1st July 2011 and 30th June 2012. Exposures measured between 1st July and 31st December 2011 included socio-demographic, socioeconomic, clinical and service use characteristics. We then determined if long-term APP (six or more months) had been initiated between 1st January and 30th June 2012. Multivariable logistic regression models, adjusted for socio-demographic and socioeconomic factors, were built to investigate the associations between the above factors and the initiation of long-term APP. Results We identified 6857 adults with SMI receiving SLaM care, of whom 115 (1.7%) were newly prescribed long-term APP. In the adjusted models, predictors of long-term APP initiation included: symptoms (severity of hallucinations and/or delusions), previous treatments (clozapine and long-acting injectable antipsychotic agents), service use (more contact with outpatient services, community treatment order receipt), social factors (higher area-level deprivation, homelessness) and socio-demographic status (younger age, not in a relationship). Conclusion Our findings highlight that certain patient groups are at an increased risk for long-term APP initiation. Identifying these groups earlier in their treatment could encourage clinicians to employ a broader range of interventions in addition to pharmacotherapy to reduce the risk of APP prescribing.

Antipsychotic polypharmacy and augmentation strategies prior to clozapine initiation: A historical cohort study of 310 adults with treatment-resistant schizophrenic disorders

Rationale: Antipsychotic polypharmacy (APP) is commonly used in schizophrenia despite a lack of robust evidence for efficacy, as well as evidence of increased rates of adverse drug reactions and mortality. Objectives: We sought to examine APP and the use of other adjunctive medications in patients with treatment-resistant schizophrenic disorders (ICD-10 diagnoses F20–F29) immediately prior to clozapine initiation, and to investigate clinical and sociodemographic factors associated with APP use in this setting. Methods: Analysis of case notes from 310 patients receiving their first course of clozapine at the South London and Maudsley NHS Trust (SLaM) was undertaken using the Clinical Record Interactive Search (CRIS) case register. Medication taken immediately prior to clozapine initiation was recorded, and global clinical severity was assessed at time points throughout the year prior to medication assessment using the Clinical Global Impression – Severity scale (CGI-S). Logistic regression was used to investigate factors associated with APP. Results: The point prevalence of APP prior to clozapine initiation was 13.6% (n=42), with 32.6% of subjects prescribed adjuvant psychotropic medications. APP was associated with increasing number of adjuvant medications (odds ratio (OR) 1.97, 95% confidence interval (CI) 1.27–3.06), concurrent depot antipsychotic prescription (OR 2.64, CI 1.24–5.62), concurrent antidepressant prescription (OR 4.40, CI 1.82–10.63) and a CGI-S over the previous year within the two middle quartiles (Quartile 2 vs 1 OR 6.19, CI 1.81–21.10; Quartile 3 vs 1 OR 4.45, CI 1.29–15.37; Quartile 4 vs 1 OR 1.88, CI 0.45–7.13). Conclusions: APP and augmentation of antipsychotics with antidepressants, mood stabilizers and benzodiazepines are being employed in treatment-resistant schizophrenia prior to clozapine. The conservative APP rate observed may have been influenced by an initiative within SLaM that reduced APP rates during the study window. Efforts to reduce the use of poorly evidenced prescribing should focus on adjuvant medications as well as APP.

Linking health and education data to plan and evaluate services for children

Linkage of routinely collected data from public services has the potential to improve how local health, education and social care are delivered to children. All mental health services, hospital-based child health services, schools and child protection services which serve the same local area could be more efficient if the design, monitoring, targeting and integration of services were based on data. Health services need evidence from the populations that they serve to plan care and know whether they are meeting childrens needs, duplicating effort or allowing some children to fall through the net. In this paper, we describe how the Clinical Record Interactive Search (CRIS) programme has joined up data from health, education and social services for children living in four local authorities in South London to create two datasets: one linking hospital to childrens mental health services and the second linking mental health data to education data. We describe these resources, give examples of how they are being used to improve services and discuss what is needed to implement this approach more widely across the UK. Across England, all National Health Service (NHS) and state education services for children routinely generate administrative data, but few areas have managed to join these data systematically to evaluate how services could better serve their populations. Details of every NHS hospital inpatient admission, emergency department and outpatient contact are centrally collated by NHS Digital.1 Demographic and socioeconomic data on every child in state education are submitted by all state-maintained schools to the Department of Education, along with the information on school attendance, attainment, exclusion, child protection involvement and special educational needs.2 Centrally collected child mental health data have yet to become available, but nearly all local services collect these data within their electronic health record systems.3 A big challenge is meeting …

Psychological consequences of child trafficking: An historical cohort study of trafficked children in contact with secondary mental health services.

Background Child trafficking is the recruitment and movement of people aged younger than 18 for the purposes of exploitation. Research on the mental health of trafficked children is limited, and little is known about the use of mental health services by this group. This study aimed to investigate the mental health and service use characteristics of trafficked children in contact with mental health services in England. Methods & findings The study employed an historical cohort design. Electronic health records of over 250,000 patients were searched to identify trafficked children, and a matched cohort of non-trafficked children was randomly selected. Data were extracted on the socio-demographic and clinical characteristics, abuse history, and trafficking experiences of the trafficked children. Logistic and linear random effects regression models were fitted to compare trafficked and non-trafficked children on their clinical profiles and service use characteristics. Fifty-one trafficked children were identified, 78% were female. The most commonly recorded diagnoses for trafficked children were post-traumatic stress disorder (PTSD) (22%) and affective disorders (22%). Records documented a high prevalence of physical violence (53%) and sexual violence (49%) among trafficked children. Trafficked children had significantly longer duration of contact with mental health services compared to non-trafficked controls (b = 1.66, 95% CI 1.09–2.55, p<0.02). No significant differences were found, however, with regards to pathways into care, prevalence of compulsory psychiatric admission, length of inpatient stays, or changes in global functioning. Conclusions Child trafficking is associated with high levels of physical and sexual abuse and longer duration of contact with mental health services. Research is needed on most effective interventions to promote recovery for this vulnerable group.

The Association Between Comorbid Autism Spectrum Disorders and Antipsychotic Treatment Failure in Early-Onset Psychosis: A Historical Cohort Study Using Electronic Health Records

OBJECTIVE In a sample of children and adolescents with first-episode psychosis, we investigated whether multiple treatment failure (MTF, defined as the initiation of a third trial of novel antipsychotic due to nonadherence, adverse effects, or insufficient response) was associated with comorbid autism spectrum disorders. METHODS Data were from the electronic health records of 638 children (51% male) aged from 10 to 17 years with first-episode psychosis (per ICD-10 criteria) from January 1, 2008, to November 1, 2014, referred to mental health services in South London, United Kingdom; data were extracted using the Clinical Record Interactive Search (CRIS) system. The effect of autism spectrum disorder comorbidity on the development of MTF during a 5-year period was modeled using Cox regression. RESULTS There were 124 cases of MTF prior to the age of 18 (19.4% of the sample). Comorbid autism spectrum disorders were significantly associated with MTF (adjusted hazard ratio = 1.99; 95% CI, 1.19-3.31; P = .008) after controlling for a range of potential confounders. Other factors significantly associated with MTF included higher age at first presentation (P = .001), black ethnicity (P = .03), and frequency of clinical contact (P < .001). No significant association between other comorbid neurodevelopmental disorders (hyperkinetic disorder or intellectual disability) and MTF was found. CONCLUSIONS Children with first-episode psychosis and comorbid autism spectrum disorders at first presentation are less likely to have a beneficial response to antipsychotics.

Identifying mortality risks in patients with opioid use disorder using brief screening assessment: Secondary mental health clinical records analysis

Highlights • Prompt identification of those at risk is key.• We examine clinical appraisal of patient risks and mortality in 4488 opioid dependent patients.• Addiction-specific risk assessment is useful in predicting mortality.• Non-admission of patients where suicidality is evident increases mortality.