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NHS Psychiatric beds comprise mental illness and intellectual disability beds. Penrose hypothesised that the number of psychiatric in-patients was inversely related to prison population size.
To ascertain whether the Penrose hypothesis held true in England between 1960 and 2018–2019.
A time-series analysis explored the association between total prison population and NHS psychiatric beds; this was also tested for the male and female prison populations, using non-psychiatric beds as a comparator. Associations were explored with time lags of up to 20 years. Linear regression was conducted to estimate the size of the effect of bed closures.
NHS psychiatric beds decreased 93% and the prison population increased 208%. A strong (r =−0.96) and highly significant negative correlation between these changes was found. Annual reduction in psychiatric bed numbers was associated with an increase in prison population, strongest at a lag of 10 years. The closure of mental illness and intellectual disability beds was associated with increases in female prisoners 10 years later. The only significant explanatory variable for the increase in male prison population was intellectual disability bed reduction.
The Penrose hypothesis held true between 1960 and 2018–2019 in England: psychiatric bed closures were associated with increases in prison population up to 10 years later. For every 100 psychiatric beds closed, there were 36 more prisoners 10 years later: 3 more female prisoners and 33 more male prisoners. Our results suggest that the dramatic increase in the female prison population may relate to the closure of NHS beds.
To assess the feasibility and utility of introducing the following changes on to in-patient units:
Structural and cultural adaptation to create a sleep friendly ward environment
A “Protected Sleep Time” between midnight and 6am
Routine screening for sleep disorders, including obstructive sleep apnoea and restless leg syndrome
Insomnia and other sleep disturbances are cause, correlate and consequence of psychiatric disorders. Routine hourly night time observations, ward noise, bright lights at night time, sleep disorders, insufficient exercise, insufficient day light exposure, too much caffeine and inappropriate psychotropic use are all causes of disturbed sleep (Horne 2018).
Seven wards participated in a pilot (SleepWell). These consisted of one male and two female Acute Wards (General Adult), a High Dependency Unit, a Neurorehabilitation ward, an in-patient dementia service and one rehabilitation ward. These wards were supported via an existing trust management structure and the pilot was specifically supported by two trust managers (RW and RB) and by a clinical director (PK). The expectation was that each ward would identify a sleep champion from existing staff to facilitate the changes. A “product” was developed which identified core sleep management features but, in addition, wards were not confined to these. The existing policy that all inpatients should be checked each hour over night was suspended for the pilot wards and the patients had protected sleep time (PST) if the MDT agreed that it was clinically appropriate.
Quantitative and qualitative techniques were used to identify facilitators of change, impact on sleep and, outcome.
Protected sleep was viewed positively by all staff and approximately 50% of patients on the pilot wards were able to have PST at some point in their admission. Routine sleep disorder assessments were harder to implement and 33% of patients were screened. There were no deaths or significant events on patients due to PST. Hypnotic use on the pilot wards reduced. It is anticipated that PST where it is safe will be rolled out across all adult and old age wards in the trust.
With support, it has been feasible to change many aspects of sleep management across a breadth of inpatient units in a large NHS trust.
Black, Asian and minority ethnicity groups may experience better health outcomes when living in areas of high own-group ethnic density – the so-called ‘ethnic density’ hypothesis. We tested this hypothesis for the treatment outcome of compulsory admission.
Data from the 2010–2011 Mental Health Minimum Dataset (N = 1 053 617) was linked to the 2011 Census and 2010 Index of Multiple Deprivation. Own-group ethnic density was calculated by dividing the number of residents per ethnic group for each lower layer super output area (LSOA) in the Census by the LSOA total population. Multilevel modelling estimated the effect of own-group ethnic density on the risk of compulsory admission by ethnic group (White British, White other, Black, Asian and mixed), accounting for patient characteristics (age and gender), area-level deprivation and population density.
Asian and White British patients experienced a reduced risk of compulsory admission when living in the areas of high own-group ethnic density [odds ratios (OR) 0.97, 95% credible interval (CI) 0.95–0.99 and 0.94, 95% CI 0.93–0.95, respectively], whereas White minority patients were at increased risk when living in neighbourhoods of higher own-group ethnic concentration (OR 1.18, 95% CI 1.11–1.26). Higher levels of own-group ethnic density were associated with an increased risk of compulsory admission for mixed-ethnicity patients, but only when deprivation and population density were excluded from the model. Neighbourhood-level concentration of own-group ethnicity for Black patients did not influence the risk of compulsory admission.
We found only minimal support for the ethnic density hypothesis for the treatment outcome of compulsory admission to under the Mental Health Act.
The steep rise in the rate of psychiatric hospital detentions in England is poorly understood.
To identify explanations for the rise in detentions in England since 1983; to test their plausibility and support from evidence; to develop an explanatory model for the rise in detentions.
Hypotheses to explain the rise in detentions were identified from previous literature and stakeholder consultation. We explored associations between national indicators for potential explanatory variables and detention rates in an ecological study. Relevant research was scoped and the plausibility of each hypothesis was rated. Finally, a logic model was developed to illustrate likely contributory factors and pathways to the increase in detentions.
Seventeen hypotheses related to social, service, legal and data-quality factors. Hypotheses supported by available evidence were: changes in legal approaches to patients without decision-making capacity but not actively objecting to admission; demographic changes; increasing psychiatric morbidity. Reductions in the availability or quality of community mental health services and changes in police practice may have contributed to the rise in detentions. Hypothesised factors not supported by evidence were: changes in community crisis care, compulsory community treatment and prescribing practice. Evidence was ambiguous or lacking for other explanations, including the impact of austerity measures and reductions in National Health Service in-patient bed numbers.
Better data are needed about the characteristics and service contexts of those detained. Our logic model highlights likely contributory factors to the rise in detentions in England, priorities for future research and potential policy targets for reducing detentions.
Sleep disturbance is common in psychiatry wards despite poor sleep worsening mental health. Contributory factors include the ward environment, frequent nightly checks on patients and sleep disorders including sleep apnoea. We evaluated the safety and feasibility of a package of measures to improve sleep across a mental health trust, including removing hourly checks when safe, sleep disorder screening and improving the ward environment.
During the pilot there were no serious adverse events; 50% of in-patients were able to have protected overnight sleep. Hypnotic issuing decreased, and feedback from patients and staff was positive. It was possible to offer cognitive–behavioural therapy for insomnia to selected patients.
Many psychiatry wards perform standardised, overnight checks, which are one cause of sleep disruption. A protected sleep period was safe and well-tolerated alongside education about sleep disturbance and mental health. Future research should evaluate personalised care rather than blanket observation policies.
The Mental Health Act in England and Wales allows for two types of detention in hospital: civil and forensic detentions. An association between the closure of mental illness beds and a rise in civil detentions has been reported.
To examine changes in the rate of court orders and transfer from prison to hospital for treatment, and explore associations with civil involuntary detentions, psychiatric bed numbers and the prison population.
Secondary analysis of routinely collected data with lagged time series analysis. We focused on two main types of forensic detentions in National Health Service (NHS) hospitals and private units: prison transfers and court treatment orders in England from 1984 to 2016. NHS bed numbers only were available.
There was an association between the number of psychiatric beds and the number of prison transfers. This was strongest at a time lag of 2 years with the change in psychiatric beds occurring first. There was an association between the rate of civil detentions and the rate of court orders. This was strongest at a time lag of 3 years. Linear regression indicated that 135 fewer psychiatric beds were associated with one additional transfer from prison to hospital; and as the rate of civil detentions increased by 72, the rate of court treatment orders fell by one.
The closure of psychiatric beds was associated with an increase in transfers from prison to hospital for treatment. The increase in civil detentions was associated with a reduction in the rate of courts detaining to hospital individuals who had offended.
Concerns have been raised about the increase in the use of involuntary detentions under the Mental Health Act in England over a number of years, and whether this merits consideration of legislative change.
To investigate changes in the rate of detentions under Part II (civil) and Part III (forensic) sections of the Mental Health Act in England between 1984 and 2016.
Retrospective analysis of data on involuntary detentions from the National Archives and NHS Digital. Rates per 100 000 population were calculated with percentage changes. The odds of being formally admitted to a National Health Service hospital compared with a private hospital were calculated for each year.
Rates of detention have at least trebled since the 1980s and doubled since the 1990s. This has been because of a rise in Part II (civil) sections. Although the overall rate of detentions under Part III (forensic) sections did not rise, transfers from prison increased and detentions by the courts reduced. The odds of being detained in a private hospital increased fivefold.
The move to community-based mental health services in England has paradoxically led to an increase in the number of people being detained in hospital each year, and in particular an inexorable rise in involuntary admissions. This is likely to be partly because of improved case finding with an increased focus on treatment and risk management, and partly because of changes in legislation. An increasing proportion of this government-funded care is being provided by private hospitals.
To compare rates of admission for different types of severe mental illness between ethnic groups, and to test the hypothesis that larger and more clustered ethnic groups will have lower admission rates. This was a descriptive study of routinely collected data from the National Health Service in England.
There was an eightfold difference in admission rates between ethnic groups for schizophreniform and mania admissions, and a fivefold variation in depression admissions. On average, Black and minority ethnic (BME) groups had higher rates of admission for schizophreniform and mania admissions but not for depression. This increased rate was greatest in the teenage years and early adulthood. Larger ethnic group size was associated with lower admission rates. However, greater clustering was associated with higher admission rates.
Our findings support the hypothesis that larger ethnic groups have lower rates of admission. This was a between-group comparison rather than within each group. Our findings do not support the hypothesis that more clustered groups have lower rates of admission. In fact, they suggest the opposite: groups with low clustering had lower admission rates. The BME population in the UK is increasing in size and becoming less clustered. Our results suggest that both of these factors should ameliorate the overrepresentation of BME groups among psychiatric in-patients. However, this overrepresentation continues, and our results suggest a possible explanation, namely, changes in the delivery of mental health services, particularly the marked reduction in admissions for depression.
Community treatment orders (CTOs) were introduced in England in 2008.
To measure the rate of CTO use in England during the first 5 years following introduction.
The number of involuntary detentions and CTOs in National Health Service (NHS) hospital trusts was collected between 2009 and 2014. Rates of CTO use and the ratio of CTOs to detentions on admission were calculated, and how these varied between trusts.
The number of new CTOs each year ranged between 3834 and 4647. The number subject to a CTO per 100 000 population increased from 6.4 in 2009/10 to 10.0 in 2013/14. There was variation between NHS trusts in the use of CTOs when compared with the number of involuntary detentions
The number of patients on CTOs increased year on year. Those on forensic sections were more likely to be discharged on a CTO than those on civil sections. There was considerable variation in the pattern of use between hospitals.
Individual variables and area-level variables have been identified as explaining much of the variance in rates of compulsory in-patient treatment.
To describe rates of voluntary and compulsory psychiatric in-patient treatment in rural and urban settings in England, and to explore the associations with age, ethnicity and deprivation.
Secondary analysis of 2010/11 data from the Mental Health Minimum Dataset.
Areas with higher levels of deprivation had increased rates of in-patient treatment. Areas with high proportions of adults aged 20–39 years had the highest rates of compulsory in-patient treatment as well as the lowest rates of voluntary in-patient treatment. Urban settings had higher rates of compulsory in-patient treatment and ethnic density was associated with compulsory treatment in these areas. After adjusting for age, deprivation and urban/rural setting, the association between ethnicity and compulsory treatment was not statistically significant.
Age structure of the adult population and ethnic density along with higher levels of deprivation can account for the markedly higher rates of compulsory in-patient treatment in urban areas.
This paper investigates the relationship between cluster (Mental Health Clustering Tool, MHCT) and diagnosis in an in-patient population. We analysed the diagnostic make-up of each cluster and the clinical utility of the diagnostic advice in the Department of Health's Mental Health Clustering Booklet. In-patients discharged from working-age adult and older people's services of a National Health Service trust over 1 year were included. Cluster on admission was compared with primary diagnosis on discharge.
Organic, schizophreniform, anxiety disorder and personality disorders aligned to one superclass cluster. Alcohol and substance misuse, and mood disorders distributed evenly across psychosis and non-psychosis superclass clusters. Two-thirds of diagnoses fell within the MHCT ‘likely’ group and a tenth into the ‘unlikely’ group.
Cluster and diagnosis are best viewed as complimentary systems to describe an individual's needs. Improvements are suggested to the MHCT diagnostic advice in in-patient settings. Substance misuse and affective disorders have a more complex distribution between superclass clusters than all other broad diagnostic groups.
To detail changes in the use of place of safety orders in England, including the outcome of these detentions, using publicly available data.
There was a sixfold increase in the rate of the Mental Health Act Section 136 detentions to places of safety in hospitals between 1984 and 2011. The use of Section 135 and the rate of subsequent detention under Section 2 or 3 also increased, but the proportion of people detained fell as the absolute rate of detention increased. There was a wide variation between regions in the use of hospitals or police stations as places of safety. The change in the annual rate of detention under Section 136 was associated with the annual change in the population of England.
The increase in detentions to places of safety in hospitals may in part reflect their move from police cells. It may also reflect a real increase in overall rate of detention and possibly a change in the threshold for the use of Section 136 detentions.
To investigate changes to admissions, compulsory detentions, diagnosis, length of stay and suicides following introduction of crisis resolution home treatment and assertive outreach teams.
There was a 45% reduction in admissions with an increase in the median length of stay from 15.5 to 25 days. Bed occupancy fell by 22%. The number of suicides remained constant. Detentions under sections 2 and 3 of the Mental Health Act 1983 increased whereas those under sections 5(2) and 5(4) declined.
The introduction of crisis and assertive outreach teams was followed by a reduction in admissions, particularly short admissions. The impact differed according to gender (reduction in female bed occupancy). This and the increased length of stay need to be considered when determining the number of acute psychiatric beds needed.
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