Emergency Department Occupancy Rate Research Articles

Development of a machine-learning algorithm to predict in-hospital cardiac arrest for emergency department patients using a nationwide database

In this retrospective observational study, we aimed to develop a machine-learning model using data obtained at the prehospital stage to predict in-hospital cardiac arrest in the emergency department (ED) of patients transferred via emergency medical services. The dataset was constructed by attaching the prehospital information from the National Fire Agency and hospital factors to data from the National Emergency Department Information System. Machine-learning models were developed using patient variables, with and without hospital factors. We validated model performance and used the SHapley Additive exPlanation model interpretation. In-hospital cardiac arrest occurred in 5431 of the 1,350,693 patients (0.4%). The extreme gradient boosting model showed the best performance with area under receiver operating curve of 0.9267 when incorporating the hospital factor. Oxygen supply, age, oxygen saturation, systolic blood pressure, the number of ED beds, ED occupancy, and pulse rate were the most influential variables, in that order. ED occupancy and in-hospital cardiac arrest occurrence were positively correlated, and the impact of ED occupancy appeared greater in small hospitals. The machine-learning predictive model using the integrated information acquired in the prehospital stage effectively predicted in-hospital cardiac arrest in the ED and can contribute to the efficient operation of emergency medical systems.

Exploring Potential Association Between Emergency Department Crowding Status and Patients' Length of Stay at a University Hospital in Saudi Arabia.

BackgroundEmergency department (ED) crowding has been described as the most serious problem that endangers the reliability of healthcare system worldwide. The aim of this study was to explore the possible relationship of ED crowding status and length of stay in patient received care. In addition, association between LOS and other variables in relation to crowding status has been explored.MethodsThis is a retrospective cohort analysis study done by using dataset abstracted from Quadra Med Information System of patients visited emergency department of a tertiary university hospital at Eastern Province of Saudi Arabia during the period of January 1st, 2018 to December 30th, 2018. ED occupancy rates were used to define crowding status (as crowding and overcrowding), while the percentage of patient who spent in ED more than 6 hours was used to define the length of stay in ED.ResultsThere were 53,309 crowded and 57,290 overcrowded presentations in ED. The median length ± interquartile range of the length of stay for low-crowded and high-crowded conditions were 211 ± 606 and 242 ± 659 minutes, respectively. There was a significant association between ED crowding status and length of stay (p < 0.05).ConclusionThe increased patients’ length of stay at ED was associated with crowding status of ED. Therefore, decision-makers at ministry of health should develop and implement measures and interventions to shed light on the causes of crowding, to reduce the crowding at ED, and resolve the problem steamed from such crowding for the purpose of shorten patients’ length of stay at ED.

Maximum emergency department overcrowding is correlated with occurrence of unexpected cardiac arrest

BackgroundEmergency department overcrowding negatively impacts critically ill patients and could lead to the occurrence of cardiac arrest. However, the association between emergency department crowding and the occurrence of in-hospital cardiac arrest has not been thoroughly investigated. This study aimed to evaluate the correlation between emergency department occupancy rates and the incidence of in-hospital cardiac arrest.MethodsA single-center, observational, registry-based cohort study was performed including all consecutive adult, non-traumatic in-hospital cardiac arrest patients between January 2014 and June 2017. We used emergency department occupancy rates as a crowding index at the time of presentation of cardiac arrest and at the time of maximum crowding, and the average crowding rate for the duration of emergency department stay for each patient. To calculate incidence rate, we divided the number of arrest cases for each emergency department occupancy period by accumulated time. The primary outcome is the association between the incidence of in-hospital cardiac arrest and emergency department occupancy rates.ResultsDuring the study period, 629 adult, non-traumatic cardiac arrest patients were enrolled in our registry. Among these, 187 patients experienced in-hospital cardiac arrest. Overall survival discharge rate was 24.6%, and 20.3% of patients showed favorable neurologic outcomes at discharge. Emergency department occupancy rates were positively correlated with in-hospital cardiac arrest occurrence. Moreover, maximum emergency department occupancy in the critical zone had the strongest positive correlation with in-hospital cardiac arrest occurrence (Spearman rank correlation ρ = 1.0, P < .01). Meanwhile, occupancy rates were not associated with the ED mortality.ConclusionMaximum emergency department occupancy was strongly associated with in-hospital cardiac arrest occurrence. Adequate monitoring and managing the maximum occupancy rate would be important to reduce unexpected cardiac arrest.

MP38: The impact of physician handoffs on the outcomes of emergency department patients: a medical administrative database retrospective cohort study

Introduction: A physician handoff is the process through which physicians transfer the primary responsibility of a care unit. The emergency department (ED) is a fast-paced and crowded environment where the risk of information loss between shifts is significant. Yet, the impact of handoffs between emergency physicians on patient outcomes remains understudied. We performed a retrospective cohort study in the ED to determine if handed-off patients, when compared to non-handed-off patients, were at higher risk of negative outcomes. Methods: We included every adult patient first assessed by an emergency physician and subsequently admitted to hospital in one of the five sites of the CHU de Québec-Université Laval during fiscal year 2016-17. Data were extracted from the local hospital discharge database and the ED information system. Primary outcome was mortality. Secondary outcomes were incidence of ICU admission and surgery and hospital length of stay. We conducted multilevel multivariate regression analyses, accounting for patient and hospital clusters and adjusting for demographics, CTAS score, comorbidities, admitting department delay before evaluation by an emergency physician and by another specialty, emergency department crowding, initial ED orientation and handoff timing. We conducted sensitivity analyses excluding patients that had an ED length of stay &gt; 24 hours or events that happened after 72 hours of hospitalization. Results: 21,136 ED visits and 17,150 unique individuals were included in the study. Median[Q1-Q3] age, Charlson index score, door-to-emergency-physician time and ED length of stay were 71[55-83] years old, 3[1-4], 48 [24,90] minutes, 20.8[9.9,32.7] hours, respectively. In multilevel multivariate analysis (OR handoff/no handoff [CI95%] or GMR[SE]), handoff status was not associated with mortality 0.89[0.77,1.02], surgery 0.95[0.85,1.07] or hospital length of stay (-0.02[0.03]). Non-handed-off patients had an increased risk of ICU admission (0.75[0.64,0.87]). ED occupancy rate was an independent predictor of mortality and ICU admission rate irrespectively of handoff status. Sensitivity and sub-group based analyses yielded no further information. Conclusion: Emergency physicians’ handoffs do not seem to increase the risk of severe in-hospital adverse events. ED occupancy rate is an independent predictor of mortality. Further studies are needed to explore the impact of ED handoffs on adverse events of low and moderate severity.

Emergency Department Crowding Is Associated With Delayed Antibiotics for Sepsis

Barriers to early antibiotic administration for sepsis remain poorly understood. We investigated the association between emergency department (ED) crowding and door-to-antibiotic time in ED sepsis. We conducted a retrospective cohort study of ED sepsis patients presenting to 2 community hospitals, a regional referral hospital, and a tertiary teaching hospital. The primary exposure was ED occupancy rate, defined as the ratio of registered ED patients tolicensed ED beds. We defined ED overcrowding as an ED occupancy rate greater than or equal to 1. We used multivariable regression tomeasure the adjusted association between ED crowding and door-to-antibiotic time (elapsed time from ED arrival to first antibiotic initiation). Using Markov multistate models, we also investigated the association between ED crowding and pre-antibiotic care processes. Among 3,572 eligible sepsis patients, 70% arrived when the ED occupancy rate was greater than or equal to 0.5 and 14% arrived to an overcrowded ED. Median door-to-antibiotic time was 158 minutes (interquartile range 109 to 216 minutes). When the ED was overcrowded, 46% of patients received antibiotics within 3 hours of ED arrival compared with 63% when it was not (difference 14.4%; 95% confidence interval 9.7% to 19.2%). After adjustment, each 10% increase in ED occupancy rate was associated with a 4.0-minute increase (95% confidence interval 2.8 to 5.2 minutes) in door-to-antibiotic time and a decrease in the odds of antibiotic initiation within 3 hours (odds ratio 0.90; 95% confidence interval 0.88 to 0.93). Increasing ED crowding was associated with slower initial patient assessment but not further delays after the initial assessment. ED crowding was associated with increased sepsis antibiotic delay. Hospitals must devise strategies to optimize sepsis antibiotic administration during periods of ED crowding.

Outcome-Based Validity and Reliability Assessment of Raters Regarding the Admission Triage Level in the Emergency Department: a Cross-Sectional Study.

Introduction:Emergency department (ED) is usually the first line of healthcare supply to patients in non-urgent to critical situations and, if necessary, provides hospital admission. A dynamic system to evaluate patients and allocate priorities is necessary. Such a structure that facilitates patients’ flow in the ED is termed triage.Objective:This study was conducted to investigate the validity and reliability of implementation of Emergency Severity Index (ESI) system version 4 by triage nurses in an overcrowded referral hospital with more than 80000 patient admissions per year and an average emergency department occupancy rate of more than 80%. Method:This prospective cross-sectional study was conducted in a tertiary care teaching hospital and trauma center with an emergency medicine residency program. Seven participating expert nurses were asked to assess the ESI level of patients in 30 written scenarios twice within a three-week interval to evaluate the inter-rater and intra-rater reliability. Patients were randomly selected to participate in the study, and the triage level assigned by the nurses was compared with that by the emergency physicians. Finally, based on the patients’ charts, an expert panel evaluated the validity of the triage level.Results:During the study period, 527 patients with mean age of 54 ± 7 years, including 253 (48%) women and 274 (52%) men, were assessed by seven trained triage nurses. The degree of retrograde agreement between the collaborated expert panel’s evaluation and the actual triage scales by the nurses and physicians for all 5 levels was excellent, with the Cohen’s weighted kappa being 0.966 (CI 0.985–0.946, p < 0.001) and 0.813 (CI 0.856–0.769, p<0.001), respectively. The intra-rater reliability was 0.94 (p < 0.0001), and the inter-rater reliability for all the nurses was in perfect agreement with the test result (Cohen’s weighted kappa were as follows: 0.919, 0.956, 0.911, 0.955, 0.860, 0.956, and 0.868; p < 0.001).Conclusion:The study findings showed that there was perfect reliability and, overall, almost perfect validity for the triage performed by the studied nurses.

Quantifying emergency department crowding: comparison between two scores

Introduction: Emergency department (ED) crowding is a major international concern with a negative impact on both patient care and providers. Currently, there is no consensus regarding measure of crowding. Therefore, emergency physicians have to choose between numerous scoring systems, from simple to more complex. The aim of the present study was to compare the complex National Emergency Department Overcrowding Scale (NEDOCS) with the simple ED Occupancy rate (OR) determination. We further evaluated the correlation between these scores and a qualitative assessment of crowding.Method: This study was conducted in two academic and one regional hospital in Liege Province, in Belgium; each accounting for an ED census of over 40,000 patient visits per year. Crowding measures were sampled four times a day, over a two-week period, in January 2016.Results: ED staff considered overcrowding as a major concern in the three ED. Median OR ranged from 68 to 100, while NEDOCS ranged from 64.5 to 76.3. A significant correlation was found in each ED between the OR and the NEDOCS (Pearson r = 0.973, 0.974 and 0.972), as well as between the OR, the NEDOCS and the subjective evaluation by the ED staff (p = 0.001).Conclusion: Crowding evaluation in ED requires validated scores. Our study in three different hospitals demonstrates that simple OR appeared as accurate as more sophisticated NEDOCS. Furthermore, this measure is perfectly correlated with the feeling of ED staff.

Emergency Overcrowding Impact on the Quality of Care of Patients Presenting with Acute Stroke.

Introduction:Emergency overcrowding is defined as when the amount of care required for patients overcomes the available amount. This can cause delays in delivering critical care in situations like stroke. Objective:The aim of this study was to assess the possible impact of emergency department (ED) crowding on the quality of care for acute stroke patients. Methods:In this cross-sectional prospective study, all patients with symptoms of acute stroke presenting to the ED of educational hospitals were enrolled. All patients were assessed and examined by the emergency medicine (EM) residents on shift and a questionnaire was filled out for them. The amount of time that passed from the first triage to performing the required interventions and delivering health services were recorded by the triage nurse. ED crowding was measured by the occupancy rate. Then, the correlation between all of the variables and ED crowding level were calculated. Results:The average daily bed occupancy rate was 184.9 ± 54.3%. The median time passed from the first triage to performing the interventions were as follows: the first EM resident visit after 34 min, the first neurologic visit after 138 min, head CT after 134 min, ECG after 104 min and ASA administration after 210 min. There was no statistically significant relationship between the ED occupancy rate and the time elapsed before different required health services in the management of stroke patients either throughout an entire day or during each 8-hour interval (p > 0.05). Conclusion:In the current study, the ED occupancy rate was not significantly correlated with the time frame associated with management of admitted acute stroke patients.

Optimal Measurement Interval for Emergency Department Crowding Estimation Tools

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. 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. 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). 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.

The impact of ED crowding on early interventions and mortality in patients with severe sepsis

ObjectiveCritically ill patients require significant time and care coordination in the emergency department (ED). We hypothesized that ED crowding would delay time to intravenous fluids and antibiotics, decrease utilization of protocolized care, and increase mortality for patients with severe sepsis or septic shock. MethodsThis was a retrospective cohort study of severe sepsis patients admitted to the hospital from the ED between January 2005 and February 2010. Associations between four validated measures of ED crowding (occupancy, waiting patients, admitted patients, and patient-hours) assigned at triage, and time of day, time to antibiotics and fluids, and mortality were tested by analyzing trends across crowding quartiles. ResultsDuring the study period, 2913 severe sepsis patients were admitted to the hospital and 1127 (38.7%) qualified for protocolized care. In-hospital mortality was 14.3% overall and 26% for patients qualifying for protocolized care. Time to IV fluids was delayed as ED occupancy rate increased and as patient hours increased. Time to antibiotics increased as occupancy rates, patient hours, and the number of boarding inpatients increased. Implementation rates of protocolized care decreased from 71.3% to 50.5% (p<0.0001, OR 0.39) as the number of ED inpatient boarders increased; initiation of protocolized care was significantly higher as occupancy increased (OR 1.52). Mortality was unaffected by crowding parameters in all analyses. ConclusionsWith increased ED crowding, time to critical severe sepsis therapies significantly increased and protocolized care initiation decreased. As crowding increases, EDs must implement systems that optimize delivery of time-sensitive therapies to critically ill patients.

Door-to-Imaging Time for Acute Stroke Patients Is Adversely Affected by Emergency Department Crowding.

National guidelines call for door-to-imaging time (DIT) within 25 minutes for suspected acute stroke patients. Studies examining factors that affect DIT have focused primarily on stroke-specific care processes and patient-specific factors. We hypothesized that emergency department (ED) crowding is associated with longer DIT. We conducted a retrospective investigation of 1 year of consecutive patients in our prospective Code Stroke registry, which included all ED stroke team activations. The registry and electronic health records were abstracted for 27 potential predictors of DIT, including patient, stroke care process, and ED operational factors. We fit a multivariate logistic regression model and calculated odds ratios and 95% confidence intervals. Second, we constructed a random forest recursive partitioning model to cross-validate our findings and explore the proportional importance of each category of predictor. Our primary outcome was the binary variable of DIT within the 25-minute goal. A total of 463 patients met inclusion criteria. In the regression model, ED occupancy rate emerged as a predictor of DIT, with odds ratio of 0.83 (95% confidence interval, 0.75-0.91) of DIT within 25 minutes per 10% absolute increase in ED occupancy rate. The secondary analysis estimated that ED operational factors accounted for nearly 14% of the algorithm's prediction of DIT. ED crowding is associated with reduced odds of meeting DIT goals for acute stroke. In addition to improving stroke-specific processes of care, efforts to reduce ED overcrowding should be considered central to optimizing the timeliness of acute stroke care.

Emergency Department Crowding Disparity: a Nationwide Cross-Sectional Study

In this study, we evaluated national differences in emergency department (ED) crowding to identify factors significantly associated with crowding in institutes and communities across Korea. This was a cross-sectional nationwide observational study using data abstracted from the National Emergency Department Information System (NEDIS). We calculated mean occupancy rates to quantify ED crowding status and divided EDs into three groups according to their occupancy rates (cutoffs: 0.5 and 1.0). Factors potentially related to ED crowding were collected from the NEDIS. We performed a multivariate regression analysis to identify variables significantly associated with ED crowding. A total of 120 EDs were included in the final analysis. Of these, 73 were categorized as 'low crowded' (LC, occupancy rate < 0.50), 37 as 'middle crowded' (MC, 0.50 ≤ occupancy rate < 1.00), 10 EDs as 'high crowded' (HC, 1.00 ≤ occupancy rate). The mean ED occupancy rate varied widely, from 0.06 to 2.33. The median value was 0.39 with interquartile ranges (IQRs) from 0.20 to 0.71. Multivariate analysis revealed that after adjustment, ED crowding was significantly associated with the number of visits, percentage of patients referred, number of nurses, and ED disposition. This nationwide study observed significant variety in ED crowding. Several input, throughput, and output factors were associated with crowding.

Abstract 19154: Emergency Department Overcrowding is Not Associated With Outcome of Out-of-hospital Cardiac Arrest

Aim of the study: Emergency department (ED) overcrowding is a worldwide problem associated with adverse outcomes. This study was performed to investigate the association between ED overcrowding and outcome and quality of cardiopulmonary resuscitation for out-of-hospital cardiac arrest (OHCA). Methods: Prospectively collected data including patient demographics, Utstein factors and outcomes on 608 consecutive OHCA patients at a single ED from January 2008 to December 2012 were retrospectively analyzed. The patients were categorized into 4 groups according to ED occupancy rate. The primary outcome was resuscitation outcome, a composite of rates of return of spontaneous circulation (ROSC), survival at discharge and neurological outcome at 6 months. The secondary outcome was resuscitation quality assessed by time to advanced airway, time to first drug administration, resuscitation duration in refractory cases and rate of initiation of therapeutic hypothermia after ROSC in the ED. Results: There was no significant difference in rates of ROSC, survival at discharge and good neurological outcome according to ED occupancy rate in the univariate and multivariate analyses (p &gt; 0.05). In addition, ED overcrowding was not associated with resuscitation quality (p &gt; 0.05). Conclusion: ED overcrowding was not associated with outcome of OHCA or resuscitation quality.

Emergency department crowding and the performance of damage control resuscitation in major trauma patients with hemorrhagic shock.

Uncontrolled hemorrhagic shock is the leading cause of potentially preventable death in major trauma patients. Damage control resuscitation (DCR), a strategy combining the techniques of permissive hypotension, hemostatic resuscitation, and damage control surgery, has been highly recommended for trauma patients. This study investigated whether emergency department (ED) crowding was associated with poor performance of the DCR strategies in treating hemorrhagic shock trauma patients. This was a retrospective cohort study in an urban tertiary hospital conducted from January 2010 to December 2013. Major trauma patients who presented to the ED with hemorrhagic shock were included. ED crowding, measured by ED occupancy rate, was categorized into three groups (low, medium, and high). The performance of DCR and inpatient outcomes were analyzed using multivariate logistic analysis. Of the 3,037 major trauma patients assessed, 852 met the inclusion criteria and were enrolled in the study. Patients in the high-crowding group had delayed initiation of transfusion (high vs. medium and low, 2.5 hours vs. 2.1 hours and 1.0 hours, respectively, p = 0.01), received less blood products in the ED (both comparisons p < 0.01), and experienced delays in procedures (4.5 hours vs. 3.3 hours and 2.4 hours, p < 0.01). However, the amount of crystalloid solution was similar among patients in all three groups (p = 0.17). In multivariate analysis, more patients from the high-crowding group developed traumatic coagulopathy in the intensive care unit (29.7% vs. 24.1% and 16.3%, p < 0.01), while no clear relationship was found between ED crowding and 30-day mortality or early lactate clearance rate (p > 0.05). ED crowding was associated with poor performance of DCR for major trauma patients in the ED. New strategies should be implemented to ameliorate crowded conditions and potential adverse outcomes.

Communication of Vital Signs at Emergency Department Handoff: Opportunities for Improvement

We describe the prevalence of vital sign communication errors during emergency department (ED) handoffs. Our secondary objective is to evaluate the association between handoff behaviors and ED crowding on vital sign handoff errors. This was a prospective observational study of ED handoffs conducted at an urban academic hospital. We observed a prespecified convenience sample of ED shift rounds and included all patients whose care was subject to a handoff during ED shift change. The primary outcome was vital sign communication errors, defined as the failure to communicate an episode of medical-record-documented hypotension or hypoxia during ED shift rounds. Trained research assistants used a standardized data collection tool to collect data through direct observation and electronic health record abstraction. We report descriptive statistics and results of a logistic regression model constructed with generalized estimating equations to describe the association between handoff and rounds-level characteristics and handoff errors. We observed 1,163 patient handoffs during 130 ED shift rounds. Of 117 patients with episodes of hypotension and 156 patients with hypoxia, 66 (42%) and 116 (74%) were not communicated at rounds, respectively. One hundred sixty-six handoffs (14%) included a vital sign communication error of omission. In multivariate analysis, no handoff or rounds characteristic, including the ED occupancy rate, was associated with omission errors of vital sign communication. Providers omitted communication of patient hypotension or hypoxia in nearly 1 in 7 ED handoffs. These communication errors do not appear to be related to ED crowding or care interruptions.

A cross-sectional study of emergency department boarding practices in the United States.

The median emergency department (ED) boarding time for admitted patients has been a nationally reportable core measure that now also affects ED accreditation and reimbursement. However, no direct national probability samples of ED boarding data have been available to guide this policy until now. The authors studied new National Hospital Ambulatory Medical Care Survey (NHAMCS) survey items to establish baseline values, to generate hypotheses for future research, and to help improve survey quality in the future. This was a cross-sectional, multistage, stratified annual analysis of EDs and ED visits from the National Hospital Ambulatory Medical Care Survey public use files from 2007 to 2010, a total of 139,502 visit records. These data represent the only national measure of ED boarding. The main outcome of interest was boarding duration for individual patient visits. Data analyses accounted for complex sampling design. The national median boarding time was 79 minutes, with an interquartile range of 36 to 145 minutes. The prevalence of boarding for more than 2 hours among admitted patients was 32% (95% confidence interval [CI] = 30% to 35%). Average ED volume, occupancy, acuity, and hospital admission rates increased abruptly from the second to the third quartile of median boarding duration. The half of hospitals with the longest median boarding times accounted for 73% of ED visits and 79% of ED hospitalizations nationally. Thirty-nine percent of EDs (95% CI = 32% to 46%) reported never holding patients for more than 2 hours, but visit-level analysis at these EDs found that 21% of admissions did in fact stay in the ED over 2 hours. Only 19% of EDs (95% CI = 16% to 22%) used a strategy of moving admitted patients to alternative sites in the hospital during crowded times. In this national survey, ED boarding of admitted patients disproportionately affects hospitals with higher ED volumes, which also see sicker patients who wait longer to be seen, but not hospitals with higher proportions of Medicaid or uninsured visits. This finding implies that, unlike other quality measures, there is a negative volume-outcome relationship for timely hospitalization from the ED.

Emergency Department Crowding is Associated with Reduced Satisfaction Scores in Patients Discharged from the Emergency Department

IntroductionEmergency department (ED) crowding has been shown to negatively impact patient outcomes. Few studies have addressed the effect of ED crowding on patient satisfaction. Our objective was to evaluate the impact of ED crowding on patient satisfaction in patients discharged from the ED.Methods:We measured patient satisfaction using Press-Ganey surveys returned by patients that visited our ED between August 1, 2007 and March 31, 2008. We recorded all mean satisfaction scores and obtained mean ED occupancy rate, mean emergency department work index (EDWIN) score and hospital diversion status over each 8-hour shift from data archived in our electronic tracking board. Univariate and multivariate logistic regression analysis was calculated to determine the effect of ED crowding and hospital diversion status on the odds of achieving a mean satisfaction score ≥ 85, which was the patient satisfaction goal set forth by our ED administration.Results:A total of 1591 surveys were returned over the study period. Mean satisfaction score was 77.6 (standard deviation [SD] ±16) and mean occupancy rate was 1.23 (SD ± 0.31). The likelihood of failure to meet patient satisfaction goals was associated with an increase in average ED occupancy rate (odds ratio [OR] 0.32, 95% confidence interval [CI] 0.17 to 0.59, P < 0.001) and an increase in EDWIN score (OR 0.05, 95% CI 0.004 to 0.55, P = 0.015). Hospital diversion resulted in lower mean satisfaction scores, but this was not statistically significant (OR 0.62, 95% CI 0.36 to 1.05). In multivariable analysis controlling for hospital diversion status and time of shift, ED occupancy rate remained a significant predictor of failure to meet patient satisfaction goals (OR 0.34, 95% CI 0.18 to 0.66, P = 0.001).Conclusion:Increased crowding, as measured by ED occupancy rate and EDWIN score, was significantly associated with reduced patient satisfaction. Although causative attribution was limited, our study suggested yet another negative impact resulting from ED crowding.

The adverse effect of emergency department crowding on compliance with the resuscitation bundle in the management of severe sepsis and septic shock

IntroductionThe aim of this study is to evaluate the effects of emergency department (ED) crowding on the implementation of tasks in the early resuscitation bundle during acute care of patients with severe sepsis and septic shock, as recommended by the Surviving Sepsis Campaign guidelines.MethodsWe analyzed the sepsis registry from August 2008 to March 2012 for patients presenting to an ED of a tertiary urban hospital and meeting the criteria for severe sepsis or septic shock. The ED occupancy rate, which was defined as the total number of patients in the ED divided by the total number of ED beds, was used for measuring the degree of ED crowding. It was categorized into three groups (low; intermediate; high crowding). The primary endpoint was the overall compliance with the entire resuscitation bundle.ResultsA total of 770 patients were enrolled. Of the eligible patients, 276 patients were assigned to the low crowding group, 250 patients to the intermediate crowding group, and 244 patients to the high crowding group (ED occupancy rate: ≤ 115; 116–149; ≥ 150%). There was significant difference in compliance rates among the three groups (31.9% in the low crowding group, 24.4% in the intermediate crowding group, and 16.4% in the high crowding group, P < 0.001). In a multivariate model, the high crowding group had a significant association with lower compliance (adjusted odds ratio (OR), 0.44; 95% confidence interval (CI), 0.26 to 0.76; P = 0.003). When the ED occupancy rate was included as a continuous variable in the model, it had also a negative correlation with the overall compliance (OR of 10% increase of the ED occupancy rate, 0.90; 95% CI, 0.84 to 0.96, P = 0.002).ConclusionsED crowding was significantly associated with lower compliance with the entire resuscitation bundle and decreased likelihood of the timely implementation of the bundle elements.

Further characterization of the influence of crowding on medication errors.

Study Objectives:Our prior analysis suggested that error frequency increases disproportionately with Emergency department (ED) crowding. To further characterize, we measured this association while controlling for the number of charts reviewed and the presence of ambulance diversion status. We hypothesized that errors would occur significantly more frequently as crowding increased, even after controlling for higher patient volumes.Materials and Methods:We performed a prospective, observational study in a large, community hospital ED from May to October of 2009. Our ED has full-time pharmacists who review orders of patients to help identify errors prior to their causing harm. Research volunteers shadowed our ED pharmacists over discrete 4- hour time periods during their reviews of orders on patients in the ED. The total numbers of charts reviewed and errors identified were documented along with details for each error type, severity, and category. We then measured the correlation between error rate (number of errors divided by total number of charts reviewed) and ED occupancy rate while controlling for diversion status during the observational period. We estimated a sample size requirement of at least 45 errors identified to allow detection of an effect size of 0.6 based on our historical data.Results:During 324 hours of surveillance, 1171 charts were reviewed and 87 errors were identified. Median error rate per 4-hour block was 5.8% of charts reviewed (IQR 0-13). No significant change was seen with ED occupancy rate (Spearman's rho = –.08, P = .49). Median error rate during times on ambulance diversion was almost twice as large (11%, IQR 0-17), but this rate did not reach statistical significance in univariate or multivariate analysis.Conclusions:Error frequency appears to remain relatively constant across the range of crowding in our ED when controlling for patient volume via the quantity of orders reviewed. Error quantity therefore increases with crowding, but not at a rate greater than the expected baseline error rate that occurs in uncrowded conditions. These findings suggest that crowding will increase error quantity in a linear fashion.

Pediatric Emergency Department Crowding Is Associated With a Lower Likelihood of Hospital Admission

Emergency department (ED) crowding may affect disposition decision-making. The objective was to measure the effect of ED crowding on probability of admission and return visit to the ED after discharge. The authors studied a historical cohort at a large pediatric ED over 40 months. Each patient was assigned a score on arrival based on the ED occupancy rate (the ratio of patients to beds). Patients were divided into quintiles by occupancy rate. The proportion admitted for each quintile was compared to the least crowded quintile adjusting for acuity, hospital occupancy, and time of arrival. The same analysis was performed for return visits to the ED within 48 hours. The analyses were repeated for the subsets of patients with asthma and with gastroenteritis and/or dehydration. From the 40 months of historical data, 198,778 visits were analyzed. The adjusted odds ratio (aOR) for admission among the whole cohort was 0.85 (95% confidence interval [CI]=0.81 to 0.89) comparing the highest to the lowest crowding quintiles (occupancy rate >1.17 and <0.54, respectively). For asthma patients, aOR=0.93 (95% CI=0.72 to 1.20), and for gastroenteritis patients, aOR=0.87 (95% CI=0.65 to 1.17). The aOR of return visits comparing the highest to the lowest crowding quintiles for all patients was aOR=0.87 (95% CI=0.79 to 0.97), for asthma patients was aOR=1.52 (95% CI=0.95 to 2.46), and for gastroenteritis patients was aOR=0.83 (95% CI=0.54 to 1.28). Increasing ED crowding is associated with a lower likelihood of hospital admission and lower frequency of return visits within 48 hours.