Recording of severe mental illness in United Kingdom primary care, 2000-2010

Socioeconomic status, alcohol use and the role of social support and neighbourhood environment among individuals meeting criteria for a mental health problem: a cross-sectional study

PURPOSE

Indicators of socioeconomic status (SES), such as education and occupational grade, are known to be associated with alcohol use but this has not been examined among individuals with a mental health problem. This study developed latent classes of SES, their associations with alcohol use, and examined the indirect effect via social support and neighbourhood environment.

METHODS

A secondary analysis of the 2014 Adult Psychiatric Morbidity Survey was conducted among participants with a mental health problem (N = 1,436). SES classes were determined using a range of indicators. Alcohol use was measured using the Alcohol Use Disorder Identification Test. Social support and neighbourhood neighbourhood environment were measured using validated questionnaires. A latent class analysis was conducted to develop SES classes. Multinomial logistic regression examined associations of SES and alcohol use. Structural equation models tested indirect effects via social support and neighbourhood environment.

RESULTS

A four-class model of SES was best-fitting; "economically inactive,GCSE-level and lower educated,social renters", "intermediate/routine occupation,GCSE-level educated,mixed owner/renters", "retired, no formal education,homeowners", and "professional occupation,degree-level educated,homeowners". Compared to "professional occupation,degree-level educated, homeowners", SES classes were more likely to be non-drinkers; odds were highest for "economically inactive,GCSE-level and lower educated,social renters" (OR = 4.96,95%CI 3.10-7.93). "Retired, no formal education,homeowners" were less likely to be hazardous drinkers (OR = 0.35,95%CI 0.20-0.59). Associations between "economically inactive,GCSE-level and lower educated,social renters" and "retired, no formal education,homeowners" and non- and harmful drinking via social support and neighbourhood environment were significant.

CONCLUSIONS

In contrast to the alcohol harms paradox, among individuals with a mental health problem, lower SES groups were more likely to be non-drinkers while no associations with harmful drinking were found. There is also a need to examine the alcohol harms paradox in the context of the area in which they live.

Predicting maintenance lithium response for bipolar disorder from electronic health records-a retrospective study

Background

Optimising maintenance drug treatment selection for people with bipolar disorder is challenging. There is some evidence that clinical and demographic features may predict response to lithium. However, attempts to personalise treatment choice have been limited.

Method

We aimed to determine if machine learning methods applied to electronic health records could predict differential response to lithium or olanzapine. From electronic United Kingdom primary care records, we extracted a cohort of individuals prescribed either lithium (19,106 individuals) or olanzapine (12,412) monotherapy. Machine learning models were used to predict successful monotherapy maintenance treatment, using 113 clinical and demographic variables, 8,017 (41.96%) lithium responders and 3,831 (30.87%) olanzapine responders.

Results

We found a quantitative structural difference in that lithium maintenance responders were weakly predictable in our holdout sample, consisting of the 5% of patients with the most recent exposure. Age at first diagnosis, age at first treatment and the time between these were the most important variables in all models.

Discussion

Even if we failed to predict successful monotherapy olanzapine treatment, and so to definitively separate lithium vs. olanzapine responders, the characterization of the two groups may be used for classification by proxy. This can, in turn, be useful for establishing maintenance therapy. The further exploration of machine learning methods on EHR data for drug treatment selection could in the future play a role for clinical decision support. Signals in the data encourage further experiments with larger datasets to definitively separate lithium vs. olanzapine responders.

Lithium and the risk of fractures in patients with bipolar disorder: A population-based cohort study

Lithium is considered to be the most effective mood stabilizer for bipolar disorder. Evolving evidence suggested lithium can also regulate bone metabolism which may reduce the risk of fractures. While there are concerns about fractures for antipsychotics and mood stabilizing antiepileptics, very little is known about the overall risk of fractures associated with specific treatments. This study aimed to compare the risk of fractures in patients with bipolar disorder prescribed lithium, antipsychotics or mood stabilizing antiepileptics (valproate, lamotrigine, carbamazepine). Among 40,697 patients with bipolar disorder from 1993 to 2019 identified from a primary care electronic health record database in the UK, 13,385 were new users of mood stabilizing agents (lithium:2339; non-lithium: 11,046). Lithium was associated with a lower risk of fractures compared with non-lithium treatments (HR 0.66, 95 % CI 0.44-0.98). The results were similar when comparing lithium with prolactin raising and sparing antipsychotics, and individual antiepileptics. Lithium use may lower fracture risk, a benefit that is particularly relevant for patients with serious mental illness who are more prone to falls due to their behaviors. Our findings could help inform better treatment decisions for bipolar disorder, and lithium's potential to prevent fractures should be considered for patients at high risk of fractures.

Mind the gap: an administrative data analysis of dental treatment outcomes and severe mental illness

BACKGROUND

Oral health of people with severe mental illness (SMI) remains an important public health issue, despite evidence pointing suboptimal dental health outcomes in this population.

AIMS

We test the hypotheses that individuals with SMI have lower contact with dental services and higher levels of fillings and extractions. We also examine effect modification by age-group.

METHODS

We used linked administrative data from general practitioner (GP), hospital and dental records to examine dental service use and treatments (extractions, fillings, crowns and x-rays) among the Northern Ireland hospital population between January 2015 and November 2019 (N = 798,564).

RESULTS

After adjusting for available socio-demographic characteristics, analysis indicated lower levels of dental service use (OR = 0.80, 95% CI = 0.77, 0.84), including lower likelihood of fillings (OR = 0.81, 0.77, 0.84) and x-rays (OR = 0.77, 0.74, 0.81), but higher levels of extractions (OR = 1.23, 1.18, 1.29) among patients with SMI. We also found effect modification by age-group, with older individuals with SMI less likely to have each of the four dental treatments.

CONCLUSIONS

We suggest that in the general area of physical healthcare for people with SMI, oral healthcare is neglected. There is a need for improved understanding of the barriers to routine care and treatment, and development of psychoeducational interventions.

Understanding alcohol use and changes in drinking habits among people with a severe mental illness: a qualitative framework analysis study

Introduction

Individuals with a severe mental illness (SMI) are more likely to drink at harmful levels or abstain. While it is known that drinking patterns change over time, the reasons for this among those with a SMI are unclear. This study aimed to (i) explore the experiences with alcohol, particularly in relation to mental health symptoms, and (ii) how drinking patterns have changed over time, among individuals who have a SMI diagnosis, who either currently drink alcohol or no longer drink.

Methods

One-to-one semi-structured telephone interviews were conducted to address the study aims. Current drinkers' alcohol use was assessed using the Alcohol Use Disorder Identification Test. A framework analysis was used to address the study aims with a specific focus on the differences in the experiences with alcohol use between current and former drinkers.

Results

16 participants were interviewed, and five themes were developed. The analysis highlighted how alcohol was increasingly used to cope with (i) trauma, (ii) SMI-related symptoms, or (iii) stress. Among those with a SMI, non-drinking was facilitated through declines in SMI-related symptoms, previous negative consequences due to alcohol and changing the social environment. Current drinking habits were facilitated through changes in the reasons for drinking and adopting different alcohol moderation techniques.

Discussion

Among those with a SMI diagnosis and who either currently drink alcohol or no longer drink, our findings support the self-medication hypothesis and drinking motives model. However, our findings indicate the need for further development of drinking to cope with a focus on symptoms of a SMI and trauma. Our findings also have implications on specialist alcohol and mental health services, the need to improve individuals' understanding of SMI, and the need to identify reasons for drinking among those with a recent diagnosis of a SMI.

Severe mental illness, race/ethnicity, multimorbidity and mortality following COVID-19 infection: nationally representative cohort study

BACKGROUND

The association of COVID-19 with death in people with severe mental illness (SMI), and associations with multimorbidity and ethnicity, are unclear.

AIMS

To determine all-cause mortality in people with SMI following COVID-19 infection, and assess whether excess mortality is affected by multimorbidity or ethnicity.

METHOD

This was a retrospective cohort study using primary care data from the Clinical Practice Research Database, from February 2020 to April 2021. Cox proportional hazards regression was used to estimate the effect of SMI on all-cause mortality during the first two waves of the COVID-19 pandemic.

RESULTS

Among 7146 people with SMI (56% female), there was a higher prevalence of multimorbidity compared with the non-SMI control group (n = 653 024, 55% female). Following COVID-19 infection, the SMI group experienced a greater risk of death compared with controls (adjusted hazard ratio (aHR) 1.53, 95% CI 1.39-1.68). Black Caribbean/Black African people were more likely to die from COVID-19 compared with White people (aHR = 1.22, 95% CI 1.12-1.34), with similar associations in the SMI group and non-SMI group (P for interaction = 0.73). Following infection with COVID-19, for every additional multimorbidity condition, the aHR for death was 1.06 (95% CI 1.01-1.10) in the SMI stratum and 1.16 (95% CI 1.15-1.17) in the non-SMI stratum (P for interaction = 0.001).

CONCLUSIONS

Following COVID-19 infection, patients with SMI were at an elevated risk of death, further magnified by multimorbidity. Black Caribbean/Black African people had a higher risk of death from COVID-19 than White people, and this inequity was similar for the SMI group and the control group.

Trends in socioeconomic inequalities in incidence of severe mental illness - A population-based linkage study using primary and secondary care routinely collected data between 2000 and 2017

OBJECTIVE

In 2008, the UK entered a period of economic recession followed by sustained austerity measures. We investigate changes in inequalities by area deprivation and urbanicity in incidence of severe mental illness (SMI, including schizophrenia-related disorders and bipolar disorder) between 2000 and 2017.

METHODS

We analysed 4.4 million individuals from primary and secondary care routinely collected datasets (2000-2017) in Wales and estimated the incidence of SMI by deprivation and urbanicity measured by the Welsh Index of Multiple Deprivation (WIMD) and urban/rural indicator respectively. Using linear modelling and joinpoint regression approaches, we examined time trends of the incidence and incidence rate ratios (IRR) of SMI by the WIMD and urban/rural indicator adjusted for available confounders.

RESULTS

We observed a turning point of time trends of incidence of SMI at 2008/2009 where slope changes of time trends were significantly increasing. IRRs by deprivation/urbanicity remained stable or significantly decreased over the study period except for those with bipolar disorder sourced from secondary care settings, with increasing trend of IRRs (increase in IRR by deprivation after 2010: 1.6 % per year, 95 % CI: 1.0 %-2.2 %; increase in IRR by urbanicity 1.0 % per year, 95 % CI: 0.6 %-1.3 %).

CONCLUSIONS

There was an association between recession/austerity and an increase in the incidence of SMI over time. There were variations in the effects of deprivation/urbanicity on incidence of SMI associated with short- and long-term socioeconomic change. These findings may support targeted interventions and social protection systems to reduce incidence of SMI.

The incidence rate of planned and emergency physical health hospital admissions in people diagnosed with severe mental illness: a cohort study

BACKGROUND

People with severe mental illness (SMI) have more physical health conditions than the general population, resulting in higher rates of hospitalisations and mortality. In this study, we aimed to determine the rate of emergency and planned physical health hospitalisations in those with SMI, compared to matched comparators, and to investigate how these rates differ by SMI diagnosis.

METHODS

We used Clinical Practice Research DataLink Gold and Aurum databases to identify 20,668 patients in England diagnosed with SMI between January 2000 and March 2016, with linked hospital records in Hospital Episode Statistics. Patients were matched with up to four patients without SMI. Primary outcomes were emergency and planned physical health admissions. Avoidable (ambulatory care sensitive) admissions and emergency admissions for accidents, injuries and substance misuse were secondary outcomes. We performed negative binomial regression, adjusted for clinical and demographic variables, stratified by SMI diagnosis.

RESULTS

Emergency physical health (aIRR:2.33; 95% CI 2.22-2.46) and avoidable (aIRR:2.88; 95% CI 2.60-3.19) admissions were higher in patients with SMI than comparators. Emergency admission rates did not differ by SMI diagnosis. Planned physical health admissions were lower in schizophrenia (aIRR:0.80; 95% CI 0.72-0.90) and higher in bipolar disorder (aIRR:1.33; 95% CI 1.24-1.43). Accident, injury and substance misuse emergency admissions were particularly high in the year after SMI diagnosis (aIRR: 6.18; 95% CI 5.46-6.98).

CONCLUSION

We found twice the incidence of emergency physical health admissions in patients with SMI compared to those without SMI. Avoidable admissions were particularly elevated, suggesting interventions in community settings could reduce hospitalisations. Importantly, we found underutilisation of planned inpatient care in patients with schizophrenia. Interventions are required to ensure appropriate healthcare use, and optimal diagnosis and treatment of physical health conditions in people with SMI, to reduce the mortality gap due to physical illness.

Severe mental illness and ophthalmic health: A linked administrative data study

BACKGROUND

While evidence has emerged highlighting the potential benefits of the eye as a window to the central nervous system, research on severe mental illness (SMI) and eye health is rare.

AIMS

We examine the association of SMI with a range of ophthalmic health outcomes, and whether any relationship is modified by age.

METHODS

We used linked administrative data from general practitioner (GP), hospital and ophthalmic records to examine receipt of any Health and Social Care (HSC) eye-test; and (based on eligibility recorded for a sight test) any glaucoma, any diabetes, and any blindness among the Northern Ireland (NI) hospital population between January 2015 and November 2019 (N = 798,564).

RESULTS

When compared with non-SMI patients, those with SMI recorded a higher prevalence of having had a sight test, diabetes, and blindness. In fully adjusted logistic regression models, higher likelihood of an eye-test and diabetes (OR = 1.71: 95%CI = 1.63, 1.79 and OR = 1.29: 1.19, 1.40 respectively); and lower likelihood of glaucoma remained (OR = 0.69: 0.53, 0.90). Amongst persons with SMI there was evidence that the likelihood of having had an eye-test was lower in the older age-groups.

CONCLUSION

Our study provides new evidence on ophthalmic health inequalities associated with SMI. While the study has immediate relevance to its NI context, we believe it is generalizable to wider UK health concerns. We emphasize the need for more research of this type, using large linkable electronic administrative databases to further our understanding of both health inequalities associated with SMI and poor eye health, and health outcomes in general.

Inequalities in cancer screening participation between adults with and without severe mental illness: results from a cross-sectional analysis of primary care data on English Screening Programmes

BACKGROUND

People with severe mental illness (SMI) are 2.5 times more likely to die prematurely from cancer in England. Lower participation in screening may be a contributing factor.

METHODS

Clinical Practice Research Datalink data for 1.71 million, 1.34 million and 2.50 million adults were assessed (using multivariate logistic regression) for possible associations between SMI and participation in bowel, breast and cervical screening, respectively.

RESULTS

Screening participation was lower among adults with SMI, than without, for bowel (42.11% vs. 58.89%), breast (48.33% vs. 60.44%) and cervical screening (64.15% vs. 69.72%; all p < 0.001). Participation was lowest in those with schizophrenia (bowel, breast, cervical: 33.50%, 42.02%, 54.88%), then other psychoses (41.97%, 45.57%, 61.98%), then bipolar disorder (49.94%, 54.35%, 69.69%; all p-values < 0.001, except cervical screening in bipolar disorder; p-value > 0.05). Participation was lowest among people with SMI who live in the most deprived quintile of areas (bowel, breast, cervical: 36.17%, 40.23%, 61.47%), or are of a Black ethnicity (34.68%, 38.68%, 64.80%). Higher levels of deprivation and diversity, associated with SMI, did not explain the lower participation in screening.

CONCLUSIONS

In England, participation in cancer screening is low among people with SMI. Support should be targeted to ethnically diverse and socioeconomically deprived areas, where SMI prevalence is greatest.

Predicting type 2 diabetes prevalence for people with severe mental illness in a multi-ethnic East London population

BACKGROUND AND AIMS

Prevalence of type two diabetes mellitus (T2DM) in people with severe mental illness (SMI) is 2-3 times higher than in general population. Predictive modelling has advanced greatly in the past decade, and it is important to apply cutting-edge methods to vulnerable groups. However, few T2DM prediction models account for the presence of mental illness, and none seemed to have been developed specifically for people with SMI. Therefore, we aimed to develop and internally validate a T2DM prevalence model for people with SMI.

METHODS

We utilised a large cross-sectional sample representative of a multi-ethnic population from London (674,000 adults); 10,159 people with SMI formed our analytical sample (1,513 T2DM cases). We fitted a linear logistic regression and XGBoost as stand-alone models and as a stacked ensemble. Age, sex, body mass index, ethnicity, area-based deprivation, past hypertension, cardiovascular diseases, prescribed antipsychotics, and SMI illness were the predictors.

RESULTS

Logistic regression performed well while detecting T2DM presence for people with SMI: area under the receiver operator curve (ROC-AUC) was 0.83 (95 % CI 0.79-0.87). XGBoost and LR-XGBoost ensemble performed equally well, ROC-AUC 0.83 (95 % CI 0.79-0.87), indicating a negligible contribution of non-linear terms to predictive power. Ethnicity was the most important predictor after age. We demonstrated how the derived models can be utilised and estimated a 2.14 % (95 %CI 2.03 %-2.24 %) increase in T2DM prevalence in East London SMI population in 20 years' time, driven by the projected demographic changes.

CONCLUSIONS

Primary care data, the setting where prediction models could be most fruitfully used, provide enough information for well-performing T2DM prevalence models for people with SMI. We demonstrated how thorough internal cross-validation of an ensemble of a linear and machine-learning model can quantify the predictive value of non-linearity in the data.

Comparison of Caregivers' Burden among Family Members of Patients with Severe Mental Disorders and Patients with Substance Use Disorder

Objective: The burden on caregivers of patients with severe mental disorders is significantly higher than the care burden of patients with other medical conditions. Substance use disorder is also one of the most common psychiatric disorders that has negative effects on people's quality of life. This study was designed to investigate caregiver burden in severe mental disorders versus substance use disorder. Method : First-degree relatives of patients admitted to the Razi Psychiatric Hospital of Tehran with a diagnosis of schizophrenia, bipolar disorder type1, schizoaffective disorder, or substance use disorder entered this study. They completed the sociodemographic questionnaire for patients and caregivers and the Zarit burden interview for caregivers. Results: Our study shows that caregiver burden in substance use disorder has no significant difference with that in severe mental disorders (P > 0.05). In both groups, the highest spectrum of burden was moderate to severe. To find caregiver burden related factors, a general linear regression model with multiple predictor variables was fitted. In this model, caregivers' burden was significantly higher in patients with comorbidity (P = 0.007), poor compliance (P < 0.001), and in female caregivers (P = 0.013). Conclusion: Statistically speaking, the caregiver burden in substance use disorders is as severe as other mental disorders. The considerable burden on both groups necessitates serious efforts to minimize its negative effects.

The association between social deprivation and the rate of identification of individuals at Ultra-High Risk for psychosis and transition to psychosis

BACKGROUND

There is a higher incidence of psychotic disorders in neighbourhoods of greater social deprivation. However, it is not known whether this represents a causal relationship, as the stage at which social deprivation exerts its influence on the development of psychotic disorders is yet to be elucidated. We aimed to investigate the association between neighbourhood-level social deprivation and the rate of identification of individuals at Ultra-High Risk for psychosis (UHR), as well as the risk of transition to psychosis in UHR individuals.

METHODS

The cohort included all young people aged 15 to 24 identified as UHR attending an Early Intervention clinic in northwestern Melbourne over a 5-year period (2012-2016). Australian census data were used to obtain the at-risk population and social deprivation information according to the postcode of residence. Levels of social deprivation were arranged into quartiles. Poisson regression was used to calculate rate ratios and Cox regression analysis determined hazard ratios.

RESULTS

Of the 461 young people identified as UHR, 11.1% (n = 49) lived in the most affluent neighbourhoods (Quartile 1) compared to 36.7% (n = 162) in the most deprived neighbourhoods (Quartile 4). There was a 35% higher rate of identification of young people who were UHR from the most deprived neighbourhoods (aIRR = 1.35, 95% CI [0.98, 1.86]). Over a median follow-up of approximately 10 months (308 days (IQR: 188-557), 17.5% (n = 77) were known to have transitioned to a full-threshold psychotic disorder. Residing in a neighbourhood of above average deprivation had a hazard ratio of 2.05 (95% CI [0.88, 4.80]) for risk of transition, when controlling for age, sex and substance use.

CONCLUSIONS

These findings provide more support that EI services should be funded as per the expected incidence of psychotic disorders.

Incidence of postural hypotension recorded in UK general practice: an electronic health records study

BACKGROUND

Postural hypotension is a common condition associated with adverse outcomes in older adults. General practice plays an important role in identification of the condition.

AIM

To examine the incidence of postural hypotension between 2008 and 2018 in general practice and how trends vary by age, sex, year, and social deprivation.

DESIGN AND SETTING

Retrospective cohort study using electronic health records from the IQVIA Medical Research Data (IMRD) between 2008 and 2018.

METHOD

Patients were included if they were aged ≥50 years. Incident postural hypotension was identified as a new (first) recording of a postural hypotension code. Recording of incident postural hypotension was estimated per 10 000 person-years at risk (PYAR) according to age, sex, year, and social deprivation. Incident rate ratios were estimated by multivariable Poisson regression.

RESULTS

Of 2 911 260 patients, 24 973 had an electronic record indicating a new diagnosis of postural hypotension between 2008 and 2018. This was equivalent to 17.9 cases per 10 000 PYAR in males (95% confidence interval [CI] = 17.6 to 18.2) and 16.2 cases per 10 000 PYAR in females (95% CI = 15.9 to 16.5). A significant age-sex interaction was identified. Recorded postural hypotension rate increased with age and social deprivation, and reduced between 2008 and 2018. The rate was higher in males compared with females, particularly in older age groups (>80 years).

CONCLUSION

To the authors' knowledge, this is the first study to quantify incident recorded postural hypotension in general practice. The rate is lower than expected compared with studies in screened older populations. Potential barriers to identification include underreporting, underdetection owing to lack of time and/or poorly standardised methods of measurement, and poor coding. Future research should investigate current practice and approaches for increased detection such as education, practical methods of screening, and standardised measurement of postural blood pressure.

Developing and internally validating a prognostic model (P Risk) to improve the prediction of psychosis in a primary care population using electronic health records: The MAPPED study

BACKGROUND

An accurate risk prediction algorithm could improve psychosis outcomes by reducing duration of untreated psychosis.

OBJECTIVE

To develop and validate a risk prediction model for psychosis, for use by family doctors, using linked electronic health records.

METHODS

A prospective prediction study. Records from family practices were used between 1/1/2010 to 31/12/2017 of 300,000 patients who had consulted their family doctor for any nonpsychotic mental health problem. Records were selected from Clinical Practice Research Datalink Gold, a routine database of UK family doctor records linked to Hospital Episode Statistics, a routine database of UK secondary care records. Each patient had 5-8 years of follow up data. Study predictors were consultations, diagnoses and/or prescribed medications, during the study period or historically, for 13 nonpsychotic mental health problems and behaviours, age, gender, number of mental health consultations, social deprivation, geographical location, and ethnicity. The outcome was time to an ICD10 psychosis diagnosis.

FINDINGS

830 diagnoses of psychosis were made. Patients were from 216 family practices; mean age was 45.3 years and 43.5 % were male. Median follow-up was 6.5 years (IQR 5.6, 7.8). Overall 8-year psychosis incidence was 45.8 (95 % CI 42.8, 49.0)/100,000 person years at risk. A risk prediction model including age, sex, ethnicity, social deprivation, consultations for suicidal behaviour, depression/anxiety, substance abuse, history of consultations for suicidal behaviour, smoking history and prescribed medications for depression/anxiety/PTSD/OCD and total number of consultations had good discrimination (Harrell's C = 0.774). Identifying patients aged 17-100 years with predicted risk exceeding 1.0 % over 6 years had sensitivity of 71 % and specificity of 84 %.

FUNDING

NIHR, School for Primary Care Research, Biomedical Research Centre.

Associations of common mental disorder with alcohol use in the adult general population: a systematic review and meta-analysis

BACKGROUND AND AIMS

Research has shown that alcohol use and common mental disorders (CMDs) co-occur; however, little is known about how the global prevalence of alcohol use compares across different CMDs. We aimed to (i) report global associations of alcohol use (alcohol use disorder (AUD), binge drinking and consumption) comparing those with and without a CMD, (ii) examine how this differed among those with and without specific types of CMDs and (iii) examine how results may differ by study characteristics.

METHODS

We used a systematic review and meta-analysis. Cross-sectional, cohort, prospective, longitudinal and case-control studies reporting the prevalence of alcohol use among those with and without a CMD in the general population were identified using PsycINFO, MEDLINE, PsyARTICLES, PubMed, Scopus and Web of Science until March 2020. Depression, anxiety and phobia were included as a CMD. Studies were included if they used a standardized measure of alcohol use. A random-effects meta-analysis was conducted to generate pooled prevalence and associations of AUD with CMD with 95% confidence intervals (CI). A narrative review is provided for binge drinking and alcohol consumption RESULTS: A total of 512 full-texts were reviewed, 51 included in our final review and 17 in our meta-analyses (n = 382 201). Individuals with a CMD had a twofold increase in the odds of reporting an AUD [odds ratio (OR) = 2.02, 95% CI = 1.72-2.36]. The odds of having an AUD were similar when stratified by the type of CMD (mood disorder: OR = 2.00, 95% CI = 1.62-2.47; anxiety/phobic disorder: OR = 1.94, 95% CI = 1.35-2.78). An analysis of study characteristics did not reveal any clear explanations for between-study heterogeneity (I²  > 80%). There were no clear patterns for associations between having a CMD and binge drinking or alcohol consumption, respectively.

CONCLUSIONS

People with common mental disorders (depression, anxiety, phobia) are twice as likely to report an alcohol use disorder than people without common mental disorders.

Initiation of antidepressant medication in people with type 2 diabetes living in the UK - a retrospective cohort study

Introduction

Depression is a common comorbidity in people with type 2 diabetes and it is associated with poorer outcomes. There is limited data on the treatments used for depression in this population. The aim of this study was to explore the rates of initiation of antidepressant prescriptions in people with type 2 diabetes in the UK and identify those most at risk of needing such treatment.

Research Design and Methods

This was a retrospective cohort study using data from IQVIA Medical Research Data (IMRD)‐UK data. Data from general practices in IMRD‐UK between January 2008 and December 2017 were used for this study.

Results

The overall rates of antidepressant prescribing were stable over the study period. The rate of initiation of antidepressant medication in people with type 2 diabetes was 22.93 per 1000 person years at risk (PYAR) with a 95%CI 22.48 to 23.39 compared to 16.89 per 1000 PYAR (95%CI 16.77 to 17.01) in an age and gender matched cohort. The risk of being prescribed antidepressant medication with age had a U‐shaped distribution with the lowest risk in the 65–69 age group. The peak age for antidepressant initiation in men and women was 40–44, with a rate in men of 32.78 per 1000 PYAR (95% CI 29.57 to 36.34) and a rate in women of 46.80 per 1000 PYAR (95% CI 41.90 to 52.26). People with type 2 diabetes with in the least deprived quintile had an initiation rate of 19.66 per 1000 PYAR (95%CI 18.67 to 20.70) compared to 27.19 per 1000 PYAR (95%CI 25.50 to 28.93) in the most deprived quintile, with a 32% increase in the risk of starting antidepressant medication (95%CI 1.22 to 1.43).

Conclusions

People with type 2 diabetes were 30% more likely to be started on antidepressant medication than people without type 2 diabetes. Women with type 2 diabetes were 35% more likely than men to be prescribed antidepressants and the risks increased with deprivation and in younger or older adults, with the lowest rates in the 65–69 year age band. The rates of antidepressant prescribing were broadly stable over the 10‐year period in this study. The antidepressant medications prescribed changed slightly over time with sertraline becoming more widely used and fewer prescriptions of citalopram.

Clustering of physical health multimorbidity in people with severe mental illness: An accumulated prevalence analysis of United Kingdom primary care data

BACKGROUND

People with severe mental illness (SMI) have higher rates of a range of physical health conditions, yet little is known regarding the clustering of physical health conditions in this population. We aimed to investigate the prevalence and clustering of chronic physical health conditions in people with SMI, compared to people without SMI.

METHODS AND FINDINGS

We performed a cohort-nested accumulated prevalence study, using primary care data from the Clinical Practice Research Datalink (CPRD), which holds details of 39 million patients in the United Kingdom. We identified 68,783 adults with a primary care diagnosis of SMI (schizophrenia, bipolar disorder, or other psychoses) from 2000 to 2018, matched up to 1:4 to 274,684 patients without an SMI diagnosis, on age, sex, primary care practice, and year of registration at the practice. Patients had a median of 28.85 (IQR: 19.10 to 41.37) years of primary care observations. Patients with SMI had higher prevalence of smoking (27.65% versus 46.08%), obesity (24.91% versus 38.09%), alcohol misuse (3.66% versus 13.47%), and drug misuse (2.08% versus 12.84%) than comparators. We defined 24 physical health conditions derived from the Elixhauser and Charlson comorbidity indices and used logistic regression to investigate individual conditions and multimorbidity. We controlled for age, sex, region, and ethnicity and then additionally for health risk factors: smoking status, alcohol misuse, drug misuse, and body mass index (BMI). We defined multimorbidity clusters using multiple correspondence analysis (MCA) and K-means cluster analysis and described them based on the observed/expected ratio. Patients with SMI had higher odds of 19 of 24 conditions and a higher prevalence of multimorbidity (odds ratio (OR): 1.84; 95% confidence interval [CI]: 1.80 to 1.88, p < 0.001) compared to those without SMI, particularly in younger age groups (males aged 30 to 39: OR: 2.49; 95% CI: 2.27 to 2.73; p < 0.001; females aged 18 to 30: OR: 2.69; 95% CI: 2.36 to 3.07; p < 0.001). Adjusting for health risk factors reduced the OR of all conditions. We identified 7 multimorbidity clusters in those with SMI and 7 in those without SMI. A total of 4 clusters were common to those with and without SMI; while 1, heart disease, appeared as one cluster in those with SMI and 3 distinct clusters in comparators; and 2 small clusters were unique to the SMI cohort. Limitations to this study include missing data, which may have led to residual confounding, and an inability to investigate the temporal associations between SMI and physical health conditions.

CONCLUSIONS

In this study, we observed that physical health conditions cluster similarly in people with and without SMI, although patients with SMI had higher burden of multimorbidity, particularly in younger age groups. While interventions aimed at the general population may also be appropriate for those with SMI, there is a need for interventions aimed at better management of younger-age multimorbidity, and preventative measures focusing on diseases of younger age, and reduction of health risk factors.

Prescribing of antipsychotics among people with recorded personality disorder in primary care: a retrospective nationwide cohort study using The Health Improvement Network primary care database

OBJECTIVES

To investigate the extent of antipsychotic prescribing to people with recorded personality disorder (PD) in UK primary care and factors associated with such prescribing.

DESIGN

Retrospective cohort study.

SETTING

General practices contributing to The Health Improvement Network UK-wide primary care database, 1 January 2000-31 December 2016.

PARTICIPANTS

46 210 people registered with participating general practices who had a record of PD in their general practice notes. 1358 (2.9%) people with missing deprivation information were excluded from regression analyses; no other missing data.

MAIN OUTCOME MEASURES

Prescriptions for antipsychotics in general practice records and length of time in receipt of antipsychotic prescriptions.

RESULTS

Of 46 210 people with recorded PD, 15 562 (34%) were ever prescribed antipsychotics. Among the subgroup of 36 875 people with recorded PD, but no recorded severe mental illness (SMI), 9208 (25%) were prescribed antipsychotics; prescribing was lower in less deprived areas (adjusted rate ratio (aRR) comparing least to most deprived quintile: 0.56, 95% CI 0.48 to 0.66, p<0.001), was higher in females (aRR:1.25, 95% CI 1.16 to 1.34, p<0.001) and with a history of adverse childhood experiences (aRR:1.44, 95% CI 1.28 to 1.56, p<0.001). Median time prescribed antipsychotics was 605 days (IQR 197-1639 days). Prescribing frequency has increased over time.

CONCLUSIONS

Contrary to current UK guidelines, antipsychotics are frequently and increasingly prescribed for extended periods to people with recorded PD, but with no history of SMI. An urgent review of clinical practice is warranted, including the effectiveness of such prescribing and the need to monitor for adverse effects, including metabolic complications.

Mapping multimorbidity in individuals with schizophrenia and bipolar disorders: evidence from the South London and Maudsley NHS Foundation Trust Biomedical Research Centre (SLAM BRC) case register

OBJECTIVES

The first aim of this study was to design and develop a valid and replicable strategy to extract physical health conditions from clinical notes which are common in mental health services. Then, we examined the prevalence of these conditions in individuals with severe mental illness (SMI) and compared their individual and combined prevalence in individuals with bipolar (BD) and schizophrenia spectrum disorders (SSD).

DESIGN

Observational study.

SETTING

Secondary mental healthcare services from South London PARTICIPANTS: Our maximal sample comprised 17 500 individuals aged 15 years or older who had received a primary or secondary SMI diagnosis (International Classification of Diseases, 10th edition, F20-31) between 2007 and 2018.

MEASURES

We designed and implemented a data extraction strategy for 21 common physical comorbidities using a natural language processing pipeline, MedCAT. Associations were investigated with sex, age at SMI diagnosis, ethnicity and social deprivation for the whole cohort and the BD and SSD subgroups. Linear regression models were used to examine associations with disability measured by the Health of Nations Outcome Scale.

RESULTS

Physical health data were extracted, achieving precision rates (F1) above 0.90 for all conditions. The 10 most prevalent conditions were diabetes, hypertension, asthma, arthritis, epilepsy, cerebrovascular accident, eczema, migraine, ischaemic heart disease and chronic obstructive pulmonary disease. The most prevalent combination in this population included diabetes, hypertension and asthma, regardless of their SMI diagnoses.

CONCLUSIONS

Our data extraction strategy was found to be adequate to extract physical health data from clinical notes, which is essential for future multimorbidity research using text records. We found that around 40% of our cohort had multimorbidity from which 20% had complex multimorbidity (two or more physical conditions besides SMI). Sex, age, ethnicity and social deprivation were found to be key to understand their heterogeneity and their differential contribution to disability levels in this population. These outputs have direct implications for researchers and clinicians.

Risk of severe COVID-19 infection in individuals with severe mental disorders, substance use disorders, and common mental disorders

OBJECTIVE

To evaluate the risk of severe COVID-19 in individuals with severe mental disorders, substance use disorders, and common mental disorders in the total adult population of Region Stockholm (N = 1,516,270), and to explore possible underlying mechanisms to the increased risk.

METHODS

In this prospective cohort study, we examined the risk of hospitalization and treatment in an intensive care unit (ICU) with COVID-19, and death from COVID-19 for individuals with mental disorders. Associations were step by step adjusted for (1) sociodemographic/economic factors, (2) indicators of virus exposure, (3) somatic conditions, and (4) psychopharmacological treatment.

RESULTS

In model 1 (adjusted for age, sex and living in a care home for elderly people), people with a mental disorder had increased risks for inpatient care (HR = 1.5), ICU care (HR = 1.5), and mortality (HR = 1.4) from COVID-19. There was an increased risk of dying from COVID-19 in all subgroups of mental disorders, particularly in people with a severe mental disorder (HR = 1.9). Different covariates had different effects on the association depending on the outcome and on sex, age, or psychiatric diagnosis of the participants.

CONCLUSION

People with mental disorders have an increased risk of severe COVID-19, including mortality. The increased risk was partly explained by the examined covariates.

Cognitive assessment using the Rapid Assessment for Developmental Disabilities, Second Edition (RADD-2)

BACKGROUND

Individuals with developmental disabilities (DD) often have severe impairments and maladaptive behaviours that make it difficult to reliably assess their cognitive abilities. Given these challenges, the Rapid Assessment of Developmental Disabilities, Second Edition (RADD-2), was designed to measure general cognitive ability in this population. The purpose of this study is to demonstrate the battery's psychometric properties when used with individuals with DD who have challenging behavioural and psychiatric conditions and for those who have limited verbal skills.

METHOD

The cognitive and adaptive behaviour skills of 193 children and adults with DD and considerable medical, behavioural and/or psychiatric problems were evaluated using the first and second editions of the RADD, Kaufmann Brief Intelligence Test - 2nd Edition, and Scales of Independent Behaviour - Revised Edition. Medication side effects and challenging behaviours were assessed using the Aberrant Behaviour Checklist.

RESULTS

There were no floor or ceiling effects on the RADD-2. Both the nonverbal index and total scores had strong concurrent validity with other abbreviated tests of intellectual ability and good discriminant validity from measures of adaptive behaviour and medication side effects. RADD-2 scores also had strong criterion validity as they successfully differentiated between all levels of intellectual functioning. Age and sex did not differentially affect RADD-2 performance, and the co-occurrence of psychiatric conditions did not negatively affect performance. The only medical condition associated with lower RADD-2 performance was epilepsy.

CONCLUSIONS

The RADD-2 can quantify the differential cognitive abilities of individuals with DD, even for those with minimal communication skills, challenging behaviours or severe medication side effects that can typically complicate assessment. This brief cognitive battery can be used to measure changes due to interventions, on the one hand, and progression of neurological disease, on the other.

Using epidemiological evidence to forecast population need for early treatment programmes in mental health: a generalisable Bayesian prediction methodology applied to and validated for first-episode psychosis in England

BACKGROUND

Mental health policy makers require evidence-based information to optimise effective care provision based on local need, but tools are unavailable.

AIMS

To develop and validate a population-level prediction model for need for early intervention in psychosis (EIP) care for first-episode psychosis (FEP) in England up to 2025, based on epidemiological evidence and demographic projections.

METHOD

We used Bayesian Poisson regression to model small-area-level variation in FEP incidence for people aged 16-64 years. We compared six candidate models, validated against observed National Health Service FEP data in 2017. Our best-fitting model predicted annual incidence case-loads for EIP services in England up to 2025, for probable FEP, treatment in EIP services, initial assessment by EIP services and referral to EIP services for 'suspected psychosis'. Forecasts were stratified by gender, age and ethnicity, at national and Clinical Commissioning Group levels.

RESULTS

A model with age, gender, ethnicity, small-area-level deprivation, social fragmentation and regional cannabis use provided best fit to observed new FEP cases at national and Clinical Commissioning Group levels in 2017 (predicted 8112, 95% CI 7623-8597; observed 8038, difference of 74 [0.92%]). By 2025, the model forecasted 11 067 new treated cases per annum (95% CI 10383-11740). For every 10 new treated cases, 21 and 23 people would be assessed by and referred to EIP services for suspected psychosis, respectively.

CONCLUSIONS

Our evidence-based methodology provides an accurate, validated tool to inform clinical provision of EIP services about future population need for care, based on local variation of major social determinants of psychosis.

Living with diabetes alongside a severe mental illness: A qualitative exploration with people with severe mental illness, family members and healthcare staff

AIMS

Diabetes is two to three times more prevalent in people with severe mental illness, yet little is known about the challenges of managing both conditions from the perspectives of people living with the co-morbidity, their family members or healthcare staff. Our aim was to understand these challenges and to explore the circumstances that influence access to and receipt of diabetes care for people with severe mental illness.

METHODS

Framework analysis of qualitative semi-structured interviews with people with severe mental illness and diabetes, family members, and staff from UK primary care, mental health and diabetes services, selected using a maximum variation sampling strategy between April and December 2018.

RESULTS

In all, 39 adults with severe mental illness and diabetes (3 with type 1 diabetes and 36 with type 2 diabetes), nine family members and 30 healthcare staff participated. Five themes were identified: (a) Severe mental illness governs everyday life including diabetes management; (b) mood influences capacity and motivation for diabetes self-management; (c) cumulative burden of managing multiple physical conditions; (d) interacting conditions and overlapping symptoms and (e) support for everyday challenges. People living with the co-morbidity and their family members emphasised the importance of receiving support for the everyday challenges that impact diabetes management, and identified barriers to accessing this from healthcare providers.

CONCLUSIONS

More intensive support for diabetes management is needed when people's severe mental illness (including symptoms of depression) or physical health deteriorates. Interventions that help people, including healthcare staff, distinguish between symptoms of diabetes and severe mental illness are also needed.

Bipolar disorder prevalence and psychotropic medication utilisation in Hong Kong and the United Kingdom

Purpose

Bipolar disorder (BPD) is often an under-addressed mental disorder. Limited studies have investigated its epidemiology and drug utilisation in Hong Kong (HK) and the United Kingdom (UK) and thus local prescribing practices remain unclear. This study aimed to determine the prevalence of BPD and the prescribing of psychotropic medications as maintenance treatment from 2001-2018 in HK and the UK.

Method

A retrospective study using the data from Clinical Data Analysis and Reporting System in HK and IQVIA Medical Research Data in the UK.

Results

The prevalence of BPD diagnosis in HK and the UK more than doubled during study period. Some distinct changes in prescribing pattern over time were observed. Lithium use declined by 2.46% and 14.58% in HK and the UK, respectively. By 2018, patients were 4.6 times more likely to receive antidepressant monotherapy in the UK versus HK (15.62% vs 3.42%). In HK, 38.41% of women of childbearing age were prescribed valproate in 2018 compared with 8.46% in the UK.

Conclusion

The prevalence of BPD diagnosis has been increasing in HK and the UK. The disparity in prescribing patterns of BPD maintenance treatment in two regions reflected three major issues in clinical practice: 1) under-prescribing of lithium in both regions, 2) antidepressant monotherapy in the UK and 3) overprescribing of valproate to women of childbearing age in HK. Review of current clinical treatment guidelines and regulations of prescribing practice by local clinicians should be immediately implemented to ensure the safe use of medications in patients with BPD.

Cigarette smoking as a risk factor for schizophrenia or all non-affective psychoses

BACKGROUND

Smoking tobacco is regarded as an epiphenomenon in patients with schizophrenia when it may be causal. We aimed to examine whether smoking status is related to the onset of schizophrenia or the broader diagnosis of non-affective psychosis, including schizophrenia.

METHODS

We used data from The Health Improvement Network primary care database to identify people aged 15-24 between 1 January 2004 and 31 December 2009. We followed them until the earliest of: first diagnosis of schizophrenia (or psychosis), patient left the practice, practice left THIN, patient died or 31 December 2014.

RESULTS

In men, incidence rates for schizophrenia per 100 000 person years at risk were higher in smoking initiators (non-smoker who became a smoker during the study) than in non-smokers (adjusted IRR 1.94; 95% CI 1.29-2.91) and higher still in smokers (adjusted IRR 3.32; 95% CI 2.67-4.14). Among women, the incidence rate of schizophrenia was higher in smokers than in non-smokers (adjusted IRR 1.50; 95% CI 1.06-2.12), but no higher in smoking initiators than non-smokers. For non-affective psychosis, the pattern was similar for men but more evident in women where psychosis incidence rates were higher in smoking initiators (adjusted IRR 1.90; 95% CI 1.40-2.56) and in smokers (adjusted IRR 2.13; 95% CI 1.76-2.57) than in non-smokers.

CONCLUSIONS

We found an important and strong association between smoking and incidence of schizophrenia. Smoking may increase risk through as yet unknown pathways or smoking may share genetic risk with schizophrenia and non-affective psychoses.

A comparison of clinical outcomes, service satisfaction and well-being in people using acute day units and crisis resolution teams: cohort study in England

BACKGROUND

For people in mental health crisis, acute day units (ADUs) provide daily structured sessions and peer support in non-residential settings, often as an addition or alternative to crisis resolution teams (CRTs). There is little recent evidence about outcomes for those using ADUs, particularly compared with those receiving CRT care alone.

AIMS

We aimed to investigate readmission rates, satisfaction and well-being outcomes for people using ADUs and CRTs.

METHOD

We conducted a cohort study comparing readmission to acute mental healthcare during a 6-month period for ADU and CRT participants. Secondary outcomes included satisfaction (Client Satisfaction Questionnaire), well-being (Short Warwick-Edinburgh Mental Well-being Scale) and depression (Center for Epidemiologic Studies Depression Scale).

RESULTS

We recruited 744 participants (ADU: n = 431, 58%; CRT: n = 312, 42%) across four National Health Service trusts/health regions. There was no statistically significant overall difference in readmissions: 21% of ADU participants and 23% of CRT participants were readmitted over 6 months (adjusted hazard ratio 0.78, 95% CI 0.54-1.14). However, readmission results varied substantially by setting. At follow-up, ADU participants had significantly higher Client Satisfaction Questionnaire scores (2.5, 95% CI 1.4-3.5, P < 0.001) and well-being scores (1.3, 95% CI 0.4-2.1, P = 0.004), and lower depression scores (-1.7, 95% CI -2.7 to -0.8, P < 0.001), than CRT participants.

CONCLUSIONS

Patients who accessed ADUs demonstrated better outcomes for satisfaction, well-being and depression, and no significant differences in risk of readmission, compared with those who only used CRTs. Given the positive outcomes for patients, and the fact that ADUs are inconsistently provided in the National Health Service, their value and place in the acute care pathway needs further consideration and research.

Time trends in the incidence of clinically diagnosed type 2 diabetes and pre-diabetes in the UK 2009-2018: a retrospective cohort study

INTRODUCTION

To describe recent trends in the incidence of clinically diagnosed type 2 diabetes and pre-diabetes in people seen in UK general practice.

RESEARCH DESIGN AND METHODS

A retrospective cohort study using IQVIA Medical Research Data looking at people newly diagnosed with type 2 diabetes and pre-diabetes through primary care registers in the UK between 1 January 2009 and 31 December 2018.

RESULTS

A cohort of 426 717 people were clinically diagnosed with type 2 diabetes and 418 656 people met the criteria for a diagnosis of pre-diabetes in that time period. The incidence of clinically diagnosed type 2 diabetes per 1000 person years at risk (PYAR) in men decreased from a peak of 5.06 per 1000 PYAR (95% CI 4.97 to 5.15) in 2013 to 3.56 per 1000 PYAR (95% CI 3.46 to 3.66) by 2018. For women, the incidence of clinically diagnosed type 2 diabetes per 1000 PYAR decreased from 4.45 (95% CI 4.37 to 4.54) in 2013 to 2.85 (2.76 to 2.93) in 2018. The incidence rate of pre-diabetes tripled by the end of the same study period in men and women.

CONCLUSIONS

Between 2009 and 2018, the incidence rate of new clinical diagnoses of type 2 diabetes recorded in a UK primary care database decreased by a third from its peak in 2013-2014, while the incidence of pre-diabetes has tripled. The implications of this on timely treatment, complication rates and mortality need further longer term exploration.

Severe mental illness diagnosis in English general hospitals 2006-2017: A registry linkage study

BACKGROUND

The higher mortality rates in people with severe mental illness (SMI) may be partly due to inadequate integration of physical and mental healthcare. Accurate recording of SMI during hospital admissions has the potential to facilitate integrated care including tailoring of treatment to account for comorbidities. We therefore aimed to investigate the sensitivity of SMI recording within general hospitals, changes in diagnostic accuracy over time, and factors associated with accurate recording.

METHODS AND FINDINGS

We undertook a cohort study of 13,786 adults with SMI diagnosed during 2006-2017, using data from a large secondary mental healthcare database as reference standard, linked to English national records for 45,706 emergency hospital admissions. We examined general hospital record sensitivity across patients' subsequent hospital records, for each subsequent emergency admission, and at different levels of diagnostic precision. We analyzed time trends during the study period and used logistic regression to examine sociodemographic and clinical factors associated with psychiatric recording accuracy, with multiple imputation for missing data. Sensitivity for recording of SMI as any mental health diagnosis was 76.7% (95% CI 76.0-77.4). Category-level sensitivity (e.g., proportion of individuals with schizophrenia spectrum disorders (F20-29) who received any F20-29 diagnosis in hospital records) was 56.4% (95% CI 55.4-57.4) for schizophrenia spectrum disorder and 49.7% (95% CI 48.1-51.3) for bipolar affective disorder. Sensitivity for SMI recording in emergency admissions increased from 47.8% (95% CI 43.1-52.5) in 2006 to 75.4% (95% CI 68.3-81.4) in 2017 (ptrend < 0.001). Minority ethnicity, being married, and having better mental and physical health were associated with less accurate diagnostic recording. The main limitation of our study is the potential for misclassification of diagnosis in the reference-standard mental healthcare data.

CONCLUSIONS

Our findings suggest that there have been improvements in recording of SMI diagnoses, but concerning under-recording, especially in minority ethnic groups, persists. Training in culturally sensitive diagnosis, expansion of liaison psychiatry input in general hospitals, and improved data sharing between physical and mental health services may be required to reduce inequalities in diagnostic practice.

Area deprivation, urbanicity, severe mental illness and social drift - A population-based linkage study using routinely collected primary and secondary care data

We investigated whether associations between area deprivation, urbanicity and elevated risk of severe mental illnesses (SMIs, including schizophrenia and bipolar disorder) is accounted for by social drift or social causation. We extracted primary and secondary care electronic health records from 2004 to 2015 from a population of 3.9 million. We identified prevalent and incident individuals with SMIs and their level of deprivation and urbanicity using the Welsh Index of Multiple Deprivation (WIMD) and urban/rural indicator. The presence of social drift was determined by whether odds ratios (ORs) from logistic regression is greater than the incidence rate ratios (IRRs) from Poisson regression. Additionally, we performed longitudinal analysis to measure the proportion of change in deprivation level and rural/urban residence 10 years after an incident diagnosis of SMI and compared it to the general population using standardised rate ratios (SRRs). Prevalence and incidence of SMIs were significantly associated with deprivation and urbanicity (all ORs and IRRs significantly >1). ORs and IRRs were similar across all conditions and cohorts (ranging from 1.1 to 1.4). Results from the longitudinal analysis showed individuals with SMIs are more likely to move compared to the general population. However, they did not preferentially move to more deprived or urban areas. There was little evidence of downward social drift over a 10-year period. These findings have implications for the allocation of resources, service configuration and access to services in deprived communities, as well as, for broader public health interventions addressing poverty, and social and environmental contexts.

Patterns of symptoms before a diagnosis of first episode psychosis: a latent class analysis of UK primary care electronic health records

BACKGROUND

The nature of symptoms in the prodromal period of first episode psychosis (FEP) remains unclear. The objective was to determine the patterns of symptoms recorded in primary care in the 5 years before FEP diagnosis.

METHODS

The study was set within 568 practices contributing to a UK primary care health record database (Clinical Practice Research Datalink). Patients aged 16-45 years with a first coded record of FEP, and no antipsychotic prescription more than 1 year prior to FEP diagnosis (n = 3045) was age, gender, and practice matched to controls without FEP (n = 12,180). Fifty-five symptoms recorded in primary care in the previous 5 years, categorised into 8 groups (mood-related, 'neurotic', behavioural change, volition change, cognitive change, perceptual problem, substance misuse, physical symptoms), were compared between cases and controls. Common patterns of symptoms prior to FEP diagnosis were identified using latent class analysis.

RESULTS

Median age at diagnosis was 30 years, 63% were male. Non-affective psychosis (67%) was the most common diagnosis. Mood-related, 'neurotic', and physical symptoms were frequently recorded (> 30% of patients) before diagnosis, and behavioural change, volition change, and substance misuse were also common (> 10%). Prevalence of all symptom groups was higher in FEP patients than in controls (adjusted odds ratios 1.33-112). Median time from the first recorded symptom to FEP diagnosis was 2-2.5 years except for perceptual problem (70 days). The optimal latent class model applied to FEP patients determined three distinct patient clusters: 'no or minimal symptom cluster' (49%) had no or few symptoms recorded; 'affective symptom cluster' (40%) mainly had mood-related and 'neurotic' symptoms; and 'multiple symptom cluster' (11%) consulted for three or more symptom groups before diagnosis. The multiple symptom cluster was more likely to have drug-induced psychosis, female, obese, and have a higher morbidity burden. Affective and multiple symptom clusters showed a good discriminative ability (C-statistic 0.766; sensitivity 51.2% and specificity 86.7%) for FEP, and many patients in these clusters had consulted for their symptoms several years before FEP diagnosis.

CONCLUSIONS

Distinctive patterns of prodromal symptoms may help alert general practitioners to those developing psychosis, facilitating earlier identification and referral to specialist care, thereby avoiding potentially detrimental treatment delay.

Exploring Severe Mental Illness and Diabetes: Protocol for a Longitudinal, Observational, and Qualitative Mixed Methods Study

Background

The average life expectancy for people with a severe mental illness (SMI) such as schizophrenia or bipolar disorder is 15 to 20 years less than that for the population as a whole. Diabetes contributes significantly to this inequality, being 2 to 3 times more prevalent in people with SMI. Various risk factors have been implicated, including side effects of antipsychotic medication and unhealthy lifestyles, which often occur in the context of socioeconomic disadvantage and health care inequality. However, little is known about how these factors may interact to influence the risk of developing diabetes and poor diabetic outcomes, or how the organization and provision of health care may contribute.

Objective

This study aims to identify the determinants of diabetes and to explore variation in diabetes outcomes for people with SMI.

Methods

This study will employ a concurrent mixed methods design combining the interrogation of electronic primary care health records from the Clinical Practice Research Datalink (CPRD GOLD) with qualitative interviews with adults with SMI and diabetes, their relatives and friends, and health care staff. The study has been funded for 2 years, from September 2017 to September 2019, and data collection has recently ended.

Results

CPRD and linked health data will be used to explore the association of sociodemographics, illness, and health care–related factors with both the development and outcomes of type 2 diabetes in people with SMI. Experiences of managing the comorbidity and accessing health care will be explored through qualitative interviews using topic guides informed by evidence synthesis and expert consultation. Findings from both datasets will be merged to develop a more comprehensive understanding of diabetes risks, interventions, and outcomes for people with SMI. Findings will be translated into recommendations for interventions and services using co-design workshops.

Conclusions

Improving diabetes outcomes for people with SMI is a high-priority area nationally and globally. Understanding how risk factors combine to generate high prevalence of diabetes and poor diabetic outcomes for this population is a necessary first step in developing health care interventions to improve outcomes for people with diabetes and SMI.

Trial Registration

ClinicalTrials.gov NCT03534921; https://clinicaltrials.gov/ct2/show/NCT03534921

High Frequency of Bipolar Disorder Comorbidity in Medical Inpatients

Objective: Bipolar disorder is a severe, disabling, and recurring disorder. Some studies have shown that the frequency of bipolar disorder in patients with medical diseases is higher than healthy controls. The aim of this study was to investigate the frequency of bipolar disorders in medically ill patients hospitalized in Iranian general hospitals. Method : In this cross sectional study, 697 inpatients (342 men, 49.1%) from different wards of 3 general hospitals, with the mean age of 39.3+-10, were enrolled in the study using nonprobability sampling. Demographic questionnaire, Mood Disorder Questionnaire (MDQ) and Bipolar Spectrum Diagnostic Scale (BSDS) were used. Inclusion criteria were as follow: informed consent, age 18-65 years, ability to speak Persian, and having at least middle school education. Results: The frequency of bipolar disorder was 12.1% and 20.8% based on BSDS and MDQ, respectively. The results of both tests were positive in 7.9% of hospitalized patients. The frequency of bipolar mood disorder was significantly higher in single patients and in those with comorbidity of alcohol and substance use disorders. Conclusion: Considering the high frequency of bipolar mood disorders in hospitalized medically ill patients and its probable effects on compliance and prognosis, early screening, diagnosis, and treatment of bipolar mood disorders is important in these patients.

The relationship between childhood adversities and dissociation in severe mental illness: a meta-analytic review

OBJECTIVE

Several studies have observed that dissociative experiences are frequently reported by individuals with severe mental illness (SMI), especially amongst patients that report a history of adverse/traumatic life experiences. This review examined the magnitude and consistency of the relationship between childhood adversity (sexual abuse, physical abuse, emotional abuse, neglect, bullying, natural disasters and mass violence) and dissociation across three SMI diagnostic groups: schizophrenia, bipolar disorder and personality disorders.

METHOD

A database search (EMBASE, PubMed and PsycINFO) identified 30 eligible empirical studies, comprising of 2199 clinical participants. Effect sizes representing the relationship between exposure to childhood adversity and dissociation were examined and integrated using a random-effects meta-analysis.

RESULTS

The results indicated that exposure to childhood trauma was associated with heightened dissociation across SMIs. Positive significant associations were also found between specific childhood adversities and dissociation, with aggregated effect sizes in the small-to-moderate range.

CONCLUSION

These findings support calls for the routine assessment of traumatic experiences in clients with SMIs presenting with dissociative symptoms and the provision of adequate therapeutic support (e.g. trauma-focused therapies) to manage and resolve these difficulties.

Posttraumatic Stress Disorder and Cancer Risk: A Nested Case-Control Study

Data regarding cancer risk for individuals who were exposed to traumatic and stressful life events are conflicting. We sought to evaluate the association between posttraumatic stress disorder (PTSD) and the risk of the four most common solid tumors: lung, breast, prostate, and colorectal cancers. We conducted four nested case-control studies using a large UK population-based database. Cases were defined as individuals with any medical code for the specific malignancy. For every case, we used incidence-density sampling to match four controls by age, sex, practice site, and both duration and calendar time of follow-up. Exposure of interest was any diagnosis of PTSD prior to cancer diagnosis. The odds ratios (ORs) and 95% confidence intervals (CIs) for cancer risk associated with PTSD were estimated using multivariable conditional logistic regression and were adjusted for smoking status, obesity, and antidepressant use. The study population included four case groups according to cancer type. There were 19,143 cases with lung cancer (74,473 matched controls), 22,163 cases with colorectal cancer (86,538 matched controls), 31,352 cases with breast cancer (123,285 matched controls), and 27,212 cases with prostate cancer (105,940 matched controls). There was no statistically significant association between PTSD and cancer risk among any of the cancer types: lung, OR = 0.73, 95% CI [0.43, 1.23]; breast, OR = 0.73, 95% CI [0.52, 1.01]; prostate, OR = 1.24, 95% CI [0.87, 1.77]; and colorectal, OR = 1.05, 95% CI [0.68, 1.62]. Our findings indicated that participants in our study with PTSD were not at increased risk of lung, breast, prostate, and colorectal cancers.

Examining the potential preventative effects of minocycline prescribed for acne on the incidence of severe mental illnesses: A historical cohort study

BACKGROUND

Animal studies suggest that the antibiotic and microglial activation inhibitor, minocycline, is likely to have a protective effect against the emergence of psychosis but evidence from human studies is lacking. The aim of this study is to examine the effects of exposure to minocycline during adolescence on the later incidence of severe mental illness (SMI).

METHODS

A historical cohort study using electronic primary care data was conducted to assess the association between exposure to minocycline during adolescence and incidence of SMI. The Incidence Rate Ratio (IRR) was measured using Poisson regression adjusted for age, gender, time of exposure, socioeconomic deprivation status, calendar year and co-medications.

RESULTS

Early minocycline prescription ( n=13,248) did not affect the incidence of SMI compared with non-prescription of minocycline ( n=14,393), regardless of gender or whether or not the data were filtered according to a minimum exposure period (minimum period: IRR 0.96; 95% CI 0.68-1.36; p=0.821; no minimum period: IRR 1.08; 95% CI 0.83-1.42; p=0.566).

CONCLUSIONS

Exposure to minocycline for acne treatment during adolescence appears to have no effect on the incidence of SMI.

Statin prescribing for prevention of cardiovascular disease amongst people with severe mental illness: Cohort study in UK primary care

BACKGROUND

Severe mental illness (SMI) is associated with excess cardiovascular disease (CVD) morbidity, but little is known on provision of preventative interventions. We investigated statin initiation for primary CVD prevention in individuals with and without SMI.

METHODS

We used primary care data from The Health Improvement Network from 2006 to 2015 for UK patients aged 30-99years with no pre-existing CVD conditions and selected individuals with schizophrenia (n=13,252) or bipolar disorder (n=11,994). In addition, we identified samples of individuals without schizophrenia (n=66,060) and bipolar disorder (n=59,765), but with similar age and gender distribution. Missing data on CVD covariates were estimated using multiple imputation. Statin prescribing differences between individuals with and without SMI were investigated using multivariable Poisson regression models.

RESULTS

Initiation of statin prescribing was between 2 and 3 fold higher in people aged 30-59years with SMI than in those without after adjusting for CVD covariates. The rates in those aged 60-74years with SMI were similar or slightly higher relative to those without SMI. The incidence rate ratio (IRR) was 1.15 (95% CI 1.03-1.28) for bipolar disorder and 1.00 (0.91-1.11) for schizophrenia. The rate of statin prescribing was lower (IRR 0.81 (0.66-0.98)) amongst the oldest (aged 75+years) with schizophrenia relative to those without schizophrenia.

CONCLUSIONS

Despite higher rates of new statin prescriptions to younger individuals with SMI relative to individuals without SMI, there was evidence of lower rates of statin initiation for older individuals with schizophrenia, and this group may benefit from additional measures to prevent CVD.

Effectiveness and cost-effectiveness of a cardiovascular risk prediction algorithm for people with severe mental illness (PRIMROSE)

OBJECTIVES

To determine the cost-effectiveness of two bespoke severe mental illness (SMI)-specific risk algorithms compared with standard risk algorithms for primary cardiovascular disease (CVD) prevention in those with SMI.

SETTING

Primary care setting in the UK. The analysis was from the National Health Service perspective.

PARTICIPANTS

1000 individuals with SMI from The Health Improvement Network Database, aged 30-74 years and without existing CVD, populated the model.

INTERVENTIONS

Four cardiovascular risk algorithms were assessed: (1) general population lipid, (2) general population body mass index (BMI), (3) SMI-specific lipid and (4) SMI-specific BMI, compared against no algorithm. At baseline, each cardiovascular risk algorithm was applied and those considered high risk (> 10%) were assumed to be prescribed statin therapy while others received usual care.

PRIMARY AND SECONDARY OUTCOME MEASURES

Quality-adjusted life years (QALYs) and costs were accrued for each algorithm including no algorithm, and cost-effectiveness was calculated using the net monetary benefit (NMB) approach. Deterministic and probabilistic sensitivity analyses were performed to test assumptions made and uncertainty around parameter estimates.

RESULTS

The SMI-specific BMI algorithm had the highest NMB resulting in 15 additional QALYs and a cost saving of approximately £53 000 per 1000 patients with SMI over 10 years, followed by the general population lipid algorithm (13 additional QALYs and a cost saving of £46 000).

CONCLUSIONS

The general population lipid and SMI-specific BMI algorithms performed equally well. The ease and acceptability of use of an SMI-specific BMI algorithm (blood tests not required) makes it an attractive algorithm to implement in clinical settings.

Mortality gap for people with bipolar disorder and schizophrenia: UK-based cohort study 2000-2014

BackgroundBipolar disorder and schizophrenia are associated with increased mortality relative to the general population. There is an international emphasis on decreasing this excess mortality.AimsTo determine whether the mortality gap between individuals with bipolar disorder and schizophrenia and the general population has decreased.MethodA nationally representative cohort study using primary care electronic health records from 2000 to 2014, comparing all patients diagnosed with bipolar disorder or schizophrenia and the general population. The primary outcome was all-cause mortality.ResultsIndividuals with bipolar disorder and schizophrenia had elevated mortality (adjusted hazard ratio (HR) = 1.79, 95% CI 1.67-1.88 and 2.08, 95% CI 1.98-2.19 respectively). Adjusted HRs for bipolar disorder increased by 0.14/year (95% CI 0.10-0.19) from 2006 to 2014. The adjusted HRs for schizophrenia increased gradually from 2004 to 2010 (0.11/year, 95% CI 0.04-0.17) and rapidly after 2010 (0.34/year, 95% CI 0.18-0.49).ConclusionsThe mortality gap between individuals with bipolar disorder and schizophrenia, and the general population is widening.

Prevalence and risk factors for HIV, hepatitis B, and hepatitis C in people with severe mental illness: a total population study of Sweden

BACKGROUND

Severe mental illness is associated with increased morbidity and mortality. The elevated risk of blood-borne viruses (BBVs) in people with severe mental illness is of concern, but the full extent of this problem is unclear. We aimed to determine the prevalence of and risk factors for BBVs in people with severe mental illness.

METHODS

In this nationwide, population-based, cross-sectional study, we estimated the point prevalence of HIV, hepatitis B (HBV), and hepatitis C (HCV) in people with severe mental illness, including the total adult (≥18 years) Swedish population. We defined severe mental illness as a clinical diagnosis of schizophrenia, schizoaffective disorder, bipolar disorder, or other psychotic illness according to the Swedish version of the International Statistical Classification of Diseases version 8, 9, or 10. We used multivariable logistic regression to determine the odds of BBVs in individuals with severe mental illness, relative to the general population, and to identify independent risk factors (age, sex, immigration status, socioeconomic status, education, and substance misuse) for BBV infection. We also did a sensitivity analysis excluding BBV diagnoses made before the introduction of the Register for Infection Disease Control (1997).

FINDINGS

Of 6 815 931 adults in Sweden, 97 797 (1·43%) individuals had a diagnosis of severe mental illness. Prevalence of BBVs was elevated in people with severe mental illness, of which 230 (0·24%) had HIV, 518 (0·53%) had HBV, and 4476 (4·58%) had HCV. After accounting for sociodemographic characteristics, the odds of HIV were 2·57 (95% CI 2·25-2·94, p<0·0001) times higher in people with severe mental illness than in the general population, whereas the odds of HBV were 2·29 (2·09-2·51, p<0·0001) times higher and the odds of HCV were 6·18 (5·98-6·39, p<0·0001) times higher. Substance misuse contributed most to the increased risk of BBV: after adjustment, odds ratios were 1·61 (1·40-1·85, p<0·0001) for HIV, 1·28 (1·16-1·41, p<0·0001) for HBV, and 1·72 (1·67-1·78, p<0·0001) for HCV.

INTERPRETATION

Our results highlight the need to address the issue of higher prevalence of BBVs in people with severe mental illness and identify interventions preventing infection. Targeting of comorbid substance misuse would have particular effect on reduction of BBV prevalence in this population.

FUNDING

Medical Research Council and Swedish Research Council.

Type 2 diabetes mellitus in people with severe mental illness: inequalities by ethnicity and age. Cross-sectional analysis of 588 408 records from the UK

AIMS

To investigate whether the association of severe mental illness with Type 2 diabetes varies by ethnicity and age.

METHODS

We conducted a cross-sectional analysis of data from an ethnically diverse sample of 588 408 individuals aged ≥18 years, registered to 98% of general practices (primary care) in London, UK. The outcome of interest was prevalent Type 2 diabetes.

RESULTS

Relative to people without severe mental illness, the relative risk of Type 2 diabetes in people with severe mental illness was greatest in the youngest age groups. In the white British group the relative risks were 9.99 (95% CI 5.34, 18.69) in those aged 18-34 years, 2.89 (95% CI 2.43, 3.45) in those aged 35-54 years and 1.16 (95% CI 1.04, 1.30) in those aged ≥55 years, with similar trends across all ethnic minority groups. Additional adjustment for anti-psychotic prescriptions only marginally attenuated the associations. Assessment of estimated prevalence of Type 2 diabetes in severe mental illness by ethnicity (absolute measures of effect) indicated that the association between severe mental illness and Type 2 diabetes was more marked in ethnic minorities than in the white British group with severe mental illness, especially for Indian, Pakistani and Bangladeshi individuals with severe mental illness.

CONCLUSIONS

The relative risk of Type 2 diabetes is elevated in younger populations. Most associations persisted despite adjustment for anti-psychotic prescriptions. Ethnic minority groups had a higher prevalence of Type 2 diabetes in the presence of severe mental illness. Future research and policy, particularly with respect to screening and clinical care for Type 2 diabetes in populations with severe mental illness, should take these findings into account.

Linked Hospital and Primary Care Database Analysis of the Incidence and Impact of Psychiatric Morbidity Following Gastrointestinal Cancer Surgery in England

OBJECTIVE

To evaluate risk of psychiatric morbidity and its impact on survival in gastrointestinal surgery.

BACKGROUND

Psychiatric morbidity related to surgery is poorly understood, and may be evaluated using linked hospital and primary care data.

METHODS

Patients undergoing gastrointestinal surgery from 2000 to 2011 with linkage of Clinical Practice Research Datalink (CPRD), Hospital Episodes Statistics (HES), Office of National Statistics (ONS), and National Cancer Intelligence Network (NCIN) databases were studied. Psychiatric morbidity was defined as a diagnosis code in CPRD or HES, or a prescription code for psychiatric medication in the 36 months before (preoperative) or 12 months after (postoperative) surgery. Newly diagnosed psychiatric morbidity was measured in patients without preoperative psychiatric morbidity.

RESULTS

In our study, 14,797 (23.8%) and 47,279 (76.2%) patients had surgery for cancer and benign disease, respectively. Postoperative psychiatric morbidity was observed in 10.1% (1500/14797) of patients undergoing cancer surgery. Logistic regression revealed that when adjusted for other factors, cancer diagnosis [odds ratio (OR) = 1.19] independently predicted postoperative psychiatric morbidity (P < 0.05). Hepatopancreaticobiliary resection (OR = 2.40) and esophagogastrectomy (OR = 2.55) carried the highest risks of postoperative psychiatric morbidity (P < 0.05). Preoperative psychiatric morbidity (OR = 1.16) and newly diagnosed psychiatric morbidity (OR = 1.87) were associated with increased 1-year mortality in cancer patients only (P < 0.05).

CONCLUSIONS

Postoperative psychiatric morbidity affected a tenth of patients who underwent gastrointestinal cancer surgery and was associated with increased mortality. Strategies to identify patients at risk preoperatively and to reduce the observed adverse impact of postoperative psychiatric morbidity should be part of perioperative care in complex cancer patients.

Relative risks of cardiovascular disease in people prescribed olanzapine, risperidone and quetiapine

Antipsychotics may confer long term benefits and risks, including cardiovascular disease (CVD) risk. Several studies using routine clinical data have reported associations between antipsychotics and CVD but potential confounding factors and unclear classification of drug exposure limits their interpretation.

METHOD

We used data from The Health Improvement Network, a large UK primary care database to determine relative risks of (CVD) comparing similar groups of people only prescribed olanzapine versus either risperidone or quetiapine. We included participants over 18 between 1995 and 2011. To assess confounding factors we created propensity scores for being prescribed each antipsychotic. We used propensity score matching and Poisson regression to calculate the CVD incidence rate ratios for olanzapine versus the other two drugs.

RESULTS

We identified 18,319 people who received a single antipsychotic during follow-up (n=5090 risperidone, 7797 olanzapine and 4613 quetiapine). In unmatched analyses, the CVD incidence rate ratio (IRR) for olanzapine versus risperidone was 0.63 (0.51-0.77) but the propensity score matched IRR was 0.78 (0.61-1.02). In the unmatched olanzapine versus quetiapine analysis the IRR adjusted for age and sex for olanzapine was 1.52 (1.16-1.98) but the propensity score matched analysis gave an IRR of 1.08 (0.79-1.46).

CONCLUSIONS

After propensity score matching, we found no statistical differences in CVD incidence between olanzapine and either risperidone or quetiapine. Analyses which did not account for confounding factors produced very different results. Researchers must address confounding factors when designing observational studies to assess adverse outcomes of drugs, including antipsychotics.

Development and Validation of a Clinically Based Risk Calculator for the Transdiagnostic Prediction of Psychosis

Importance

The overall effect of At Risk Mental State (ARMS) services for the detection of individuals who will develop psychosis in secondary mental health care is undetermined.

Objective

To measure the proportion of individuals with a first episode of psychosis detected by ARMS services in secondary mental health services, and to develop and externally validate a practical web-based individualized risk calculator tool for the transdiagnostic prediction of psychosis in secondary mental health care.

Design, Setting, and Participants

Clinical register-based cohort study. Patients were drawn from electronic, real-world, real-time clinical records relating to 2008 to 2015 routine secondary mental health care in the South London and the Maudsley National Health Service Foundation Trust. The study included all patients receiving a first index diagnosis of nonorganic and nonpsychotic mental disorder within the South London and the Maudsley National Health Service Foundation Trust in the period between January 1, 2008, and December 31, 2015. Data analysis began on September 1, 2016.

Main Outcomes and Measures

Risk of development of nonorganic International Statistical Classification of Diseases and Related Health Problems, Tenth Revision psychotic disorders.

Results

A total of 91 199 patients receiving a first index diagnosis of nonorganic and nonpsychotic mental disorder within South London and the Maudsley National Health Service Foundation Trust were included in the derivation (n = 33 820) or external validation (n = 54 716) data sets. The mean age was 32.97 years, 50.88% were men, and 61.05% were white race/ethnicity. The mean follow-up was 1588 days. The overall 6-year risk of psychosis in secondary mental health care was 3.02 (95% CI, 2.88-3.15), which is higher than the 6-year risk in the local general population (0.62). Compared with the ARMS designation, all of the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision diagnoses showed a lower risk of psychosis, with the exception of bipolar mood disorders (similar risk) and brief psychotic episodes (higher risk). The ARMS designation accounted only for a small proportion of transitions to psychosis (n = 52 of 1001; 5.19% in the derivation data set), indicating the need for transdiagnostic prediction of psychosis in secondary mental health care. A prognostic risk stratification model based on preselected variables, including index diagnosis, age, sex, age by sex, and race/ethnicity, was developed and externally validated, showing good performance and potential clinical usefulness.

Conclusions and Relevance

This online individualized risk calculator can be of clinical usefulness for the transdiagnostic prediction of psychosis in secondary mental health care. The risk calculator can help to identify those patients at risk of developing psychosis who require an ARMS assessment and specialized care. The use of this calculator may eventually facilitate the implementation of an individualized provision of preventive focused interventions and improve outcomes of first episode psychosis.

Impact of Financial Incentives on Alcohol Consumption Recording in Primary Health Care Among Adults with Schizophrenia and Other Psychoses: A Cross-Sectional and Retrospective Cohort Study

Aims

Lack of financial incentive is a frequently cited barrier to alcohol screening in primary care. The Quality and Outcomes Framework (QOF) pay for performance scheme has reimbursed UK primary care practices for alcohol screening in people with schizophrenia since April 2011. This study aimed to determine the impact of financial incentives on alcohol screening by comparing rates of alcohol recording in people with versus those without schizophrenia between 2000 and 2013.

Methods

Cross-sectional and retrospective cohort study. Alcohol data were extracted from The Health Improvement Network (THIN) database of UK primary care records using (a) Read Codes for level of alcohol consumption, (b) continuous measures of drinking (e.g. units a week) and (c) Read Codes for types of screening test.

Results

A total of 14,860 individuals (54% (8068) men and 46% (6792) women) from 409 general practices aged 18–99 years with schizophrenia were identified during April 2011–March 2013. Of these, 11,585 (78%) had an alcohol record, of which 99% (8150/8257) of Read Codes for level of consumption were eligible for recompense in the QOF. There was an 839% increase in alcohol recording among people with schizophrenia over the 13-year period (rate ratio per annum increase 1.19 (95% CI 1.18–1.20)) compared with a 62% increase among people without a severe mental illness (rate ratio per annum increase 1.04 (95% CI 1.03–1.05)).

Conclusion

Financial incentives offered by the QOF appear to have a substantial impact on alcohol screening among people with schizophrenia in UK primary care.

Short summary

Alcohol screening among people with schizophrenia increased dramatically in primary health care following the introduction of the UK pay for performance incentive scheme (Quality and Outcomes Framework) for severe mental illness, with an 839% rise (>8-fold increase) compared with a 62% increase among people without a over the 13-year study period (2000–2013).

Statin prescribing for people with severe mental illnesses: a staggered cohort study of 'real-world' impacts

OBJECTIVES

To estimate the 'real-world effectiveness of statins for primary prevention of cardiovascular disease (CVD) and for lipid modification in people with severe mental illnesses (SMI), including schizophrenia and bipolar disorder.

DESIGN

Series of staggered cohorts. We estimated the effect of statin prescribing on CVD outcomes using a multivariable Poisson regression model or linear regression for cholesterol outcomes.

SETTING

587 general practice (GP) surgeries across the UK reporting data to The Health Improvement Network.

PARTICIPANTS

All permanently registered GP patients aged 40-84 years between 2002 and 2012 who had a diagnosis of SMI. Exclusion criteria were pre-existing CVD, statin-contraindicating conditions or a statin prescription within the 24 months prior to the study start.

EXPOSURE

One or more statin prescriptions during a 24-month 'baseline' period (vs no statin prescription during the same period).

MAIN OUTCOME MEASURES

The primary outcome was combined first myocardial infarction and stroke. All-cause mortality and total cholesterol concentration were secondary outcomes.

RESULTS

We identified 2944 statin users and 42 886 statin non-users across the staggered cohorts. Statin prescribing was not associated with significant reduction in CVD events (incident rate ratio 0.89; 95% CI 0.68 to 1.15) or all-cause mortality (0.89; 95% CI 0.78 to 1.02). Statin prescribing was, however, associated with statistically significant reductions in total cholesterol of 1.2 mmol/L (95% CI 1.1 to 1.3) for up to 2 years after adjusting for differences in baseline characteristics. On average, total cholesterol decreased from 6.3 to 4.6 in statin users and 5.4 to 5.3 mmol/L in non-users.

CONCLUSIONS

We found that statin prescribing to people with SMI in UK primary care was effective for lipid modification but not CVD events. The latter finding may reflect insufficient power to detect a smaller effect size than that observed in randomised controlled trials of statins in people without SMI.

Natural language processing to extract symptoms of severe mental illness from clinical text: the Clinical Record Interactive Search Comprehensive Data Extraction (CRIS-CODE) project

OBJECTIVES

We sought to use natural language processing to develop a suite of language models to capture key symptoms of severe mental illness (SMI) from clinical text, to facilitate the secondary use of mental healthcare data in research.

DESIGN

Development and validation of information extraction applications for ascertaining symptoms of SMI in routine mental health records using the Clinical Record Interactive Search (CRIS) data resource; description of their distribution in a corpus of discharge summaries.

SETTING

Electronic records from a large mental healthcare provider serving a geographic catchment of 1.2 million residents in four boroughs of south London, UK.

PARTICIPANTS

The distribution of derived symptoms was described in 23 128 discharge summaries from 7962 patients who had received an SMI diagnosis, and 13 496 discharge summaries from 7575 patients who had received a non-SMI diagnosis.

OUTCOME MEASURES

Fifty SMI symptoms were identified by a team of psychiatrists for extraction based on salience and linguistic consistency in records, broadly categorised under positive, negative, disorganisation, manic and catatonic subgroups. Text models for each symptom were generated using the TextHunter tool and the CRIS database.

RESULTS

We extracted data for 46 symptoms with a median F1 score of 0.88. Four symptom models performed poorly and were excluded. From the corpus of discharge summaries, it was possible to extract symptomatology in 87% of patients with SMI and 60% of patients with non-SMI diagnosis.

CONCLUSIONS

This work demonstrates the possibility of automatically extracting a broad range of SMI symptoms from English text discharge summaries for patients with an SMI diagnosis. Descriptive data also indicated that most symptoms cut across diagnoses, rather than being restricted to particular groups.

Long-term validity of the At Risk Mental State (ARMS) for predicting psychotic and non-psychotic mental disorders

BACKGROUND

The long-term clinical validity of the At Risk Mental State (ARMS) for the prediction of non-psychotic mental disorders is unknown.

METHODS

Clinical register-based cohort study including all non-psychotic individuals assessed by the Outreach And Support in South London (OASIS) service (2002-2015). The primary outcome was risk of developing any mental disorder (psychotic or non-psychotic). Analyses included Cox proportional hazard models, Kaplan-Meier survival/failure function and C statistics.

RESULTS

A total of 710 subjects were included. A total of 411 subjects were at risk (ARMS+) and 299 not at risk (ARMS-). Relative to ARMS-, the ARMS+ was associated with an increased risk (HR=4.825) of developing psychotic disorders, and a reduced risk (HR=0.545) of developing non-psychotic disorders (mainly personality disorders). At 6-year, the ARMS designation retained high sensitivity (0.873) but only modest specificity (0.456) for the prediction of psychosis onset (AUC 0.68). The brief and limited intermittent psychotic symptoms (BLIPS) subgroup had a higher risk of developing psychosis, and a lower risk of developing non-psychotic disorders as compared to the attenuated psychotic symptoms (APS) subgroup (P<0.001).

CONCLUSIONS

In the long-term, the ARMS specifically predicts the onset of psychotic disorders, with modest accuracy, but not of non-psychotic disorders. Individuals meeting BLIPS criteria have distinct clinical outcomes.

SIGNIFICANT OUTCOMES

In the long-term, the ARMS designation is still significantly associated with an increased risk of developing psychotic disorders but its prognostic accuracy is only modest. There is no evidence that the ARMS is associated with an increased risk of developing non-psychotic mental disorders. The BLIPS subgroup at lower risk of developing non-psychotic disorders compared to the APS subgroup.

LIMITATIONS

While incident diagnoses employed in this study are high in ecological validity they have not been subjected to formal validation with research-based criteria.