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.

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.

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.

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.

Catatonia, 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.

Electronic 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.

We 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.

In 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.

Growing 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.

To 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.

We 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.

Following 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.

Residential 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.

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.

We set out to examine the relationship between the continuity of care of patients with schizophrenia, their mortality and cause of death.

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.

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.

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.

Research 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.

Lambeth 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.

We 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).

Our 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.

How neighbourhood characteristics affect the physical safety of people with mental illness is unclear.

To examine neighbourhood effects on physical victimisation towards people using mental health services.

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.

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.

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.

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.

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.

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.

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.

The density of information in digital health records offers new potential opportunities for automated prediction of cost-relevant outcomes.

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.

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.

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%).

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.

In 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.

In 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.

Clinical 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.

New 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.

Paper 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.

Studies indicate that risk of mortality is higher for patients admitted to acute hospitals at the weekend. However, less is known about clinical outcomes among patients admitted to psychiatric hospitals.

To investigate whether weekend admission to a psychiatric hospital is associated with worse clinical outcomes.

Data were obtained from 45 264 consecutive psychiatric hospital admissions. The association of weekend admission with in-patient mortality, duration of hospital admission and risk of readmission was investigated using multivariable regression analyses. Secondary analyses were performed to investigate the distribution of admissions, discharges, in-patient mortality, episodes of seclusion and violent incidents on different days of the week.

There were 7303 weekend admissions (16.1%). Patients who were aged between 26 and 35 years, female or from a minority ethnic group were more likely to be admitted at the weekend. Patients admitted at the weekend were more likely to present via acute hospital services, other psychiatric hospitals and the criminal justice system than to be admitted directly from their own home. Weekend admission was associated with a shorter duration of admission (B coefficient –21.1 days, 95% CI –24.6 to –17.6, P<0.001) and an increased risk of readmission in the 12 months following index admission (incidence rate ratio 1.13, 95% CI 1.08 to 1.18, P<0.001), but in-patient mortality (odds ratio (OR) = 0.79, 95% CI 0.51 to 1.23, P = 0.30) was not greater than for weekday admission. Fewer episodes of seclusion occurred at the weekend but there was no significant variation in deaths during hospital admission or violent incidents on different days of the week.

Being admitted at the weekend was not associated with an increased risk of in-patient mortality. However, patients admitted at the weekend had shorter admissions and were more likely to be readmitted, suggesting that they may represent a different clinical population to those admitted during the week. This is an important consideration if mental healthcare services are to be implemented across a 7-day week.

To 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.

Of 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.

The 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.

The 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.

To develop a data collection and diagnostic application that can be used across a broad range of clinical and research settings.

We 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.

OPCRIT+ performed well in an interrater reliability study with relatively inexperienced clinicians, giving a combined, weighted kappa of 0.70 for diagnostic reliability.

OPCRIT+ 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.

Clinicians 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.

Accurate 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.

This 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.