Temporal and demographic variations in attendance at accident and emergency departments

Variation in attendance at emergency departments in England across local areas: A system under unequal pressure

BACKGROUND

Crowding in Accident and Emergency Departments (AEDs) and long waiting times are critical issues contributing to adverse patient outcomes and system inefficiencies. These challenges are exacerbated by varying levels of AED attendance across different local areas, which may reflect underlying disparities in primary care provision and population characteristics.

METHOD

We used regression analysis to determine how much variation across local areas in England of attendance at emergency departments remained after controlling for population risk factors and alternative urgent care provision.

FINDINGS

There is substantial residual variation of the order of 3 to 1 (highest to lowest) in per person attendance rate across different areas. This is not related to in-hospital capacity as proxied by the per person number of hospital emergency doctors in an area.

CONCLUSION

Some areas in England have emergency departments that are under much greater pressure than others, and this cannot be explained in terms of their population characteristics or the availability of alternative treatment options. It is imperative to better understand the drivers of this variation so that effective interventions to address utilisation can be designed.

Enhancing Emergency Department Management: A Data-Driven Approach to Detect and Predict Surge Persistence

The prediction of patient attendance in emergency departments (ED) is crucial for effective healthcare planning and resource allocation. This paper proposes an early warning system that can detect emerging trends in ED attendance, offering timely alerts for proactive operational planning. Over 13 years of historical ED attendance data (from January 2010 till December 2022) with 1,700,887 data points were used to develop and validate: (1) a Seasonal Autoregressive Integrated Moving Average with eXogenous factors (SARIMAX) forecasting model; (2) an Exponentially Weighted Moving Average (EWMA) surge prediction model, and (3) a trend persistence prediction model. Drift detection was achieved with the EWMA control chart, and the slopes of a kernel-regressed ED attendance curve were used to train various machine learning (ML) models to predict trend persistence. The EWMA control chart effectively detected significant COVID-19 events in Singapore. The surge prediction model generated preemptive signals on changes in the trends of ED attendance over the COVID-19 pandemic period from January 2020 until December 2022. The persistence of novel trends was further estimated using the trend persistence model, with a mean absolute error of 7.54 (95% CI: 6.77-8.79) days. This study advanced emergency healthcare management by introducing a proactive surge detection framework, which is vital for bolstering the preparedness and agility of emergency departments amid unforeseen health crises.

A Comparison of Univariate and Multivariate Forecasting Models Predicting Emergency Department Patient Arrivals during the COVID-19 Pandemic

The COVID-19 pandemic has heightened the existing concern about the uncertainty surrounding patient arrival and the overutilization of resources in emergency departments (EDs). The prediction of variations in patient arrivals is vital for managing limited healthcare resources and facilitating data-driven resource planning. The objective of this study was to forecast ED patient arrivals during a pandemic over different time horizons. A secondary objective was to compare the performance of different forecasting models in predicting ED patient arrivals. We included all ED patient encounters at an urban teaching hospital between January 2019 and December 2020. We divided the data into training and testing datasets and applied univariate and multivariable forecasting models to predict daily ED visits. The influence of COVID-19 lockdown and climatic factors were included in the multivariable models. The model evaluation consisted of the root mean square error (RMSE) and mean absolute error (MAE) over different forecasting horizons. Our exploratory analysis illustrated that monthly and weekly patterns impact daily demand for care. The Holt-Winters approach outperformed all other univariate and multivariable forecasting models for short-term predictions, while the Long Short-Term Memory approach performed best in extended predictions. The developed forecasting models are able to accurately predict ED patient arrivals and peaks during a surge when tested on two years of data from a high-volume urban ED. These short- and long-term prediction models can potentially enhance ED and hospital resource planning.

Use of a Semi-Automatic Text Message System to Improve Satisfaction with Wait Time in the Adult Emergency Department: A Cross-Sectional Survey Study (Preprint)

Background

Objective

Methods

Results

Conclusions

Prevalence and Temporal Characteristics of Housing Needs in an Urban Emergency Department

Introduction

Our objective was to determine the proportion of patients in our emergency department (ED) who are unhoused or marginally housed and when they typically present to the ED.

Methods

We surveyed patients in an urban, safety-net ED from June–August 2018, using a sampling strategy that met them at all times of day, every day of the week. Patients used two social needs screening tools with additional questions on housing during sampling shifts representing two full weeks. Housing status was determined using items validated for housing stability, including PRAPARE, the Accountable Health Communities Survey, and items from the United States Department of Health and Human Services. Propensity scores estimated differences among respondents and non-respondents.

Results

Of those surveyed, 35% (95% confidence interval [CI], 31–38) identified as homeless and 28% (95% CI, 25–31) as unstably housed. Respondents and non-respondents were similar by propensity score. The average cumulative number of homeless and unstably housed patients arriving per daily 8-hour window peaks at 7 AM, with 46% (95% CI, 29–64) of the daily aggregate of those reporting homelessness and 44% (95% CI, 24–64) with unstable housing presenting over the next eight hours.

Conclusion

The ED represents a low-barrier contact point for reaching individuals experiencing housing challenges, who may interact rarely with other institutions. The current prevalence of homelessness and housing instability among urban ED patients may be substantially higher than reported in historical and national-level statistics. Housing services offered within normal business hours would reach a meaningful number of those who are unhoused or marginally housed

Association Between Emergency Physician Length of Stay Rankings and Patient Characteristics

OBJECTIVE

Emergency physicians are commonly compared by their patients' length of stay (LOS). We test the hypothesis that LOS is associated with patient characteristics and that accounting for these features impacts physician LOS rankings.

METHODS

This was a retrospective observational study of all encounters at an emergency department in 2010 to 2015. We compared the characteristics of patients seen by physicians in different quartiles of LOS. Primary outcome was variation in patient characteristics at time of physician assignment (age, sex, comorbidities, Emergency Severity Index [ESI], and chief complaint) across LOS quartiles. We also quantified the change in LOS rankings after accounting for difference in characteristics of patients seen by different physicians.

RESULTS

A total of 264,776 encounters seen by 62 attending physicians met inclusion criteria. Physicians in the longest LOS quartile saw patients who were older (age = 49.1 vs 48.6 years, difference = +0.5 years, 95% confidence interval [CI] = 0.3 to 0.7) with more comorbidities (Gagne score = 1.3 vs. 0.9, difference = +0.4, 95% CI = 0.4 to 0.4) and higher acuity (ESI = 2.8 vs. 2.9, difference = -0.1, 95% CI = 0.1 to 0.1) than physicians in the shortest LOS quartile. The odds ratio (OR) of physicians in the longest LOS quartile seeing patients over age 50 compared to the shortest LOS quartile was 1.1 (95% CI = 1.0 to 1.1); the OR of physicians in the longest LOS quartile seeing patients with ESI of 1 or 2 was also 1.1 (95% CI = 1.0 to 1.1). Accounting for variation in patient characteristics seen by different physicians resulted in substantial reordering of physician LOS rankings: 62.9% (39/62) of physicians reclassified into a different quartile with mean absolute percentile change of 25.8 (95% CI = 20.3 to 31.3). A total of 62.5% (10/16) of physicians in the shortest LOS quartile and 56.3% (9/16) in the longest LOS quartile moved into a different quartile after accounting for variation in patient characteristics.

CONCLUSIONS

Length of stay was significantly associated with patient characteristics, and accounting for variation in patient characteristics resulted in substantial reordering of relative physician rankings by LOS. Comparisons of emergency physicians by LOS that do not account for patient characteristics should be reconsidered.

Association of Clinical Characteristics With Variation in Emergency Physician Preferences for Patients

Importance

Much of the wide variation in health care has been associated with practice variation among physicians. Physicians choosing to see patients with more (or fewer) care needs could also produce variations in care observed across physicians.

Objective

To quantify emergency physician preferences by measuring nonrandom variations in patients they choose to see.

Design, Setting, and Participants

This cross-sectional study used a large, detailed clinical data set from an electronic health record system of a single academic hospital. The data set included all emergency department (ED) encounters of adult patients from January 1, 2010, to May 31, 2015, as well as ED visits information. Data were analyzed from September 1, 2018, to March 31, 2019.

Exposure

Patient assignment to a particular emergency physician.

Main Outcomes and Measures

Variation in patient characteristics (age, sex, acuity [Emergency Severity Index score], and comorbidities) seen by emergency physicians before patient selection, adjusted for temporal factors (seasonal, weekly, and hourly variation in patient mix).

Results

This study analyzed 294 915 visits to the ED seen by 62 attending physicians. Of the 294 915 patients seen, the mean (SD) age was 48.6 (19.8) years and 176 690 patients (59.9%) were women. Many patient characteristics, such as age (F = 2.2; P < .001), comorbidities (F = 1.7; P < .001), and acuity (F = 4.7; P < .001), varied statistically significantly. Compared with the lowest-quintile physicians for each respective characteristic, the highest-quintile physicians saw patients who were older (mean age, 47.9 [95% CI, 47.8-48.1] vs 49.7 [95% CI, 49.5-49.9] years, respectively; difference, +1.8 years; 95% CI, 1.5-2.0 years) and sicker (mean comorbidity score: 0.4 [95% CI, 0.3-0.5] vs 1.8 [95% CI, 1.7-1.8], respectively; difference, +1.3; 95% CI, 1.2-1.4). These differences were absent or highly attenuated during overnight shifts, when only 1 physician was on duty and there was limited room for patient selection. Compared with earlier in the shift, the same physician later in the shift saw patients who were younger (mean age, 49.7 [95% CI, 49.4-49.7] vs 44.6 [95 % CI, 44.3-44.9] years, respectively; difference, -5.1 years; 95% CI, 4.8-5.5) and less sick (mean comorbidity score: 0.7 [95% CI, 0.7-0.8] vs 1.1 [95% CI, 1.1-1.1], respectively; difference, -0.4; 95% CI, 0.4-0.4). Accounting for preference variation resulted in substantial reordering of physician ranking by care intensity, as measured by ED charges, with 48 of 62 physicians (77%) being reclassified into a different quintile and 9 of 12 physicians (75%) in the highest care intensity quintile moving into a lower quintile. A regression model demonstrated that 22% of reported ED charges were associated with physician preference.

Conclusions and Relevance

This study found preference variation across physicians and within physicians during the course of a shift. These findings suggest that current efforts to reduce practice variation may not affect the variation associated with physician preferences, which reflect underlying differences in patient needs and not physician practice.

Emergency department patient experience: Same location, same provider, different scores by different survey methods

BACKGROUND

Recent findings on emergency department (ED) patient experience surveys and concerns for the low response rates challenge the quality and reliability of the survey reports. We assessed the consistency of an ED patient experience survey report and identified the effects of patient demographics on ED patient experiences.

METHODS

We conducted a prospective, cross-sectional study at a university-based ED from July to December 2017. We obtained ED patient experience scores from an institutional version (IS) survey and the Press Ganey Associates-distributed survey (PGA). We compared top box scores from the two reports using frequency analysis and performed multivariable logistic regressions to identify associations between IS patient demographics and scores.

RESULTS

We obtained 289 PGA and 234 IS responses. The IS reported significant, higher top box scores in doctor-specific patient questions compared to PGA (all four P-values < 0.01). Female, Christian and White patients were more likely to give top box scores (OR 3.07, OR 2.22 and OR 2.41, P-value < 0.05, respectively).

CONCLUSION

We found significant differences in ED patient experience scores between the IS and PGA surveys. We recommend that healthcare providers consider patient demographic variables when interpreting ED experience score reports. Multiple survey techniques and distribution methods may be adopted to best capture ED patient experiences.

Factors and outcomes associated with paediatric emergency department arrival patterns through the day

Introduction

Steadily increasing emergency department (ED) utilization has prompted efforts to increase resource allocation to meet demand. Little is known about the distribution and characteristics of patient arrivals by time of day. This study describes the variability and patterns of ED resource utilization related to patient, acuity, clinical, and disposition characteristics over a 24-hour period.

Methods

Retrospective cross-sectional study of all visits to a tertiary children's hospital over a 1-year period. We use descriptive statistics to present ED visit details stratified by shift of arrival, and multivariable regression to explore the association between shift of presentation and hospital admission at index and 7-day return ED visits.

Results

Of 46,942 visits during the study period, 12% arrived overnight, 42% during the day, and 45% during the evening with variability in pattern of shift arrival by day of week. Overnight arrivals had a higher acuity (Canadian Triage and Acuity Scale [CTAS]) and different presenting complaints (more viral infection, less minor trauma) than day and evening arrivals, but similar ED length of stay. Shift of arrival was not associated with admission to hospital, but age, gender, socioeconomic status (SES), and day of week were.

Discussion

ED utilization patterns vary by shift of arrival. Though overnight arrivals represent a smaller proportion of total daily arrivals, their acuity is higher, and the spectrum of disease differs from day or evening arrivals.

Conclusions

Understanding variations and patterns of ED utilization by shift of arrival and day of week may be helpful in tailoring resource allocation to more accurately and specifically meet demands.

A simple tool to predict admission at the time of triage

Aim

To create and validate a simple clinical score to estimate the probability of admission at the time of triage.

Methods

This was a multicentre, retrospective, cross-sectional study of triage records for all unscheduled adult attendances in North Glasgow over 2 years. Clinical variables that had significant associations with admission on logistic regression were entered into a mixed-effects multiple logistic model. This provided weightings for the score, which was then simplified and tested on a separate validation group by receiving operator characteristic (ROC) analysis and goodness-of-fit tests.

Results

215 231 presentations were used for model derivation and 107 615 for validation. Variables in the final model showing clinically and statistically significant associations with admission were: triage category, age, National Early Warning Score (NEWS), arrival by ambulance, referral source and admission within the last year. The resulting 6-variable score showed excellent admission/discharge discrimination (area under ROC curve 0.8774, 95% CI 0.8752 to 0.8796). Higher scores also predicted early returns for those who were discharged: the odds of subsequent admission within 28 days doubled for every 7-point increase (log odds=+0.0933 per point, p<0.0001).

Conclusions

This simple, 6-variable score accurately estimates the probability of admission purely from triage information. Most patients could accurately be assigned to ‘admission likely’, ‘admission unlikely’, ‘admission very unlikely’ etc., by setting appropriate cut-offs. This could have uses in patient streaming, bed management and decision support. It also has the potential to control for demographics when comparing performance over time or between departments.

Eye casualty services in London

The combined pressures of the European Working Time Directive, 4 h waiting time target, and growing rates of unplanned hospital attendances have forced a major consolidation of eye casualty departments across the country, with the remaining units seeing a rapid increase in demand. We examine the effect of these changes on the provision of emergency eye care in Central London, and see what wider lessons can be learned. We surveyed the managers responsible for each of London's 8 out-of-hours eye casualty services, analysed data on attendance numbers, and conducted detailed interviews with lead clinicians. At London's two largest units, Moorfields Eye Hospital and the Western Eye Hospital, annual attendance numbers have been rising at 7.9% per year (to 76 034 patients in 2010/11) and 9.6% per year (to 31 128 patients in 2010/11), respectively. Using Moorfields as a case study, we discuss methods to increase capacity and efficiency in response to this demand, and also examine some of the unintended consequences of service consolidation including patients travelling long distances to geographically inappropriate units, and confusion over responsibility for out-of-hours inpatient cover. We describe a novel 'referral pathway' developed to minimise unnecessary travelling and delay for patients, and propose a forum for the strategic planning of London's eye casualty services in the future.

Likelihood of acute coronary syndrome in emergency department chest pain patients varies with time of presentation

BACKGROUND

There is a circadian and circaseptal (weekly) variation in the onset of acute coronary syndrome (ACS). The aim of this study was to elucidate whether the likelihood of ACS among emergency department (ED) chest pain patients varies with the time of presentation.

METHODS

All patients presenting to the Lund ED at Skåne University Hospital with chest pain or discomfort during 2006 and 2007 were retrospectively included. Age, sex, arrival time at the ED and discharge diagnose (ACS or not) were obtained from the electronic medical records.

RESULTS

There was a clear but moderate circadian variation in the likelihood of ACS among presenting chest pain patients, the likelihood between 8 and 10 am being almost twice as high as between 6 and 8 pm. This was mainly explained by a variation in the ACS likelihood in females and patients under 65 years, with no significant variation in males and patients over 65 years. There was no significant circaseptal variation in the ACS likelihood.

CONCLUSIONS

Our results indicate that there is a circadian variation in the likelihood of ACS among ED chest pain patients, and suggest that physicians should consider the time of presentation to the ED when determining the likelihood of ACS.

Characteristics of family violence victims presenting to emergency departments in Hong Kong

BACKGROUND

The Emergency Department (ED) has been shown to be a valuable location to screen for family violence.

STUDY OBJECTIVE

To investigate the characteristics of family violence victims presenting to EDs in a Chinese population in Hong Kong.

METHODS

This study examined a retrospective cohort of patients presenting to the Accident and Emergency Departments of three regional hospitals in the Kwai Tsing district of Hong Kong for evaluation and management of physical injuries related to family violence during the period of January 1, 1997 to December 31, 2008.

RESULTS

A total of 15,797 patients were assessed. The sample comprised cases of intimate partner violence (IPV; n=10,839), child abuse and neglect (CAN; n=3491), and elder abuse (EA; n=1467). Gender differences were found in patterns of ED utilization among the patients. The rates of readmission were 12.9% for IPV, 12.8% for CAN, and 8.9% for EA. Logistic regression showed that being male, being discharged against medical advice, and arriving at the hospital via ambulance were the common factors associated with readmission to the EDs for patients victimized by IPV and CAN.

CONCLUSION

This study investigates the victim profile of a large cohort of a Chinese population, providing a unique data set not previously released in this cultural or medical system. The findings give insights to early identification of victims of family violence in the EDs and suggest that screening techniques focused on multiple forms of family violence would improve identification of violence cases. Multidisciplinary collaboration between health, legal, and social service professionals is also warranted to meet the various needs of victims and to reduce hospital readmissions.

Patient throughput times and inflow patterns in Swedish emergency departments. A basis for ANSWER, A National SWedish Emergency Registry

OBJECTIVE

Quality improvement initiatives in emergency medicine (EM) often suffer from a lack of benchmarking data on the quality of care. The objectives of this study were twofold: 1. To assess the feasibility of collecting benchmarking data from different Swedish emergency departments (EDs) and 2. To evaluate patient throughput times and inflow patterns.

METHOD

We compared patient inflow patterns, total lengths of patient stay (LOS) and times to first physician at six Swedish university hospital EDs in 2009. Study data were retrieved from the hospitals' computerized information systems during single on-site visits to each participating hospital.

RESULTS

All EDs provided throughput times and patient presentation data without significant problems. In all EDs, Monday was the busiest day and the fewest patients presented on Saturday. All EDs had a large increase in patient inflow before noon with a slow decline over the rest of the 24 h, and this peak and decline was especially pronounced in elderly patients. The average LOS was 4 h of which 2 h was spent waiting for the first physician. These throughput times showed a considerable diurnal variation in all EDs, with the longest times occurring 6-7 am and in the late afternoon.

CONCLUSION

These results demonstrate the feasibility of collecting benchmarking data on quality of care targets within Swedish EM, and form the basis for ANSWER, A National SWedish Emergency Registry.

Walk-ins seeking treatment at an emergency department or general practitioner out-of-hours service: a cross-sectional comparison

Background

Emergency Departments (ED) in Switzerland are faced with increasing numbers of patients seeking non-urgent treatment. The high rate of walks-ins with conditions that may be treated in primary care has led to suggestions that those patients would best cared for in a community setting rather than in a hospital. Efficient reorganisation of emergency care tailored to patients needs requires information on the patient populations using the various emergency services currently available. The aim of this study is to evaluate the differences between the characteristics of walk-in patients seeking treatment at an ED and those of patients who use traditional out-of-hours GP (General Practitioner) services provided by a GP-Cooperative (GP-C).

Methods

In 2007 and 2009 data was collected covering all consecutive patient-doctor encounters at the ED of a hospital and all those occurring as a result of contacting a GP-C over two evaluation periods of one month each. Comparison was made between a GP-C and the ED of the Waid City Hospital in Zurich. Patient characteristics, time and source of referral, diagnostic interventions and mode of discharge were evaluated. Medical problems were classified according to the International Classification of Primary Care (ICPC-2). Patient characteristics were compared using non-parametric tests and multiple logistic regression analysis was applied to investigate independent determinants for contacting a GP-C or an ED.

Results

Overall a total of 2974 patient encounters were recorded. 1901 encounters were walk-ins and underwent further analysis (ED 1133, GP-C 768). Patients consulting the GP-C were significantly older (58.9 vs. 43.8 years), more often female (63.5 vs. 46.9%) and presented with non-injury related medical problems (93 vs. 55.6%) in comparison with patients at the ED. Independent determining factors for ED consultation were injury, male gender and younger age. Walk-in distribution in both settings was equal over a period of 24 hours and most common during daytime hours (65%).

Outpatient care was predominant in both settings but significantly more so at the GP-C (79.9 vs. 85.7%).

Conclusions

We observed substantial differences between the two emergency settings in a non gate-keeping health care system. Knowledge of the distribution of diagnoses, their therapy, of diagnostic measures and of the factors which determine the patients' choice of the ED or the GP-C is essential for the efficient allocation of resources and the reduction of costs.

Forecasting emergency department crowding: a discrete event simulation

STUDY OBJECTIVE

To develop a discrete event simulation of emergency department (ED) patient flow for the purpose of forecasting near-future operating conditions and to validate the forecasts with several measures of ED crowding.

METHODS

We developed a discrete event simulation of patient flow with evidence from the literature. Development was purely theoretical, whereas validation involved patient data from an academic ED. The model inputs and outputs, respectively, are 6-variable descriptions of every present and future patient in the ED. We validated the model by using a sliding-window design, ensuring separation of fitting and validation data in time series. We sampled consecutive 10-minute observations during 2006 (n=52,560). The outcome measures--all forecast 2, 4, 6, and 8 hours into the future from each observation--were the waiting count, waiting time, occupancy level, length of stay, boarding count, boarding time, and ambulance diversion. Forecasting performance was assessed with Pearson's correlation, residual summary statistics, and area under the receiver operating characteristic curve.

RESULTS

The correlations between crowding forecasts and actual outcomes started high and decreased gradually up to 8 hours into the future (lowest Pearson's r for waiting count=0.56; waiting time=0.49; occupancy level=0.78; length of stay=0.86; boarding count=0.79; boarding time=0.80). The residual means were unbiased for all outcomes except the boarding time. The discriminatory power for ambulance diversion remained consistently high up to 8 hours into the future (lowest area under the receiver operating characteristic curve=0.86).

CONCLUSION

By modeling patient flow, rather than operational summary variables, our simulation forecasts several measures of near-future ED crowding, with various degrees of good performance.

The effect of aromatherapy massage with music on the stress and anxiety levels of emergency nurses: comparison between summer and winter

AIMS AND OBJECTIVES

This research aimed to evaluate the use of aromatherapy massage and music as an intervention to cope with the occupational stress and anxiety that emergency department staff experience. The study also aimed to compare any differences in results between a summer and winter 12-week massage plan.

BACKGROUND

Emergency nurses are subjected to significant stressors during their work and it is known that workloads and patient demands influence the role stress has on nurses. The perception that winter months are busier for emergency departments has long been held and there is some evidence that people with cardiac and respiratory dysfunction do present more frequently in the winter months. Massage has been found to decrease staff anxiety.

DESIGN

The study used a one-group pre-test, post-test quasi-experimental design with random assignment.

METHOD

Staff occupational stress was assessed pre- and post- 12 weeks of aromatherapy massage with music and anxiety was measured pre and post each massage session. Sick leave was also measured. Comparisons of summer and winter data were undertaken.

RESULTS

A total of 365 massages were given over two 12-week periods, one during summer and the other during winter. Analysis identified that aromatherapy massage with music significantly reduced anxiety for both seasonal periods. Premassage anxiety was significantly higher in winter than summer. No differences in sick leave and workload were found. There was no difference in the occupational stress levels of nurses following the two 12-week periods of massage.

CONCLUSION

Emergency nurses were significantly more anxious in winter than summer but this cannot be attributed to increased sick leave or workloads. Aromatherapy massage with music significantly reduced emergency nurses' anxiety.

RELEVANCE TO CLINICAL PRACTICE

High levels of anxiety and stress can be detrimental to the physical and emotional health of emergency nurses and the provision of a support mechanism such as on-site massage as an effective strategy should be considered.

Short stay emergency admissions to a West Midlands NHS Trust: a longitudinal descriptive study, 2002 2005

OBJECTIVES

To describe changes and characteristics in emergency admissions to a West Midlands National Health Service Trust, 2002-2005, with a focus on short stay emergency admissions.

METHODS

A longitudinal descriptive study using retrospective analysis of routine admissions data. Admissions were categorised as short (0/1 day) or long (>or=2 days) and examined separately using a General Linear Model. Factors favouring short stays as opposed to long stays were examined using multivariable logistic regression.

RESULTS

There were 151 478 emergency admissions to the Trust between 1 April 2002 and 31 December 2005, of which 2910 (1.92%) had no discharge date recorded. Adjusted means showed a 7.76% increase in emergency admissions in winter months (October-January) and a 14.50% increase across the study period. Increases were greater in short stay (34.03%) than long stay emergency admissions (8.38%). Odds of short stays in admitted patients increased by 25%. Higher odds of short stays were also associated with younger age, winter month and medical admitting specialty (p<0.001).

CONCLUSIONS

Increases in emergency admissions were greater in short stay than long stay cases. Reasons for this may be both appropriate (increased use of clinical protocols and falling average length of stay) and detrimental (pressure to meet 4 h emergency department target, changing primary care provision). Further research is needed before generalising findings to other Trusts.

Out-of-hours demand for GP care and emergency services: patients' choices and referrals by general practitioners and ambulance services

Background

Over the last five years, Dutch provision of out-of-hours primary health care has shifted from practice-based services towards large-scale general practitioner (GP) cooperatives. Only few population-based studies have been performed to assess the out-of-hours demand for GP and emergency care, including the referral patterns to the Accident and Emergency Department (AED) by GPs and ambulance services.

Method

During two four-month periods (five-year interval), a prospective cross-sectional study was performed for a Dutch population of 62,000 people. Data were collected on all patient contacts with one GP cooperative and three AEDs bordering the region.

Results

Overall, GPs handled 88% of all out-of-hours contacts (275/1000 inhabitants/year), while the AED dealt with the remaining 12% of contacts (38/1000 inhabitants/year). Within the AED, the self-referrals represented a substantial number of contacts (43%), although within the total out-of-hours demand they only represented 5% of all contacts. Self-referrals were predominantly young adult males presenting with an injury, nineteen percent of whom had a fracture. Compared to self-referrals, patients who were referred by the GP or brought in by the ambulance services were generally older and were more frequently admitted for both injury and non-injury (p < 0.01 for all differences).

Conclusion

The GP cooperative deals with the large majority of out-of-hours problems presented. Within the total demand, self-referrals constitute a stable, yet small group of patients, many of whom seem to have made a reasonable choice to attend the AED. The GPs and the ambulance services appear to be effectively selecting the problems that are presented to the AED.

The effect of working hours on outcome from major trauma

OBJECTIVE

To determine whether being admitted with major trauma to an emergency department outside rather than within working hours results in an adverse outcome.

METHODS

The data were collected from hospitals in England and Wales participating in the Trauma Audit and Research Network (TARN). Data from the TARN database were used. Admission time and discharge status were cross matched, and this was repeated while controlling for Injury Severity Score (ISS) values. Logistic regression was carried out, calculating the effects of Revised Trauma Score (RTS), ISS, age, and time of admission on outcome from major trauma. This allowed observed versus expected mortality rates (Ws) scores to be compared within and outside working hours. As much of the RTS data were missing, this was repeated using the Glasgow Coma Score instead of RTS.

RESULTS

In total, 5.2% of people admitted "out of hours" died, compared with 5.3% of people within working hours, and 12.2% of people admitted outside working hours had an ISS score greater than 15, compared with 10.1% admitted within working hours. Outcome in cases with comparable ISS values were very similar (31.1% of cases with ISS >15 died out of hours, compared with 33.5% inside working hours.) The subgroup of data with missing RTS values had a significantly increased risk of death. Therefore, GCS was used to calculate severity adjusted odds of death instead of RTS. However, with either model, Ws scores were identical (both 0%) within and outside working hours.

CONCLUSIONS

Out of hours admission does not in itself have an adverse effect on outcome from major trauma.

Social care's impact on emergency medicine: a model to test

Mainly in response to the policy drive to avoid unnecessary acute hospital admissions and delayed discharge on social grounds, there has been a gradual development of social work services attached to emergency departments (EDs) in the UK. In the absence of a clearly articulated evidence base or debate about the roles of ED attached social workers, a model of ED based social work practice and indicative supporting evidence is presented. It is argued that social workers may be able to contribute to the efficiency and effectiveness of hospital services while providing a key point of access to social care services. A number of obstacles remain to the implementation of this model of service, including the narrow focus of current social care practice, the hours that a social work service is normally provided, chronic under-funding, and continuing perverse incentives in the health and social care system. More systematic evidence in the UK context is needed to support the case for change.