In-patient mental health rehabilitation services provide specialist treatment to people with complex psychosis. On average, rehabilitation admissions last around a year and usually follow several years of recurrent and often lengthy psychiatric hospital admissions.

To compare in-patient service use before and after an in-patient rehabilitation admission, using electronic patient healthcare records in one National Health Service Trust in London.

We carried out a retrospective cohort study comprised of individuals with an in-patient rehabilitation admission lasting ≥84 days between 1 January 2010 and 30 April 2019, with at least ≥365 days of records available before and after their rehabilitation admission. We used negative binomial regression models to compare the number of in-patient days before and after the rehabilitation admission.

A total of 172 individuals met our eligibility criteria. The median percentage of days spent as an in-patient before the rehabilitation admission was 29% (interquartile range 18–52%), and 8% (interquartile range 0–31%) after the admission. The regression model adjusted for potential confounder variables produced an incidence rate ratio of 0.520 (95% CI 0.367–0.737).

The rate of in-patient service use was halved in the period after an in-patient rehabilitation admission compared with the period before. This suggests that in-patient rehabilitation is a clinical and cost-effective intervention in the treatment and support of people with complex psychosis.

There is currently no definitive method for identifying individuals with psychosis in secondary care on a population-level using administrative healthcare data from England.

To develop various algorithms to identify individuals with psychosis in the Mental Health Services Data Set (MHSDS), guided by national estimates of the prevalence of psychosis.

Using a combination of data elements in the MHSDS for financial years 2017–2018 and 2018–2019 (mental health cluster (a way to describe and classify a group of individuals with similar characteristics), Health of the Nation Outcome Scale (HoNOS) scores, reason for referral, primary diagnosis, first-episode psychosis flag, early intervention in psychosis team flag), we developed 12 unique algorithms to detect individuals with psychosis seen in secondary care. The resulting numbers were then compared with national estimates of the prevalence of psychosis to ascertain whether they were reasonable or not.

The 12 algorithms produced 99 204–138 516 and 107 545–134 954 cases of psychosis for financial years 2017–2018 and 2018–2019, respectively, in line with national prevalence estimates. The numbers of cases of psychosis identified by the different algorithms differed according to the type and number (3–6) of data elements used. Most algorithms identified the same core of patients.

The MHSDS can be used to identify individuals with psychosis in secondary care in England. Users can employ several algorithms to do so, depending on the objective of their analysis and their preference regarding the data elements employed. These algorithms could be used for surveillance, research and/or policy purposes.

Contemporary data relating to antipsychotic prescribing in UK primary care for patients diagnosed with severe mental illness (SMI) are lacking.

To describe contemporary patterns of antipsychotic prescribing in UK primary care for patients diagnosed with SMI.

Cohort study of patients with an SMI diagnosis (i.e. schizophrenia, bipolar disorder, other non-organic psychoses) first recorded in primary care between 2000 and 2017 derived from Clinical Practice Research Datalink. Patients were considered exposed to antipsychotics if prescribed at least one antipsychotic in primary care between 2000 and 2019. We compared characteristics of patients prescribed and not prescribed antipsychotics; calculated annual prevalence rates for antipsychotic prescribing; and computed average daily antipsychotic doses stratified by patient characteristics.

Of 309 378 patients first diagnosed with an SMI in primary care between 2000 and 2017, 212,618 (68.7%) were prescribed an antipsychotic between 2000 and 2019. Antipsychotic prescribing prevalence was 426 (95% CI, 420–433) per 1000 patients in the year 2000, reaching a peak of 550 (547–553) in 2016, decreasing to 470 (468–473) in 2019. The proportion prescribed antipsychotics was higher among patients diagnosed with schizophrenia (81.0%) than with bipolar disorder (64.6%) and other non-organic psychoses (65.7%). Olanzapine, quetiapine, risperidone and aripiprazole accounted for 78.8% of all antipsychotic prescriptions. Higher mean olanzapine equivalent total daily doses were prescribed to patients with the following characteristics: schizophrenia diagnosis, ethnic minority status, male gender, younger age and greater relative deprivation.

Antipsychotic prescribing is dominated by olanzapine, quetiapine, risperidone and aripiprazole. We identified potential disparities in both the receipt and prescribed doses of antipsychotics across subgroups. To inform efforts to optimise prescribing and ensure equity of care, further research is needed to understand why certain groups are prescribed higher doses and are more likely to be treated with long-acting injectable antipsychotics compared with others.

Delirium is a severe neuropsychiatric syndrome caused by physical illness, associated with high mortality. Understanding risk factors for delirium is key to targeting prevention and screening. Whether severe mental illness (SMI) predisposes people to delirium is not known. We aimed to establish whether pre-existing SMI diagnosis is associated with higher risk of delirium diagnosis and mortality following delirium diagnosis.

A retrospective cohort and nested case–control study using linked primary and secondary healthcare databases from 2000–2017. We identified people diagnosed with SMI, matched to non-SMI comparators. We compared incidence of delirium diagnoses between people with SMI diagnoses and comparators, and between SMI subtypes; schizophrenia, bipolar disorder and ‘other psychosis’. We compared 30-day mortality following a hospitalisation involving delirium between people with SMI diagnoses and comparators, and between SMI subtypes.

We identified 20 566 people with SMI diagnoses, matched to 71 374 comparators. Risk of delirium diagnosis was higher for all SMI subtypes, with a higher risk conferred by SMI in the under 65-year group, (aHR:7.65, 95% CI 5.45–10.7, ⩾65-year group: aHR:3.35, 95% CI 2.77–4.05). Compared to people without SMI, people with an SMI diagnosis overall had no difference in 30-day mortality following a hospitalisation involving delirium (OR:0.66, 95% CI 0.38–1.14).

We found an association between SMI and delirium diagnoses. People with SMI may be more vulnerable to delirium when in hospital than people without SMI. There are limitations to using electronic healthcare records and further prospective study is needed to confirm these findings.

Access to psychedelic drugs is liberalizing, yet responses are highly unpredictable. It is therefore imperative that we improve our ability to predict the nature of the acute psychedelic experience to improve safety and optimize potential therapeutic outcomes. This study sought to validate the ‘Imperial Psychedelic Predictor Scale’ (IPPS), a short, widely applicable, prospective measure intended to be predictive of salient dimensions of the psychedelic experience.

Using four independent datasets in which the IPPS was completed prospectively – two online surveys of ‘naturalistic’ use (N = 741, N = 836) and two controlled administration datasets (N = 30, N = 28) – we conducted factor analysis, regression, and correlation analyses to assess the construct, predictive, and convergent validity of the IPPS.

Our approach produced a 9-item scale with good internal consistency (Cronbach's α = 0.8) containing three factors: set, rapport, and intention. The IPPS was significantly predictive of ‘mystical’, ‘challenging’, and ‘emotional breakthrough’ experiences. In a controlled administration dataset (N = 28), multiple regression found set and rapport explaining 40% of variance in mystical experience, and simple regression found set explained 16% of variance in challenging experience. In another (N = 30), rapport was related to emotional breakthrough explaining 9% of variance.

Together, these data suggest that the IPPS is predictive of relevant acute features of the psychedelic experience in a broad range of contexts. We hope that this brief 9-item scale will be widely adopted for improved knowledge of psychedelic preparedness in controlled settings and beyond.

A significantly higher prevalence of neurological conditions has been found both before and after a diagnosis of schizophrenia, bipolar disorder and other psychotic illnesses compared with the general population.

We aimed to understand the cumulative prevalence of 16 neurological conditions in people with severe mental illness (SMI) from 5 years before to 5 years after their SMI diagnosis. We hypothesised that individual neurological conditions would have differential temporal relationships relative to SMI diagnosis.

In a longitudinal matched study, we identified a cohort of patients aged 18–100 years from Jan 1, 2000, and Dec 31, 2018, from the UK Clinical Practice Research Datalink (CPRD). Neurological conditions were classified using ICD–11 criteria into umbrella clusters of disease. Outcome of interest was a diagnosis of SMI. Each SMI patient was matched 1:4 to patients without SMI in the CPRD cohort, matching for sex, 5-year age band, primary care practice and year of practice registration. The cumulative prevalence of 16 neurological conditions was recorded cross-sectionally at 5, 3, 1 years prior to SMI diagnosis, at SMI diagnosis (index), and 1, 3 and 5 years after SMI diagnosis. Logistic regression modelling aided comparison of differential prevalence of neurological conditions, adjusting for sociodemographic variables, and with further adjustment for body mass index, smoking, alcohol and non-prescription drug use. Multiple imputation was applied in cases of missing data.

We identified 68,789 patients with SMI, matched to 274,827 controls. The median age was 40.9 years, 49.05% of the overall cohort were female (33,783 SMI patients, 134,740 controls), and the majority were of White ethnicity (35,228, 51.2% SMI patients, 125,518, 45.7% controls). The most prevalent neurological conditions across seven timepoints were cerebral palsy, cerebrovascular disease, dementia, epilepsy, multiple sclerosis, paralysis and Parkinson's disease. Conditions with the highest fully adjusted odds ratios (ORs) for SMI diagnosis were dementia 3 years after SMI diagnosis (5.32, 95% CI 4.95–5.71) and Parkinson's disease 5 years after SMI diagnosis (4.26, 95% CI 3.68–4.94).

All 16 neurological conditions have higher prevalence in the SMI cohort compared with controls, with different prevalence patterns observed over the 10-year study period. A consistently lower OR for schizophrenia compared with other SMI warrants further exploration, as neurological conditions risk being under-recorded.

A greater understanding of the temporal relationship between SMI and neurological conditions may help promote earlier diagnosis, increased screening and better holistic management of both conditions.

Heat exposure can negatively impact mental health. Evidence for the effect of temperature on mood disorders is inconsistent. Current studies exploring the link between temperature and mood disorders are limited by poor temporal and geographical resolution. We aimed to use ecological momentary assessment (EMA) to investigate the effect of real-time temperature on depressive and manic symptoms. We hypothesised higher temperatures would be associated with increased depressive and manic symptoms.

We used EMA data from the digital platform and smartphone app juli to investigate the effect of real-time mean and maximum ambient temperature on depressive and manic symptoms in adults with depression and bipolar disorder. Depressive and manic symptoms were assessed using the Patient Health Questionnaire-8 and the Altman Self Rating Mania score, respectively. Time- and location-specific temperature data were collected from participants’ smartphone geolocation on a 5-by-5 km resolution grid. We analysed data using negative binomial mixed-effects regression models, controlled for demographic and weather variables, and stratified by season.

We analysed data from 4,000 participants with depressive symptoms and 2,132 with manic symptoms, between July 2021 and March 2023. We found that each 1°C increase in mean daily temperature in the preceding two weeks was associated with a 0.2% reduction in depressive symptom scores (IRR 0.998, 95%CI 0.997–0.999). This association was most pronounced in the spring (IRR 0.995, 95%CI 0.992–0.999). For manic symptoms, we found that each 1°C increase in mean temperature in the preceding two weeks was associated with a 0.4% increase in manic symptom scores (IRR 1.004, 95%CI 1.001–1.007), with the strongest association observed in the autumn (IRR 1.011, 95%CI 1.002–1.020). Associations between maximum temperature and depressive and manic symptoms followed a similar pattern.

We found evidence that higher temperatures were associated with decreased depressive symptoms and increased manic symptoms, indicating a complex relationship between temperature and mood disorder symptoms. With globally rising temperatures due to climate change, there is a need to understand the impact of heat on mental health symptoms to provide targeted support. This study demonstrates the potential for using novel data sources and EMA methods to inform our understanding of the link between climate and mental health, although there is a need for improved data collection to realise the potential of these methods. Clinically, our findings highlight opportunities for risk stratification and targeted interventions based on local temperature patterns.

Most evidence on suicidal thoughts, plans and attempts comes from Western countries; prevalence rates may differ in other parts of the world.

This study determined the prevalence of suicidal thoughts, plans and attempts in high school students in three different regional settings in Kenya.

This was a cross-sectional study of 2652 high school students. We asked structured questions to determine the prevalence of various types of suicidality, the methods planned or effected, and participants’ gender, age and form (grade level). We provided descriptive statistics, testing significant differences by chi-squared and Fisher's exact tests, and used logistic regression to identify relationships among different variables and their associations with suicidality.

The prevalence rates of suicidal thoughts, plans and attempts were 26.8, 14.9 and 15.7%, respectively. These rates are higher than those reported for Western countries. Some 6.7% of suicide attempts were not associated with plans. The most common method used in suicide attempts was drinking chemicals/poison (18.8%). Rates of suicidal thoughts and plans were higher for older students and students in urban rather than rural locations, and attempts were associated with female gender and higher grade level – especially the final year of high school, when exam performance affects future education and career prospects.

Suicidal thoughts, plans and attempts are prevalent in Kenyan high school students. There is a need for future studies to determine the different starting points to suicidal attempts, particularly for the significant number whose attempts are not preceded by thoughts and plans.

Depression, anxiety and insomnia often co-occur. However, there is a lack of research regarding how they cluster and how this is related to medication used to treat them.

To describe the frequencies and associations between depression, anxiety and insomnia, and treatment for these conditions in primary care.

A retrospective cohort study using UK electronic primary care records. We included individuals aged between 18 and 99 years old with one or more records suggesting they had a diagnosis, symptom or drug treatment for anxiety, depression or insomnia between 2015 and 2017. We report the conditional probabilities of having different combinations of diagnoses, symptoms and treatments recorded.

There were 1 325 960 records indicative of depression, anxiety or insomnia, for 739 834 individuals. Depression was the most common condition (n = 106 117 records), and SSRIs were the most commonly prescribed medication (n = 347 751 records). Overall, individuals with a record of anxiety were most likely to have co-occurring symptoms and diagnoses of other mental health conditions. For example, of the individuals with a record of generalised anxiety disorder (GAD), 24% also had a diagnosis of depression. In contrast, only 0.6% of those who had a diagnosis of depression had a diagnosis or symptom of GAD. Prescribing of more than one psychotropic medication within the same year was common. For example, of those who were prescribed an SNRI (serotonin-norepinephrine reuptake inhibitor), 40% were also prescribed an SSRI (selective serotonin reuptake inhibitor).

The conditional probabilities of co-occurring anxiety, depression and insomnia symptoms, diagnoses and treatments are high.

Depression is associated with higher rates of premature mortality in people with physical comorbidities, such as type 2 diabetes. Conceptually, the successful treatment of depression in people with type 2 diabetes could prevent premature mortality.

To investigate the association between antidepressant prescribing and the rates of all-cause and cause-specific (endocrine, cardiovascular, respiratory, cancer, unnatural) mortality in individuals with comorbid depression and type 2 diabetes.

Using UK primary care records between years 2000 and 2018, we completed a nested case–control study in a cohort of people with comorbid depression and type 2 diabetes who were starting oral antidiabetic treatment for the first time. We used incident density sampling to identify cases who died and matched controls who remained alive after the same number of days observation. We estimated incidence rate ratios for the association between antidepressant prescribing and mortality, adjusting for demographic characteristics, comorbidities, medication use and health behaviours.

We included 5222 cases with a recorded date of death, and 18 675 controls, observed for a median of 7 years. Increased rates of all-cause mortality were associated with any antidepressant prescribing during the observation period (incidence rate ratio 2.77, 95% CI 2.48–3.10). These results were consistent across all causes of mortality that we investigated.

Antidepressant prescribing was highly associated with higher rates of mortality. However, we suspect that this is not a direct causal effect, but that antidepressant treatment is a marker of more severe and unsuccessfully treated depression.

Population-wide restrictions during the COVID-19 pandemic may create barriers to mental health diagnosis. This study aims to examine changes in the number of incident cases and the incidence rates of mental health diagnoses during the COVID-19 pandemic.

By using electronic health records from France, Germany, Italy, South Korea and the UK and claims data from the US, this study conducted interrupted time-series analyses to compare the monthly incident cases and the incidence of depressive disorders, anxiety disorders, alcohol misuse or dependence, substance misuse or dependence, bipolar disorders, personality disorders and psychoses diagnoses before (January 2017 to February 2020) and after (April 2020 to the latest available date of each database [up to November 2021]) the introduction of COVID-related restrictions.

A total of 629,712,954 individuals were enrolled across nine databases. Following the introduction of restrictions, an immediate decline was observed in the number of incident cases of all mental health diagnoses in the US (rate ratios (RRs) ranged from 0.005 to 0.677) and in the incidence of all conditions in France, Germany, Italy and the US (RRs ranged from 0.002 to 0.422). In the UK, significant reductions were only observed in common mental illnesses. The number of incident cases and the incidence began to return to or exceed pre-pandemic levels in most countries from mid-2020 through 2021.

Healthcare providers should be prepared to deliver service adaptations to mitigate burdens directly or indirectly caused by delays in the diagnosis and treatment of mental health conditions.

In England, a range of mental health crisis care models and approaches to organising crisis care systems have been implemented, but characteristics associated with their effectiveness are poorly understood.

To (a) develop a typology of catchment area mental health crisis care systems and (b) investigate how crisis care service models and system characteristics relate to psychiatric hospital admissions and detentions.

Crisis systems data were obtained from a 2019 English national survey. Latent class analyses were conducted to identify discernible typologies, and mixed-effects negative binomial regression models were fitted to explore associations between crisis care models and admissions and detention rates, obtained from nationally reported data.

No clear typology of catchment area crisis care systems emerged. Regression models suggested that provision of a crisis telephone service within the local crisis system was associated with a 11.6% lower admissions rate and 15.3% lower detention rate. Provision of a crisis cafe was associated with a 7.8% lower admission rates. The provision of a crisis assessment team separate from the crisis resolution and home treatment service was associated with a 12.8% higher admission rate.

The configuration of crisis care systems varies considerably in England, but we could not derive a typology that convincingly categorised crisis care systems. Our results suggest that a crisis phone line and a crisis cafe may be associated with lower admission rates. However, our findings suggest crisis assessment teams, separate from home treatment teams, may not be associated with reductions in admission and detentions.

The co-occurrence of stroke and psychosis is a serious neuropsychiatric condition but little is known about the course of this comorbidity. We aimed to estimate longitudinal associations between stroke and psychosis over 10 years.

A 10-year population-based study using data from the English Longitudinal Study of Ageing. A structured health assessment recorded (i) first-occurrence stroke and (ii) psychosis, at each wave. Each were considered exposures and outcomes in separate analyses. Logistic and Cox proportional hazards regression and Kaplan–Meier methods were used. Models were adjusted for demographic and health behaviour covariates, with missing covariates imputed using random forest multiple imputation.

Of 19 808 participants, 24 reported both stroke and psychosis (median Wave 1 age 63, 71% female, 50% lowest quintile of net financial wealth) at any point during follow-up. By 10 years, the probability of an incident first stroke in participants with psychosis was 21.4% [95% confidence interval (CI) 12.1–29.6] compared to 8.3% (95% CI 7.8–8.8) in those without psychosis (absolute difference: 13.1%; 95% CI 20.8–4.3, log rank p < 0.001; fully-adjusted hazard ratio (HR): 3.57; 95% CI 2.18–5.84). The probability of reporting incident psychosis in participants with stroke was 2.3% (95% CI 1.4–3.2) compared to 0.9% (95% CI 0.7–1.1) in those without (absolute difference: 1.4%; 95% CI 0.7–2.1, log rank p < 0.001; fully-adjusted HR: 4.98; 95% CI 2.55–9.72).

Stroke is an independent predictor of psychosis (and vice versa), after adjustment for potential confounders.

To minimise infection during COVID-19, the clozapine haematological monitoring interval was extended from 4-weekly to 12-weekly intervals in South London and Maudsley NHS Foundation Trust.

To investigate the impact of this temporary policy change on clinical and safety outcomes.

All patients who received clozapine treatment with extended (12-weekly) monitoring in a large London National Health Service trust were included in a 1-year mirror-image study. A comparison group was selected with standard monitoring. The proportion of participants with mild to severe neutropenia and the proportion of participants attending the emergency department for clozapine-induced severe neutropenia treatment during the follow-up period were compared. Psychiatric hospital admission rates, clozapine dose and concomitant psychotropic medication in the 1 year before and the 1 year after extended monitoring were compared. All-cause clozapine discontinuation at 1-year follow-up was examined.

Of 569 participants, 459 received clozapine with extended monitoring and 110 controls continued as normal. The total person-years were 458 in the intervention group and 109 in the control group, with a median follow-up time of 1 year in both groups. During follow-up, two participants (0.4%) recorded mild to moderate neutropenia in the intervention group and one (0.9%) in the control group. There was no difference in the incidence of haematological events between the two groups (IRR = 0.48, 95% CI 0.02–28.15, P = 0.29). All neutropenia cases in the intervention group were mild, co-occurring during COVID-19 infection. The median number of admissions per patient during the pre-mirror period remained unchanged (0, IQR = 0) during the post-mirror period. There was one death in the control group, secondary to COVID-19 infection.

There was no evidence that the incidence of severe neutropenia was increased in those receiving extended monitoring.

Individuals with physical comorbidities and polypharmacy may be at higher risk of depression relapse, however, they are not included in the ‘high risk of relapse’ group for whom longer antidepressant treatment durations are recommended.

In individuals with comorbid depression and type 2 diabetes (T2DM), we aimed to investigate the association and interaction between depression relapse and (a) polypharmacy, (b) previous duration of antidepressant treatment.

This was a cohort study using primary care data from the UK Clinical Practice Research Datalink (CPRD) from years 2000 to 2018. We used Cox regression models with penalised B-splines to describe the association between restarting antidepressants and our two exposures.

We identified 48 001 individuals with comorbid depression and T2DM, who started and discontinued antidepressant treatment during follow-up. Within 1 year of antidepressant discontinuation, 35% of participants restarted treatment indicating depression relapse. As polypharmacy increased, the rate of restarting antidepressants increased until a maximum of 18 concurrent medications, where individuals were more than twice as likely to restart antidepressants (hazard ratio (HR) = 2.15, 95% CI 1.32–3.51). As the duration of previous antidepressant treatment increased, the rate of restarting antidepressants increased – individuals with a previous duration of ≥25 months were more than twice as likely to restart antidepressants than those who previously discontinued in <7 months (HR = 2.36, 95% CI 2.25–2.48). We found no interaction between polypharmacy and previous antidepressant duration.

Polypharmacy and longer durations of previous antidepressant treatment may be associated with depression relapse following the discontinuation of antidepressant treatment.

Alcohol use is a risk factor for suicidal behaviour, yet the nature of the relationship is unclear. Most research on the topic is conducted in clinical populations, with few studies exploring this association across the general population.

We investigated the association between specific domains of alcohol use and suicide attempt, suicidal thoughts and non-suicidal self-harm in a general population sample.

A total of 14 949 adults who completed the 2007 or 2014 Adult Psychiatric Morbidity Survey were included. We measured alcohol use with the Alcohol Use Disorders Identification Test (AUDIT). Domains of alcohol use relating to risk categories, weekly consumption, binge drinking, dependence symptoms, harmful effects and concern from others were derived from relevant AUDIT items. Self-reported past year suicide attempt, suicidal thoughts and non-suicidal self-harm were measured with the Clinical Interview Schedule, Revised.

We found a linear association between total AUDIT score and outcomes. Three of six specific domains of alcohol use (dependence symptoms, harmful effects of drinking and binge drinking) were associated with increased odds of all three outcomes. There was no association of outcomes with the other domains of alcohol use.

We found evidence of a linear association between total AUDIT score and suicide attempt, suicidal thoughts and non-suicidal self-harm in a representative English general population sample. Our analyses suggest that where alcohol use significantly disrupts day-to-day functioning, this may underpin the relationship between alcohol use and suicide-related outcomes to a greater extent than higher alcohol consumption. Longitudinal research is needed to further understand these relationships.

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.

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.

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).

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.

Patients with bipolar disorder (BPD) are prone to engage in risk-taking behaviours and self-harm, contributing to higher risk of traumatic injuries requiring medical attention at the emergency room (ER).We hypothesize that pharmacological treatment of BPD could reduce the risk of traumatic injuries by alleviating symptoms but evidence remains unclear. This study aimed to examine the association between pharmacological treatment and the risk of ER admissions due to traumatic injuries.

Individuals with BPD who received mood stabilizers and/or antipsychotics were identified using a population-based electronic healthcare records database in Hong Kong (2001–2019). A self-controlled case series design was applied to control for time-invariant confounders.

A total of 5040 out of 14 021 adults with BPD who received pharmacological treatment and had incident ER admissions due to traumatic injuries from 2001 to 2019 were included. An increased risk of traumatic injuries was found 30 days before treatment [incidence rate ratio (IRR) 4.44 (3.71–5.31), p < 0.0001]. After treatment initiation, the risk remained increased with a smaller magnitude, before returning to baseline [IRR 0.97 (0.88–1.06), p = 0.50] during maintenance treatment. The direct comparison of the risk during treatment to that before and after treatment showed a significant decrease. After treatment cessation, the risk was increased [IRR 1.34 (1.09–1.66), p = 0.006].

This study supports the hypothesis that pharmacological treatment of BPD was associated with a lower risk of ER admissions due to traumatic injuries but an increased risk after treatment cessation. Close monitoring of symptoms relapse is recommended to clinicians and patients if treatment cessation is warranted.