Acute inpatient psychiatry in England: an old problem and a new priority

With the development of community care, the number of National Health Service psychiatric beds in England has been reduced to between one-fifth and one-quarter of those provided in the mid-1950s. Psychiatric bed numbers are close to the irreducible minimum if they have not already reached it. The problems facing today's acute psychiatric admission wards include: poor design, maintenance and ambience; a lack of therapeutic and leisure activities for patients leading to inactivity and boredom; frequent incidents of aggression and low-level violence and problems with staffing. It is suggested that there are a number of underlying causes: First, there has been failure to plan inpatient services, or to define their role, as attention has focused on new developments in community care. Second, the reduction in bed numbers has led to a change in the casemix of inpatients with a concentration on admission wards of a more challenging group of patients. Third, admission ward environments are permeable to the adverse effects of local street life, including drug taking. After years of neglect, acute inpatient psychiatric services in England are now high on the UK Government agenda. The paper lists a number of national initiatives designed to improve their quality and safety. A recent review of qualitative research suggests that acute psychiatric wards in other countries face similar problems to those reported in England. It is suggested that there might be a need for joint action which might take the form either of international research about acute inpatient care or the development of international standards and a common quality improvement system.

Measures of crowding in the emergency department: a systematic review

OBJECTIVES

Despite consensus regarding the conceptual foundation of crowding, and increasing research on factors and outcomes associated with crowding, there is no criterion standard measure of crowding. The objective was to conduct a systematic review of crowding measures and compare them in conceptual foundation and validity.

METHODS

This was a systematic, comprehensive review of four medical and health care citation databases to identify studies related to crowding in the emergency department (ED). Publications that "describe the theory, development, implementation, evaluation, or any other aspect of a 'crowding measurement/definition' instrument (qualitative or quantitative)" were included. A "measurement/definition" instrument is anything that assigns a value to the phenomenon of crowding in the ED. Data collected from papers meeting inclusion criteria were: study design, objective, crowding measure, and evidence of validity. All measures were categorized into five measure types (clinician opinion, input factors, throughput factors, output factors, and multidimensional scales). All measures were then indexed to six validation criteria (clinician opinion, ambulance diversion, left without being seen (LWBS), times to care, forecasting or predictions of future crowding, and other).

RESULTS

There were 2,660 papers identified by databases; 46 of these papers met inclusion criteria, were original research studies, and were abstracted by reviewers. A total of 71 unique crowding measures were identified. The least commonly used type of crowding measure was clinician opinion, and the most commonly used were numerical counts (number or percentage) of patients and process times associated with patient care. Many measures had moderate to good correlation with validation criteria.

CONCLUSIONS

Time intervals and patient counts are emerging as the most promising tools for measuring flow and nonflow (i.e., crowding), respectively. Standardized definitions of time intervals (flow) and numerical counts (nonflow) will assist with validation of these metrics across multiple sites and clarify which options emerge as the metrics of choice in this "crowded" field of measures.

Scheduled admissions and high occupancy at a children's hospital

BACKGROUND

High hospital occupancy is a challenge for quality of care and access, while low levels of occupancy may be inefficient in terms of resource utilization. Variability from scheduling decisions may affect occupancy and be amenable to alteration.

OBJECTIVE

Describe variability in admission, discharge, and occupancy patterns at a large children's hospital and assess the relationship between scheduled admissions and occupancy.

DESIGN

Retrospective administrative data analysis.

SETTING

One urban, tertiary-care children's hospital.

PATIENTS

A total of 22,310 consecutive patients admitted from July 1, 2007 to June 30, 2008.

MEASUREMENTS

Admission-discharge-transfer (ADT) data for 1 fiscal year were abstracted for analysis of admission and occupancy patterns.

RESULTS

Among 22,310 admissions, 78% were coded as emergent and 22% as scheduled. Variation in admission volume by day of week was high for scheduled admissions (coefficient of variation [CV] 65.3%), while it was more consistent for emergent admissions (CV 12.0%). For patients with length of stay (LOS) ≤ 7 days (84%), Mondays and Tuesdays generated 45.2% of scheduled patient hours. Wednesdays and Thursdays had the highest frequency of high occupancy.

CONCLUSIONS

Scheduled admissions contribute significantly to variability in occupancy and risk of mid-week crowding. Predictable patterns of admissions lead to high occupancy on some days and unused capacity on others, which can be addressed with proactive management of admissions (eg, greater use of unused capacity on weekends and in summer). Hospitals interested in optimizing patient flow should assess their admission and occupancy patterns. Further studies should link variation in occupancy to outcomes including quality of care, educational activities, and staff satisfaction.

Understanding the current state of patient flow in a hospital

The challenge of generating bed availability is constant in most NHS acute trusts. Building on previous work applying queue theory, this paper now takes operational data from one NHS trust, collected over a period of more than a year, to provide an evidence base and to establish the practical challenges associated with demand variation and managing length of stay. The problem is split into three separate parts. Daily bed shortages are mostly influenced by the timing of arrival and discharge of patients with a short length of stay. Patients who stay for longer than one to two days contribute most significantly to the observed weekly bed availability problem. The problems associated with bed shortages around Christmas time and into the New Year are not simply issues of increased demand. A reduction in discharge capacity is a major contributory factor that results in unnecessary increases in length of stay.

The Hospital Compare mortality model and the volume-outcome relationship

OBJECTIVE

We ask whether Medicare's Hospital Compare random effects model correctly assesses acute myocardial infarction (AMI) hospital mortality rates when there is a volume-outcome relationship.

DATA SOURCES/STUDY SETTING

Medicare claims on 208,157 AMI patients admitted in 3,629 acute care hospitals throughout the United States.

STUDY DESIGN

We compared average-adjusted mortality using logistic regression with average adjusted mortality based on the Hospital Compare random effects model. We then fit random effects models with the same patient variables as in Medicare's Hospital Compare mortality model but also included terms for hospital Medicare AMI volume and another model that additionally included other hospital characteristics.

PRINCIPAL FINDINGS

Hospital Compare's average adjusted mortality significantly underestimates average observed death rates in small volume hospitals. Placing hospital volume in the Hospital Compare model significantly improved predictions.

CONCLUSIONS

The Hospital Compare random effects model underestimates the typically poorer performance of low-volume hospitals. Placing hospital volume in the Hospital Compare model, and possibly other important hospital characteristics, appears indicated when using a random effects model to predict outcomes. Care must be taken to insure the proper method of reporting such models, especially if hospital characteristics are included in the random effects model.

Children's hospitals do not acutely respond to high occupancy

OBJECTIVE

High hospital occupancy may lead to overcrowding in emergency departments and inpatient units, having an adverse impact on patient care. It is not known how children's hospitals acutely respond to high occupancy. The objective of this study was to describe the frequency, direction, and magnitude of children's hospitals' acute responses to high occupancy.

METHODS

Patients who were discharged from 39 children's hospitals that participated in the Pediatric Health Information System database during 2006 were eligible. Midnight census data were used to construct occupancy levels. Acute response to high occupancy was measured by 8 variables, including changes in hospital admissions (4 measures), transfers (2 measures), and length of stay (2 measures).

RESULTS

Hospitals were frequently at high occupancy, with 28% of midnights at 85% to 94% occupancy and 42% of midnights at > or =95% occupancy. Whereas half of children's hospitals used occupancy-mitigating responses, there was variability in responses and magnitudes were small. When occupancy was >95%, no more than 8% of hospitals took steps to reduce admissions, 13% increased transfers out, and up to 58% reduced standardized length of stay. Two-day lag response was more common but remained of too small a magnitude to make a difference in hospital crowding. Additional modeling techniques also revealed little response.

CONCLUSIONS

We found a low rate of acute response to high occupancy. When there was a response, the magnitude was small.

Critical care medicine in the United States 2000-2005: an analysis of bed numbers, occupancy rates, payer mix, and costs

OBJECTIVES

To analyze the evolving role, patterns of use, and costs of critical care medicine in the United States from 2000 to 2005.

DESIGN

Retrospective study of data from the Hospital Cost Report Information System (Centers for Medicare and Medicaid Services, Baltimore, Maryland).

SETTING

Nonfederal, acute care hospitals with critical care medicine beds in the United States.

SUBJECTS

None.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

We analyzed hospital and critical care medicine beds, bed types, days, occupancy rates, payer mix (Medicare and Medicaid), and costs. Critical care medicine costs were compared with national cost indexes. Between 2000 and 2005, the total number of U.S. hospitals with critical care medicine beds decreased by 12.2% (from 3,586 to 3,150). Although the number of hospital beds decreased by 4.2% (from 655,785 to 628,409), both hospital days and occupancy rates increased by 5.1% (from 145.1 to 152.5 million) and 13.7% (from 59% to 67%), respectively. Critical care medicine beds increased by 6.5% (from 88,252 to 93,955), days by 10.6% (from 21.0 to 23.2 million), and occupancy rates by 4.5% (from 65% to 68%). The majority (90%) of critical care medicine beds were classified as intensive care, premature/neonatal, and coronary care unit beds. The percentage of critical care medicine days used by Medicare decreased by 3.8% (from 37.9% to 36.5%) compared with an increase of 15.5% (from 14.5% to 16.8%) by Medicaid. From 2000 to 2005, critical care medicine costs per day increased by 30.4% (from $2698 to $3518). Although annual critical care medicine costs increased by 44.2% (from $56.6 to $81.7 billion), the proportion of hospital costs and national health expenditures allocated to critical care medicine decreased by 1.6% and 1.8%, respectively. However, the proportion of the gross domestic product used by critical care medicine increased by 13.7%. In 2005, critical care medicine costs represented 13.4% of hospital costs, 4.1% of national health expenditures, and 0.66% of the gross domestic product.

CONCLUSIONS

Critical care medicine continues to grow in a shrinking U.S. hospital system. The critical care medicine payer mix is evolving, with Medicaid increasing in its percentage of critical care medicine use. Critical care medicine is more cost controlled than other healthcare indexes, but is still using an increasing percentage of the gross domestic product. Our updated and comprehensive critical care medicine use and cost analysis provides a contemporary benchmark for the strategic planning of critical care medicine services within the U.S. healthcare system.

Pattern of medical admissions at the Federal Medical Centre, Asaba-a two year review

OBJECTIVE

A two-year retrospective evaluation of the pattern of medical admissions at the Federal Medical Centre (FMC), Asaba, Delta State, Nigeria.

METHODOLOGY

Case notes of all admissions and deaths in the medical wards between November 2005 and October 2007 were retrieved and reviewed. The mean, standard deviation and percentages of relevant data were derived and presented in simple descriptive statistics.

RESULTS

One thousand, eight hundred and sixty patients were admitted over the study period. One thousand and eight of these [1008; 54.2%], were male, while eight hundred and fifty two [850; 45.8%] were female, making a female/male ratio of 1:1.18.The patients ages ranged between fifteen and ninety years, with a mean of 51.56 +/- 18.35 years. The age range of male patients ranged from 16 to 88 years, with a mean of 55.55 +/- 17.99 years, while that of the female patients ranged from 15 to 90 years, with a mean of 57.14 +/- 13.79.The length of stay in the ward ranged from 1 to 97 days, with a mean of 10.32 +/- 10.93 days. There were 23.25 patients per bed per year and a bed occupancy rate of 65.74%. There were 240 deaths [12.90% of total admissions]. The interval between admission and death ranged between 1 and 31 days, with a mean of 7.14 +/- 6.7 days. One hundred and twenty four patients [124; 6.7%] were referred to other health facilities, while ninety six [96; 5.2%] left against medical advice.The commonest causes of admission in males was hypertension, diabetes mellitus and HIV, while in females, it was HIV, hypertension and diabetes mellitus. Commonest causes of death in males were hypertension, HIV and diabetes, while in female subjects, it was HIV, hypertension and diabetes.

CONCLUSION

Non-communicable diseases- [hypertension, diabetes mellitus] and HIV/AIDS were the major causes of admissions and death in both genders.

Critical care services and 2009 H1N1 influenza in Australia and New Zealand

BACKGROUND

Planning for the treatment of infection with the 2009 pandemic influenza A (H1N1) virus through health care systems in developed countries during winter in the Northern Hemisphere is hampered by a lack of information from similar health care systems.

METHODS

We conducted an inception-cohort study in all Australian and New Zealand intensive care units (ICUs) during the winter of 2009 in the Southern Hemisphere. We calculated, per million inhabitants, the numbers of ICU admissions, bed-days, and days of mechanical ventilation due to infection with the 2009 H1N1 virus. We collected data on demographic and clinical characteristics of the patients and on treatments and outcomes.

RESULTS

From June 1 through August 31, 2009, a total of 722 patients with confirmed infection with the 2009 H1N1 virus (28.7 cases per million inhabitants; 95% confidence interval [CI], 26.5 to 30.8) were admitted to an ICU in Australia or New Zealand. Of the 722 patients, 669 (92.7%) were under 65 years of age and 66 (9.1%) were pregnant women; of the 601 adults for whom data were available, 172 (28.6%) had a body-mass index (the weight in kilograms divided by the square of the height in meters) greater than 35. Patients infected with the 2009 H1N1 virus were in the ICU for a total of 8815 bed-days (350 per million inhabitants). The median duration of treatment in the ICU was 7.0 days (interquartile range, 2.7 to 13.4); 456 of 706 patients (64.6%) with available data underwent mechanical ventilation for a median of 8 days (interquartile range, 4 to 16). The maximum daily occupancy of the ICU was 7.4 beds (95% CI, 6.3 to 8.5) per million inhabitants. As of September 7, 2009, a total of 103 of the 722 patients (14.3%; 95% CI, 11.7 to 16.9) had died, and 114 (15.8%) remained in the hospital.

CONCLUSIONS

The 2009 H1N1 virus had a substantial effect on ICUs during the winter in Australia and New Zealand. Our data can assist planning for the treatment of patients during the winter in the Northern Hemisphere.

[The anesthetic service of a one-day hospital: is it an independent entity or a subdivision of the hospital?]

To evaluate the efficiency of the anesthetic service of a one-day hospital, the authors analyzed the anesthesias made over 5 years in 3219 (2119 males and 1100 females) patients in the Outpatient Surgery Center (OSC). Based on the given criteria for selecting patients for outpatient surgeries and the assessment of bed occupancy and load on an anesthetist, the author concluded that it is optimal to set up an anesthetic service in the OSC.

Inappropriate acute neurosurgical bed occupancy and short falls in rehabilitation: implications for the National Service Framework

Patients undergoing neurosurgical intervention may require different types of organized rehabilitation. A prospective study was performed of the care needs of neurosurgical inpatients between the ages of 16 and 70 years who were in acute wards for more than 2 weeks. Only 58% of bed occupancy days were devoted to essential acute neurosurgical ward management. This figure was even lower for patients admitted with subarachnoid haemorrhage (36%) or traumatic brain injury (38%). Overall, 21% of bed days would have more appropriately spent in 'rapid access'/acute rehabilitation beds, 13% in 'active participation' rehabilitation beds and 5% in cognitive/behavioural rehabilitation units. Addressing this unmet need would increase the availability of acute neurosurgery beds, without needing to build and staff more neurosurgery wards.

Factors associated with increasing nursing home closures

PURPOSE

We determine the rate of nursing home closures for 7 years (1999-2005) and examine internal (e.g., quality), organizational (e.g., chain membership), and external (e.g., competition) factors associated with these closures.

DESIGN AND METHOD

The names of the closed facilities and dates of closure from state regulators in all 50 states were obtained. This information was linked to the Online Survey, Certification, and Reporting data, which contains information on internal, organizational, and market factors for almost all nursing homes in the United States.

RESULTS

One thousand seven hundred and eighty-nine facilities closed over this time period (1999-2005). The average annual rate of closure was about 2 percent of facilities, but the rate of closure was found to be increasing. Nursing homes with higher rates of deficiency citations, hospital-based facilities, chain members, small bed size, and facilities located in markets with high levels of competition were more likely to close. High Medicaid occupancy rates were associated with a high likelihood of closure, especially for facilities with low Medicaid reimbursement rates.

IMPLICATIONS

As states actively debate about how to redistribute long-term care services/dollars, our findings show that they should be cognizant of the potential these decisions have for facilitating nursing home closures.

Forecasting models of emergency department crowding

OBJECTIVES

The authors investigated whether models using time series methods can generate accurate short-term forecasts of emergency department (ED) bed occupancy, using traditional historical averages models as comparison.

METHODS

From July 2005 through June 2006, retrospective hourly ED bed occupancy values were collected from three tertiary care hospitals. Three models of ED bed occupancy were developed for each site: 1) hourly historical average, 2) seasonal autoregressive integrated moving average (ARIMA), and 3) sinusoidal with an autoregression (AR)-structured error term. Goodness of fits were compared using log likelihood and Akaike's Information Criterion (AIC). The accuracies of 4- and 12-hour forecasts were evaluated by comparing model forecasts to actual observed bed occupancy with root mean square (RMS) error. Sensitivity of prediction errors to model training time was evaluated, as well.

RESULTS

The seasonal ARIMA outperformed the historical average in complexity adjusted goodness of fit (AIC). Both AR-based models had significantly better forecast accuracy for the 4- and the 12-hour forecasts of ED bed occupancy (analysis of variance [ANOVA] p < 0.01), compared to the historical average. The AR-based models did not differ significantly from each other in their performance. Model prediction errors did not show appreciable sensitivity to model training times greater than 7 days.

CONCLUSIONS

Both a sinusoidal model with AR-structured error term and a seasonal ARIMA model were found to robustly forecast ED bed occupancy 4 and 12 hours in advance at three different EDs, without needing data input beyond bed occupancy in the preceding hours.

Patient volume affects outcome in critically ill patients

CONTEXT

A positive relationship between patient volume and outcome has been demonstrated for a variety of clinical conditions and procedures, but the evidence is sparse for critically ill patients.

OBJECTIVE

To evaluate the relationship between patient volume and outcome in a large cohort of critically ill patients.

DESIGN

Prospective multicenter cohort study, January 1998 through December 2005.

SETTING

40 intensive care units in Austria.

PATIENTS

A total of 83,259 consecutively admitted patients.

MAIN OUTCOME MEASURES

Structural quality of participating ICUs was evaluated using a questionnaire and merged with the prospectively collected data. Volume related indices were then calculated, representing patient turnover, occupancy rate, nursing workload and diagnostic variability.

RESULTS

Univariate analysis revealed that several volume variables were associated with outcome: more patients treated per year per bed in the intensive care unit and more patients treated in the same diagnostic category reduced the risk of dying in the hospital (odds ratios, 0.967 and 0.991 for each additional 10 patients treated, respectively). In contrast, an increase in the patient-to-nurse ratio and an increase in the number of diagnostic categories were associated with increased mortality rates. Multivariate analysis confirmed these results. The relationship between the number of patients treated in the same diagnostic category and their outcomes showed not a linear but a U shape, with increasing mortality rates below and above a certain patient volume.

CONCLUSIONS

Our results provide evidence for a relationship between patient volume and outcome in critically ill patients. Besides the total number of patients, diagnostic variability plays an important role. The relationship between volume and outcome seems, however, to be complex and to be influenced by other variables, such as workload of nursing staff.

A comparison of infection control program resources, activities, and antibiotic resistant organism rates in Canadian acute care hospitals in 1999 and 2005: pre- and post-severe acute respiratory syndrome

BACKGROUND

The Resources for Infection Control in Hospitals (RICH) project assessed infection control programs and rates of antibiotic-resistant organisms (AROs) in Canadian acute care hospitals in 1999. In the meantime, the severe acute respiratory syndrome (SARS) outbreak and the concern over pandemic influenza have stimulated considerable government and health care institutional efforts to improve infection control systems in Canada.

METHODS

In 2006, a version of the RICH survey similar to the original RICH instrument was mailed to infection control programs in all Canadian acute care hospitals with 80 or more beds. We used chi(2), analysis of variance, and analysis of covariance analyses to test for differences between the 1999 and 2005 samples for infection control program components and ARO rates.

RESULTS

72.3% of Canadian acute care hospitals completed the RICH survey for 1999 and 60.1% for 2005. Hospital size was controlled for in analyses involving AROs and surveillance and control intensity levels. Methicillin-resistant Staphylococcus aureus (MRSA) rates increased from 1999 to 2005 (F = 9.4, P = .003). In 2005, the mean MRSA rate was 5.2 (standard deviation [SD], 6.1) per 1000 admissions, and, in 1999, it was 2.0 (SD, 2.9). Clostridium difficile-associated diarrhea rates trended up from 1999 to 2005 (F = 2.9, P = .09). In 2005, the mean Clostridium difficile-associated diarrhea rate was 4.7 (SD, 4.3), and, in 1999, it was 3.8 (SD, 4.3). The proportion of hospitals that reported having new nosocomial vancomycin-resistant Enterococcus (VRE) cases was greater in 2005 than in 1999 (chi(2) = 10.5, P = .001). In 1999, 34.5% (40/116) of hospitals reported having new nosocomial VRE cases, and, in 2005, 61.0% (64/105) reported new cases. Surveillance intensity index scores increased from a mean of 61.7 (SD, 18.5) in 1999 to 68.1 (SD, 15.4) in 2005 (F = 4.1, P = .04). Control intensity index scores trended upward slightly from a mean of 60.8 (SD, 14.6) in 1999 to 64.1 (SD, 12.2) in 2005 (F = 3.2, P = .07). Infection control professionals (ICP) full-time equivalents (FTEs) per 100 beds increased from a mean of 0.5 (SD, 0.2) in 1999 to 0.8 (SD, 0.3) in 2005 (F = 90.8, P < .0001). However, the proportion of ICPs in hospitals certified by the Certification Board of Infection Control decreased from 53% (SD, 46) in 1999 to 38% (SD, 36) in 2005 (F = 8.7, P = .004).

CONCLUSION

Canadian infection control programs in 2005 continued to fall short of expert recommendations for human resources and surveillance and control activities. Meanwhile, nosocomial MRSA rates more than doubled between 1999 and 2005, and hospitals reporting new nosocomial VRE cases increased 77% over the same period. Although investments have been made toward infection control programs in Canadian acute care hospitals, the rapid rise in ICP positions has not yet translated into marked improvements in surveillance and control activities. In the face of substantial increases in ARO rates in Canada, continued efforts to train ICPs and support hospital infection control programs are necessary.

Infection control resources in New York State hospitals, 2007

BACKGROUND

In July 2005, New York State legislation requiring the mandatory reporting of specific hospital-associated infections (HAIs) was passed by the legislature and signed by the governor. In an effort to measure the impact of this legislation on infection control resources, the New York State Department of Health (NYSDOH) conducted a baseline survey in March 2007. This report presents an overview of the methods and results of this survey.

METHODS

An electronic survey of infection control resources and responsibilities was conducted by the NYSDOH on their secure data network. The survey contained questions regarding the number and percent time for infection prevention and control professional (ICP) and hospital epidemiologist (HE) staff members, ICP/HE educational background and certification, infection control program support services, activities and responsibilities of infection prevention and control program staff, and estimates of time dedicated to various activities, including surveillance.

RESULTS

Practitioners in 222 of 224 acute care hospitals (99%) responded. The average number of ICPs per facility depended on the average daily census of acute care beds and ranged from a mean of 0.64 full-time equivalent (FTE) ICP in facilities with an average daily census of < or = 100 beds to 6.5 FTE ICPs in facilities with an average daily census of > or = 900 beds. Averaging the ICP resources over the health care settings for which they were responsible revealed that the "average full-time ICP" was responsible for 151 acute care facility beds, 1.3 intensive care units (ICUs) (average, 16 ICU beds), 21 long-term care facility beds, 0.6 dialysis centers, 0.5 ambulatory surgery centers, 4.8 ambulatory/outpatient clinics, and 1.1 private practice offices. The ICPs reported that 45% of their time is dedicated to surveillance. Other activities for which ICPs reported at least partial responsibility include staff education, quality assurance, occupational health, emergency preparedness, construction, central supply/processing, and risk management.

CONCLUSIONS

This survey was designed to monitor and assess infection prevention and control resources and activities in hospitals as New York State embarks on mandatory public reporting of HAI rates. Monitoring infection control resources and activities will be important as HAI reporting moves forward. The information collected will serve as a baseline, and repeat surveys will be conducted to determine which, if any, of the various indicators correlate with the completeness and accuracy of HAI reporting.

Changes in patient mortality based on increased patient load in the emergency department

Being able to better understand the effects of emergency department overcrowding can improve patient outcome. We propose to evaluate various predictors of mortality based on our ability to identify at what point an ED becomes too busy causing decreased quality of care. The study aims to utilize information from hospital records and statewide death records to find significant increases in mortality associated with presenting to the ED during a busy period of time.

Nurse labor effects of residency work hour limits

Hospitals employing large numbers of residents increased their hiring of registered nurses, (including nurse practitioners, nurse anesthetists, and other RNs with greater training) significantly more than hospitals with smaller numbers of residents as a result of the ACGME work hours reforms. Patient safety was the main intent of the regulation and should remain the central concern when discussing the merits of resident work-hours limitations. However, the regulations also reduced the number of resident labor hours available to hospitals. This analysis suggests that nurses have compensated for reduced resident workload, with an additional full-time nurse for every 5.5 residents. This finding contributes to a better understanding of the hospital labor response to the regulation that resulted in the reduction in resident hours.

Retrospective analysis of hospital episode statistics, involuntary admissions under the Mental Health Act 1983, and number of psychiatric beds in England 1996-2006

OBJECTIVE

To analyse the number of voluntary and involuntary (detentions under the Mental Health Act 1983) admissions for mental disorders between 1996 and 2006 in England.

DESIGN

Retrospective analysis.

SETTING

England.

MAIN OUTCOME MEASURES

Number of voluntary and involuntary admissions for mental disorders in England's health service, number of involuntary admissions to private beds, and number of NHS beds for patients with mental disorders or learning disabilities.

RESULTS

Admissions for mental disorders in the NHS in England peaked in 1998 and then started to fall. Reductions in admissions were confined to patients with depression, learning disabilities, or dementia. Admissions for schizophrenic and manic disorders did not change whereas those for drug and alcohol problems increased. The number of NHS psychiatric beds decreased by 29%. The total number of involuntary admissions per annum increased by 20%, with a threefold increase in the likelihood of admission to a private facility. Patients admitted involuntarily occupied 23% of NHS psychiatric beds in 1996 but 36% in 2006.

CONCLUSIONS

Psychiatric inpatient care changed considerably in the decade from 1996 to 2006, with more involuntary admissions to fewer NHS beds. The case mix has shifted further towards psychotic and substance misuse disorders, which has changed the milieu of inpatient wards. Increasing proportions of involuntary patients were admitted to private facilities.