Volume-Related Differences in Emergency Department Performance

Overcrowding in Emergency Department: Causes, Consequences, and Solutions—A Narrative Review

Overcrowding in Emergency Departments (EDs) is a phenomenon that is now widespread globally and causes a significant negative impact that goes on to affect the entire hospital. This contributes to a number of consequences that can affect both the number of resources available and the quality of care. Overcrowding is due to a number of factors that in most cases lead to an increase in the number of people within the ED, an increase in mortality and morbidity, and a decrease in the ability to provide critical services in a timely manner to patients suffering from medical emergencies. This phenomenon results in the Emergency Department reaching, and in some cases exceeding, its optimal capacity. In this review, the main causes and consequences involving this phenomenon were collected, including the effect caused by the SARS-CoV-2 virus in recent years. Finally, special attention was paid to the main operational strategies that have been developed over the years, strategies that can be applied both at the ED level (microlevel strategies) and at the hospital level (macrolevel strategies).

Worsening of emergency department length of stay during the COVID-19 pandemic

OBJECTIVE

Our study sought to determine whether there was a change in emergency department (ED) length of stay (LOS) during the coronavirus disease 2019 (COVID-19) pandemic compared to prior years.

METHODS

We performed a retrospective analysis using ED performance data 2018-2020 from 56 EDs across the United States. We used a generalized estimating equation (GEE) model to assess differences in ED LOS for admitted (LOS-A) and discharged (LOS-D) patients during the COVID-19 pandemic period compared to prior years.

RESULTS

GEE modeling showed that LOS-A and LOS-D were significantly higher during the COVID-19 period compared to the pre-COVID-19 period. LOS-A during the COVID-19 period was 10.3% higher compared to the pre-COVID-19 time period, which represents a higher geometric mean of 28 minutes. LOS-D during the COVID-19 period was 2.8% higher compared to the pre-COVID-19 time period, which represents a higher geometric mean of 2 minutes.

CONCLUSIONS

ED LOS-A and LOS-D were significantly higher in the COVID-19 period compared to the pre-COVID-19 period despite a lower volume of patients in the COVID-19 period.

The development and validation of a resource consumption score of an emergency department consultation

Background

Emergency Department (ED) visits and health care costs are increasing globally, but little is known about contributing factors of ED resource consumption. This study aims to analyse and to predict the total ED resource consumption out of the patient and consultation characteristics in order to execute performance analysis and evaluate quality improvements.

Methods

Characteristics of ED visits of a large Swiss university hospital were summarized according to acute patient condition factors (e.g. chief complaint, resuscitation bay use, vital parameter deviations), chronic patient conditions (e.g. age, comorbidities, drug intake), and contextual factors (e.g. night-time admission). Univariable and multivariable linear regression analyses were conducted with the total ED resource consumption as the dependent variable.

Results

In total, 164,729 visits were included in the analysis. Physician resources accounted for the largest proportion (54.8%), followed by radiology (19.2%), and laboratory work-up (16.2%). In the multivariable final model, chief complaint had the highest impact on the total ED resource consumption, followed by resuscitation bay use and admission by ambulance. The impact of age group was small. The multivariable final model was validated (R² of 0.54) and a scoring system was derived out of the predictors.

Conclusions

More than half of the variation in total ED resource consumption can be predicted by our suggested model in the internal validation, but further studies are needed for external validation. The score developed can be used to calculate benchmarks of an ED and provides leaders in emergency care with a tool that allows them to evaluate resource decisions and to estimate effects of organizational changes.

Association between long boarding time in the emergency department and hospital mortality: a single-center propensity score-based analysis

Once diagnostic work-up and first therapy are completed in patients visiting the emergency department (ED), boarding them within the ED until an in-hospital bed became available is a common practice in busy hospitals. Whether this practice may harm the patients remains a debate. We sought to determine whether an ED boarding time longer than 4 h places the patients at increased risk of in-hospital death. This retrospective, propensity score-matched analysis and propensity score-based inverse probability weighting analysis was conducted in an adult ED in a single, academic, 1136-bed hospital in France. All patients hospitalized via the adult ED from January 1, 2013 to March 31, 2018 were included. Hospital mortality (primary outcome) and hospital length of stay (LOS) were assessed in (1) a matched cohort (1:1 matching of ED visits with or without ED boarding time longer than 4 h but similar propensity score to experience an ED boarding time longer than 4 h); and (2) the whole study cohort. Sensitivity analysis to unmeasured confounding and analyses in pre-specified cohorts of patients were conducted. Among 68,632 included ED visits, 17,271 (25.2%) had an ED boarding time longer than 4 h. Conditional logistic regression performed on a 10,581 pair-matched cohort, and generalized estimating equations with adjustment on confounders and stabilized propensity score-based inverse probability weighting applied on the whole cohort showed a significantly increased risk of hospital death in patients experiencing an ED boarding time longer than 4 h: odds ratio (OR) of 1.13 (95% confidence interval [95% CI] 1.05-1.22), P = 0.001; and OR of 1.12 (95% CI 1.03-1.22), P = 0.007, respectively. Sensitivity analyses showed that these findings might be robust to unmeasured confounding. Hospital LOS was significantly longer in patients exposed to ED boarding time longer than 4 h: median difference 2 days (95% CI 1-2) (P < 0.001) in matched analysis and mean difference 1.15 days (95% CI 1.02-1.28) (P < 0.001) in multivariable unmatched analysis. In this single-center propensity score-based cohort analysis, patients experiencing an ED boarding time longer than 4 h before being transferred to an in-patient bed were at increased risk of hospital death.

Clinical operations of academic versus non-academic emergency departments: a descriptive comparison of two large emergency department operations surveys

Background

Academic and non-academic emergency departments (EDs) are regularly compared in clinical operations benchmarking despite suggestion that the two groups may differ in their clinical operations characteristics. and outcomes. We sought to describe and compare clinical operations characteristics of academic versus non-academic EDs.

Methods

We performed a descriptive, comparative analysis of academic and non-academic adult and general EDs with 40,000+ annual encounters, using the Academy of Academic Administrators of Emergency Medicine (AAAEM)/Association of Academic Chairs of Emergency Medicine (AACEM) and Emergency Department Benchmarking Alliance (EDBA) survey results. We defined academic EDs as primary teaching sites for emergency medicine (EM) residencies and non-academic EDs as sites with minimal resident involvement. We constructed the academic and non-academic cohorts from the AAAEM/AACEM and EDBA surveys, respectively, and analyzed metrics common to both surveys.

Results

Eighty and 454 EDs met inclusion criteria for academic and non-academic EDs, respectively. Academic EDs had more median annual patient encounters (73,001 vs 54,393), lower median proportion of pediatric patients (6.3% vs 14.5%), higher median proportion of EMS patients (27% vs 19%), and were more commonly designated as Level I or II Trauma Centers (94% vs 24%). Median patient arrival-to-provider times did not differ (26 vs 25 min). Median length-of-stay was longer (277 vs 190 min) for academic EDs, and left-before-treatment-complete was higher (5.7% vs 2.9%). MRI utilization was higher for academic EDs (2.2% patients with at least one MRI vs 1.0 MRIs performed per 100 patients). Patients-per-hour of provider coverage was lower for academic EDs with and without consideration for advanced practice providers and residents.

Conclusions

Demographic and operational performance measures differ between academic and non-academic EDs, suggesting that the two groups may be inappropriate operational performance comparators. Causes for the differences remain unclear but the differences appear not to be attributed solely to the academic mission.

Establishment of a Unified Quality Indicators System to Increase the Effectiveness of Emergency Departments

The overall quality of an emergency department (ED) can be measured by its ability to provide fast, efficient yet high-quality medical treatments to its patients. The objective of the present study was to derive a common set of key indicators that could be used to assess the quality of the performance of EDs. A modified Delphi process was employed to achieve this. This consisted of a detailed literature review followed by a three-round expert panel interaction, which was used to reduce and refine the list of indicators. The members of the panel comprised ED physicians, ED nurses and hospital and ED administrators drawn from six EDs. This process yielded 47 essential performance indicators and 12 recommended indicators. The performance indicators were classified into 7 main groups according to their characteristics. The chosen indicators comprise a core set that will be used in an ongoing study on a representative sample of EDs.

Resource Utilization in Non-Academic Emergency Departments with Advanced Practice Providers

INTRODUCTION

Advanced practice providers (APP), including physicians' assistants and nurse practitioners, have been increasingly incorporated into emergency department (ED) staffing over the past decade. There is scant literature examining resource utilization and the cost benefit of having APPs in the ED. The objectives of this study were to compare resource utilization in EDs that use APPs in their staffing model with those that do not and to estimate costs associated with the utilized resources.

METHODS

In this five-year retrospective secondary data analysis of the Emergency Department Benchmarking Alliance (EDBA), we compared resource utilization rates in EDs with and without APPs in non-academic EDs. Primary outcomes were hospital admission and use of computed tomography (CT), radiography, ultrasound, and magnetic resonance imaging (MRI). Costs were estimated using the 2014 physician fee schedule and inpatient payments from the Centers for Medicare and Medicaid Services. We measured outcomes as rates per 100 visits. Data were analyzed using a mixed linear model with repeated measures, adjusted for annual volume, patient acuity, and attending hours. We used the adjusted net difference to project utilization costs between the two groups per 1000 visits.

RESULTS

Of the 1054 EDs included in this study, 79% employed APPs. Relative to EDs without APPs, EDs staffing APPs had higher resource utilization rates (use per 100 visits): 3.0 more admissions (95% confidence interval [CI], 2.0-4.1), 1.7 more CTs (95% CI, 0.2-3.1), 4.5 more radiographs (95% CI, 2.2-6.9), and 1.0 more ultrasound (95% CI, 0.3-1.7) but comparable MRI use 0.1 (95% CI, -0.2-0.3). Projected costs of these differences varied among the resource utilized. Compared to EDs without APPs, EDs with APPs were estimated to have 30.4 more admissions per 1000 visits, which could accrue $414,717 in utilization costs.

CONCLUSION

EDs staffing APPs were associated with modest increases in resource utilization as measured by admissions and imaging studies.

The emergency department landscape in The Netherlands: an exploration of characteristics and hypothesized relationships

BACKGROUND

Nationwide optimization of the emergency department (ED) landscape is being discussed in The Netherlands. The emphasis is put mostly on the number of EDs actually present at the time versus a proposed minimum number of EDs needed in the future. The predominant idea in general is that by concentrating emergency care in less EDs costs would be saved and quality of care would increase. However, structural insight into similarities as well as differences of ED characteristics is missing. This knowledge and fact interpretation is needed to provide better steering information which could contribute to strategies aiming to optimize the ED landscape. This study provides an in-depth insight in the ED landscape of The Netherlands by presentation of providing an overview of the variation in ED characteristics and by exploring associations between ED volume characteristics on one side and measures of available ED and hospital resources on the other side. Obtained insight can be a starting point towards a more well-founded future optimization policy.

METHODS

This is a nationwide cross-sectional observational study. All 24/7 operational EDs meeting the IFEM definition in The Netherlands in December 2016 were identified, contacted and surveyed. Requested information was retrieved from local hospital information systems and entered into a database. Till August 1, 2017, data have been collected.

RESULTS

All 87 eligible EDs in The Netherlands participated in this study (100%). All of them were hospital based. These were 8 EDs in universities (9%), 27 EDs in teaching hospitals (31%) and 52 EDs in general hospitals (60%). On average, 22,755 patients were seen per ED (range 6082-53,196). On average, 85% (range 44-99%) was referred versus 15% self-referred (range 1-56%). Further subdivision of the referred patients showed 17% 'emergency call' (range 0.5-30%), 52% by GPC (range 16-77%) and 15% other referral (range 1-52%). On average, 38% of patients per ED (range 13-76%) were hospitalized. ED treatment bays ranged from 4 to 36 and added nationally up to 1401 (mean and median of 16 per ED). The number of hospital beds behind these EDs ranged from 104 to 1339 and added up to 36,630 beds nationally (mean of 421 and median of 375 behind each ED). Information about ED nurse workforce was available for 83 of 87 EDs and ranged from 11 to 65, adding up to 2348 fulltime-equivalent nationally (mean of 28 and median of 27 per ED). We found positive and significant correlations, confirming all formulated hypotheses. The strongest correlation was seen between the number of patients seen in the ED and ED nurse workforce, followed by the number of patients seen in the ED and ED treatment bays. The other hypotheses showed less positive significant correlations.

CONCLUSION

Our study shows that the ED landscape is still pluriform by numbers and specifications of individual ED locations. This study identifies associations between patient and hospitalization volumes on a national level on one side and number of ED treatment bays, ED nurse workforce capacity and available hospital beds on the other side. These findings might be useful as input for the development of an ED resource allocation framework and a more targeted optimization policy in the future.

Can interprofessional teamwork reduce patient throughput times? A longitudinal single-centre study of three different triage processes at a Swedish emergency department

OBJECTIVE

To determine the impact on emergency department (ED) throughput times and proportion of patients who leave without being seen by a physician (LWBS) of two triage interventions, where comprehensive nurse-led triage was first replaced by senior physician-led triage and then by interprofessional teamwork.

DESIGN

Single-centre before-and-after study.

SETTING

Adult ED of a Swedish urban hospital.

PARTICIPANTS

Patients arriving on weekdays 08:00 to 21:00 during three 1-year periods in the interval May 2012 to November 2015. A total of 185 806 arrivals were included.

INTERVENTIONS

Senior physicians replaced triage nurses May 2013 to May 2014. Interprofessional teamwork replaced the triage process on weekdays 08:00 to 21:00 November 2014 to November 2015.

MAIN OUTCOME MEASURES

Primary outcomes were the median time to physician (TTP) and the median length of stay (LOS). Secondary outcome was the LWBS rate.

RESULTS

The crude median LOS was shortest for teamwork, 228 min (95% CI 226.4 to 230.5) compared with 232 min (95% CI 230.8 to 233.9) for nurse-led and 250 min (95% CI 248.5 to 252.6) for physician-led triage. The adjusted LOS for the teamwork period was 16 min shorter than for nurse-led triage and 23 min shorter than for physician-led triage. The median TTP was shortest for physician-led triage, 56 min (95% CI 54.5 to 56.6) compared with 116 min (95% CI 114.4 to 117.5) for nurse-led triage and 74 min (95% CI 72.7 to 74.8) for teamwork. The LWBS rate was 1.9% for nurse-led triage, 1.2% for physician-led triage and 3.2% for teamwork. All outcome measure differences had two-tailed p values<0.01.

CONCLUSIONS

Interprofessional teamwork had the shortest length of stay, a shorter time to physician than nurse-led triage, but a higher LWBS rate. Interprofessional teamwork may be a useful approach to reducing ED throughput times.

Overcrowding and Its Association With Patient Outcomes in a Median-Low Volume Emergency Department

Background

Crowding occurs commonly in high volume emergency departments (ED) and has been associated with negative patient care outcomes. We aim to assess ED crowding in a median-low volume setting and evaluate associations with patient care outcomes.

Methods

This was a prospective single-center study from November 14, 2016 until December 14, 2016. ED crowding was measured every 2 h by three different estimation tools: National Emergency Department Overcrowding Score (NEDOCS); Community Emergency Department Overcrowding Score (CEDOCS); and Severely-overcrowding Overcrowding and Not-overcrowding Estimation Tool (SONET) categorized under six different levels of crowding (not busy, busy, extremely busy, overcrowded, severely overcrowded, and dangerously overcrowded). Crowding scores were assigned to each patient upon ED arrival. We evaluated the distributions of crowding and patient ED length of stay (ED LOS) across estimation tools. Accelerated failure time models were utilized to estimate time ratios and their corresponding 95% confidence intervals comparing median LOS across levels of crowding within each estimation tool.

Results

This study comprised 2,557 patients whose median ED LOS was 150 min. Approximately 2% of patients arrived during 2 h time intervals deemed overcrowded regardless of the crowding tool used. Median ED LOS increased with the increased level of ED crowding and prolonged median ED LOS (> 150 min) occurred at ED of extremely busy status. Time ratios ranged from 1.09 to 1.48 for NEDOCS, 1.25 - 1.56 for CEDOCS, and 1.26 - 1.72 for SONET.

Conclusion

Overcrowding rarely occurred in study ED with median-low annual volume and might not be a valuable marker for ED crowding report. Though similar patterns of prolonged ED LOS occurred with increased levels of ED crowding, it seems crowding alerts should be initiated during extremely busy status in this ED setting.

Optimal Measurement Interval for Emergency Department Crowding Estimation Tools

STUDY OBJECTIVE

Emergency department (ED) crowding is a barrier to timely care. Several crowding estimation tools have been developed to facilitate early identification of and intervention for crowding. Nevertheless, the ideal frequency is unclear for measuring ED crowding by using these tools. Short intervals may be resource intensive, whereas long ones may not be suitable for early identification. Therefore, we aim to assess whether outcomes vary by measurement interval for 4 crowding estimation tools.

METHODS

Our eligible population included all patients between July 1, 2015, and June 30, 2016, who were admitted to the JPS Health Network ED, which serves an urban population. We generated 1-, 2-, 3-, and 4-hour ED crowding scores for each patient, using 4 crowding estimation tools (National Emergency Department Overcrowding Scale [NEDOCS], Severely Overcrowded, Overcrowded, and Not Overcrowded Estimation Tool [SONET], Emergency Department Work Index [EDWIN], and ED Occupancy Rate). Our outcomes of interest included ED length of stay (minutes) and left without being seen or eloped within 4 hours. We used accelerated failure time models to estimate interval-specific time ratios and corresponding 95% confidence limits for length of stay, in which the 1-hour interval was the reference. In addition, we used binomial regression with a log link to estimate risk ratios (RRs) and corresponding confidence limit for left without being seen.

RESULTS

Our study population comprised 117,442 patients. The time ratios for length of stay were similar across intervals for each crowding estimation tool (time ratio=1.37 to 1.30 for NEDOCS, 1.44 to 1.37 for SONET, 1.32 to 1.27 for EDWIN, and 1.28 to 1.23 for ED Occupancy Rate). The RRs of left without being seen differences were also similar across intervals for each tool (RR=2.92 to 2.56 for NEDOCS, 3.61 to 3.36 for SONET, 2.65 to 2.40 for EDWIN, and 2.44 to 2.14 for ED Occupancy Rate).

CONCLUSION

Our findings suggest limited variation in length of stay or left without being seen between intervals (1 to 4 hours) regardless of which of the 4 crowding estimation tools were used. Consequently, 4 hours may be a reasonable interval for assessing crowding with these tools, which could substantially reduce the burden on ED personnel by requiring less frequent assessment of crowding.

Risk-Adjusted Variation of Publicly Reported Emergency Department Timeliness Measures

STUDY OBJECTIVE

The Centers for Medicare & Medicaid Services (CMS) recently published emergency department (ED) timeliness measures. These data show substantial variation in hospital performance and suggest the need for process improvement initiatives. However, the CMS measures are not risk adjusted and may provide misleading information about hospital performance and variation. We hypothesize that substantial hospital-level variation will persist after risk adjustment.

METHODS

This cross-sectional study included hospitals that participated in the Emergency Department Benchmarking Alliance and CMS ED measure reporting in 2012. Outcomes included the CMS measures corresponding to median annual boarding time, length of stay of admitted patients, length of stay of discharged patients, and waiting time of discharged patients. Covariates included hospital structural characteristics and case-mix information from the American Hospital Association Survey, CMS cost reports, and the Emergency Department Benchmarking Alliance. We used a γ regression with a log link to model the skewed outcomes. We used indirect standardization to create risk-adjusted measures. We defined "substantial" variation as coefficient of variation greater than 0.15.

RESULTS

The study cohort included 723 hospitals. Risk-adjusted performance on the CMS measures varied substantially across hospitals, with coefficient of variation greater than 0.15 for all measures. Ratios between the 10th and 90th percentiles of performance ranged from 1.5-fold for length of stay of discharged patients to 3-fold for waiting time of discharged patients.

CONCLUSION

Policy-relevant variations in publicly reported CMS ED timeliness measures persist after risk adjustment for nonmodifiable hospital and case-mix characteristics. Future "positive deviance" studies should identify modifiable process measures associated with high performance.

Disparities in Adherence to Pediatric Sepsis Guidelines across a Spectrum of Emergency Departments: A Multicenter, Cross-Sectional Observational In Situ Simulation Study

BACKGROUND

Each year in the United States, 72,000 pediatric patients develop septic shock, at a cost of $4.8 billion. Adherence to practice guidelines can significantly reduce mortality; however, few methods to compare performance across a spectrum of emergency departments (EDs) have been described.

OBJECTIVES

We employed standardized, in situ simulations to measure and compare adherence to pediatric sepsis guidelines across a spectrum of EDs. We hypothesized that pediatric EDs (PEDs) would have greater adherence to the guidelines than general EDs (GEDs). We also explored factors associated with improved performance.

METHODS

This multi-center observational study examined in situ teams caring for a simulated infant in septic shock. The primary outcome was overall adherence to the pediatric sepsis guideline as measured by six subcomponent metrics. Characteristics of teams were compared using multivariable logistic regression to describe factors associated with improved performance.

RESULTS

We enrolled 47 interprofessional teams from 24 EDs. Overall, 21/47 teams adhered to all six sepsis metrics (45%). PEDs adhered to all six metrics more than GEDs (93% vs. 22%; difference 71%, 95% confidence interval [CI] 43-84). Adherent teams had significantly higher Emergency Medical Services for Children readiness scores, MD composition of physicians to total team members, teamwork scores, provider perceptions of pediatric preparedness, and provider perceptions of sepsis preparedness. In a multivariable regression model, only greater composite team experience had greater adjusted odds of achieving an adherent sepsis score (adjusted odds ratio 1.38, 95% CI 1.01-1.88).

CONCLUSIONS

Using standardized in situ scenarios, we revealed high variability in adherence to the pediatric sepsis guideline across a spectrum of EDs. PEDs demonstrated greater adherence to the guideline than GEDs; however, in adjusted analysis, only composite team experience level of the providers was associated with improved guideline adherence.

Emergency department performance measures updates: proceedings of the 2014 emergency department benchmarking alliance consensus summit

OBJECTIVES

The objective was to review and update key definitions and metrics for emergency department (ED) performance and operations.

METHODS

Forty-five emergency medicine leaders convened for the Third Performance Measures and Benchmarking Summit held in Las Vegas, February 21-22, 2014. Prior to arrival, attendees were assigned to workgroups to review, revise, and update the definitions and vocabulary being used to communicate about ED performance and operations. They were provided with the prior definitions of those consensus summits that were published in 2006 and 2010. Other published definitions from key stakeholders in emergency medicine and health care were also reviewed and circulated. At the summit, key terminology and metrics were discussed and debated. Workgroups communicated online, via teleconference, and finally in a face-to-face meeting to reach consensus regarding their recommendations. Recommendations were then posted and open to a 30-day comment period. Participants then reanalyzed the recommendations, and modifications were made based on consensus.

RESULTS

A comprehensive dictionary of ED terminology related to ED performance and operation was developed. This article includes definitions of operating characteristics and internal and external factors relevant to the stratification and categorization of EDs. Time stamps, time intervals, and measures of utilization were defined. Definitions of processes and staffing measures are also presented. Definitions were harmonized with performance measures put forth by the Centers for Medicare and Medicaid Services (CMS) for consistency.

CONCLUSIONS

Standardized definitions are necessary to improve the comparability of EDs nationally for operations research and practice. More importantly, clear precise definitions describing ED operations are needed for incentive-based pay-for-performance models like those developed by CMS. This document provides a common language for front-line practitioners, managers, health policymakers, and researchers.

Overall ED efficiency is associated with decreased time to percutaneous coronary intervention for ST-segment elevation myocardial infarction

BACKGROUND

Performance of percutaneous coronary intervention (PCI) within 90 minutes of hospital arrival for ST-segment elevation myocardial infarction patients is a commonly cited clinical quality measure. The Centers for Medicare and Medicaid Services use this measure to adjust hospital reimbursement via the Value-Based Purchasing Program. This study investigated the relationship between hospital performance on this quality measure and emergency department (ED) operational efficiency.

METHODS

Hospital-level data from Centers for Medicare and Medicaid Services on PCI quality measure performance was linked to information on operational performance from 272 US EDs obtained from the Emergency Department Benchmarking Alliance annual operations survey. Standard metrics of ED size, acuity, and efficiency were compared across hospitals grouped by performance on the door-to-balloon time quality measure.

RESULTS

Mean hospital performance on the 90-minute arrival to PCI measure was 94.0% (range, 42-100). Among hospitals failing to achieve the door-to-balloon time performance standard, median ED length of stay was 209 minutes, compared with 173 minutes among those hospitals meeting the benchmark standard (P < .001). Similarly, median time from ED patient arrival to physician evaluation was 39 minutes for hospitals below the performance standard and 23 minutes for hospitals at the benchmark standard (P < .001). Markers of ED size and acuity, including annual patient volume, admission rate, and the percentage of patients arriving via ambulance did not vary with door-to-balloon time.

CONCLUSION

Better performance on measures associated with ED efficiency is associated with more timely PCI performance.

Rebuilding Emergency Care After Hurricane Sandy

A freestanding, 911-receiving emergency department was implemented at Bellevue Hospital Center during the recovery efforts after Hurricane Sandy to compensate for the increased volume experienced at nearby hospitals. Because inpatient services at several hospitals remained closed for months, emergency volume increased significantly. Thus, in collaboration with the New York State Department of Health and other partners, the Health and Hospitals Corporation and Bellevue Hospital Center opened a freestanding emergency department without on-site inpatient care. The successful operation of this facility hinged on key partnerships with emergency medical services and nearby hospitals. Also essential was the establishment of an emergency critical care ward and a system to monitor emergency department utilization at affected hospitals. The results of this experience, we believe, can provide a model for future efforts to rebuild emergency care capacity after a natural disaster such as Hurricane Sandy. (Disaster Med Public Health Preparedness. 2014;0:1-4).

Association of emergency department and hospital characteristics with elopements and length of stay

BACKGROUND

As the Centers for Medicare & Medicaid Services (CMS) core measures in 2013 compare Emergency Department (ED) treatment time intervals, it is important to identify ED and hospital characteristics associated with these metrics to facilitate accurate comparisons.

STUDY OBJECTIVES

The objective of this study is to assess differences in operational metrics by ED and hospital characteristics. ED-level characteristics included annual ED volume, percentage of patients admitted, percentage of patients presenting by ambulance, and percentage of pediatric patients. Hospital-level characteristics included teaching hospital status, trauma center status, hospital ownership (nonprofit or for-profit), inpatient bed capacity, critical access status, inpatient bed occupancy, and rural vs. urban location area.

METHODS

Data from the ED Benchmarking Alliance from 2004 to 2009 were merged with the American Hospital Association's Annual Survey Database to include hospital characteristics that may impact ED throughput. Overall median length of stay (LOS) and left before treatment is complete (LBTC) were the primary outcome variables, and a linear mixed model was used to assess the association between outcome variables and ED and hospital characteristics, while accounting for correlations among multiple observations within each hospital. All data were at the hospital level on a yearly basis.

RESULTS

There were 445 EDs included in the analysis, from 2004 to 2009, with 850 observations over 6 years. Higher-volume EDs were associated with higher rates of LBTC and LOS. For-profit hospitals had lower LBTC and LOS. Higher inpatient bed occupancies were associated with a higher LOS. Increasing admission percentages were positively associated with overall LOS for EDs, but not with rates of LBTC.

CONCLUSIONS

Higher-volume EDs are associated with higher LBTC and LOS, and for-profit hospitals appear more favorably in these metrics compared with their nonprofit counterparts. It is important to appreciate that hospitals have different baselines for performance that may be more tied to volume and capacity, and less to quality of care.

Emergency care and health systems: consensus-based recommendations and future research priorities

The theme of the 14th annual Academic Emergency Medicine consensus conference was "Global Health and Emergency Care: A Research Agenda." The goal of the conference was to create a robust and measurable research agenda for evaluating emergency health care delivery systems. The concept of health systems includes the organizations, institutions, and resources whose primary purpose is to promote, restore, and/or maintain health. This article further conceptualizes the vertical and horizontal delivery of acute and emergency care in low-resource settings by defining specific terminology for emergency care platforms and discussing how they fit into broader health systems models. This was accomplished through discussion surrounding four principal questions touching upon the interplay between health systems and acute and emergency care. This research agenda is intended to assist countries that are in the early stages of integrating emergency services into their health systems and are looking for guidance to maximize their development and health systems planning efforts.

Real time shift reporting by emergency physicians predicts overall ED performance

OBJECTIVE

To investigate factors associated with emergency physician perception of the shift and to determine whether these perceptions were predictors of overall daily emergency department (ED) performance indicators.

METHODS

This was an observational study conducted at an inner city ED in New South Wales. Shift reports completed by the emergency physician in charge at clinical handover times between February and July 2012 were included. Variables collected by the shift report included (1) total number of patients in ED, (2) number of patients in the ED with length of stay (LOS) greater than 4 h, (3) number of admitted patients, (4) number of patients waiting to be seen by a doctor and (5) medical staffing levels. Outcomes of interest for this study were shift perception scores (1=very poor to 5=very good) and daily ED performance measures. Performance measures were the proportion of patients admitted or discharged from ED within 4 h (National Emergency Access Target, NEAT) and the percentage of inpatient admissions leaving ED within 8 h of ED arrival time.

RESULTS

The number of patients in ED with LOS >4 h (OR 0.83, 95% CI 0.79 to 0.87, p value <0.001) and number of patients waiting to be seen (OR 0.92, 95% CI 0.88 to 0.95, p value <0.001) were the factors most strongly associated with shift perception score. After adjustment, the mean NEAT performance improved 6% for each incremental increase in average shift perception score (β=0.06 95% CI 0.04 to 0.07, p<0.001).

CONCLUSIONS

Shift reports and shift perceptions by emergency physicians may be used to predict overall ED performance.