The Emergency Department Occupancy Rate: A Simple Measure of Emergency Department Crowding?

An Effective Methodology for Scoring to Assist Emergency Physicians in Identifying Overcrowding in an Academic Emergency Department in Thailand

BACKGROUND

Emergency Department (ED) overcrowding is a global concern, with tools like NEDOCS, READI, and Work Score used as predictors. These tools aid healthcare professionals in identifying overcrowding and preventing negative patient outcomes. However, there's no agreed-upon method to define ED overcrowding. Most studies on this topic are U.S.-based, limiting their applicability in EDs without waiting rooms or ambulance diversion roles. Additionally, the intricate calculations required for these scores, with multiple variables, make them impractical for use in developing nations.

OBJECTIVE

This study sought to examine the relationship between prevalent ED overcrowding scores such as EDWIN, occupancy rate, and Work Score, and a modified version of EDWIN newly introduced by the authors, in comparison to the real-time perspectives of emergency physicians. Additionally, the study explored the links between these overcrowding scores and adverse events related to ED code activations as secondary outcomes.

METHOD

The method described in the provided text is a correlational study. The study aims to examine the relationship between various Emergency Department (ED) overcrowding scores and the real-time perceptions of emergency physicians in every two-hour period. Additionally, it seeks to explore the associations between these scores and adverse events related to ED code activations.

RESULTS

The study analyzed 459 periods, with 5.2% having Likert scores of 5-6. EDOR had the highest correlation coefficient (0.69, p < 0.001) and an AUC of 0.864. Only EDOR significantly correlated with adverse events (p = 0.033).

CONCLUSION

EDOR shows the most robust link with 'emergency physicians' views on overcrowding. Additionally, elevated EDOR scores correlate with a rise in adverse events. Emergency physicians' perceptionof overcrowding could hint at possible adverse events. Notably, all overcrowding scores have high negative predictive values, efficiently negating the likelihood of adverse incidents.

Impacts of the 2021 heat dome on emergency department visits, hospitalizations, and health system operations in three hospitals in Seattle, Washington

Objectives

Extreme heat events (EHEs) are associated with excess healthcare utilization but specific impacts on emergency department (ED) operations and throughput are unknown. In 2021, the Pacific Northwest experienced an unprecedented heat dome that resulted in substantial regional morbidity and mortality. The aim of this study was to examine its impact on ED utilization, unplanned hospitalization, and hospital operations in a large academic healthcare system.

Methods

Retrospective electronic medical records from three Seattle-area hospitals were used to compare healthcare utilization during the EHE compared to a pre-event reference period within the same month. Interrupted time series analysis was used to evaluate the association between EHE exposure and ED visits and hospitalizations. Metrics of ED crowding for the EHE were compared to the reference period using Student's t-tests and chi-squared tests. Additionally, multivariable Poisson regression was used to identify risk factors for heat-related illness and hospital admission.

Results

Interrupted time series analysis showed an increase of 21.7 ED visits per day (95% confidence interval [CI] = 14.7, 28.6) and 9.9 unplanned hospitalizations per day (95% CI = 8.3, 11.5) during the EHE, as compared to the reference period. ED crowding and process measures also displayed significant increases, becoming the most pronounced by day 3 of the EHE; the EHE was associated with delays in ED length of stay of 1.0 h (95% CI = 0.4, 1.6) compared to the reference period. Higher incidence rate ratios for heat-related illness were observed for patients who were older (incidence rate ratio [IRR] = 1.02; 95% CI = 1.01,1.03), female (IRR = 1.47; 95% CI = 1.06, 2.04), or who had pre-existing diabetes (IRR = 3.19; 95% CI = 1.47, 6.94).

Conclusions

The 2021 heat dome was associated with a significant increase in healthcare utilization including ED visits and unplanned hospitalizations. Substantial impacts on ED and hospital throughput were also noted. These findings contribute to the understanding of the role extreme heat events play on impacting patient outcomes and healthcare system function.

Strategies to Measure and Improve Emergency Department Performance: A Review

Emergency Departments (EDs) globally face escalating challenges such as overcrowding, resource limitations, and increased patient demand. This study aims to identify and analyze strategies to enhance the structural performance of EDs, with a focus on reducing overcrowding, optimizing resource allocation, and improving patient outcomes. Through a comprehensive review of the literature and observational studies, the research highlights the effectiveness of various approaches, including triage optimization, dynamic staffing, technological integration, and strategic resource management. Key findings indicate that tailored strategies, such as implementing advanced triage protocols and leveraging telemedicine, can significantly reduce wait times and enhance patient throughput. Furthermore, evidence suggests that dynamic staffing models and the integration of cutting-edge diagnostic tools contribute to operational efficiency and improved quality of care. These strategies, when combined, offer a multifaceted solution to the complex challenges faced by EDs, promising better patient care and satisfaction. The study underscores the need for a comprehensive approach, incorporating both organizational and technological innovations, to address the evolving needs of emergency healthcare.

Association of emergency department crowding with inpatient outcomes

OBJECTIVE

To examine the association of higher emergency department (ED) census with inpatient outcomes on the day of discharge (inpatient length of stay, in-hospital mortality, ED revisits, and readmissions).

DATA SOURCES AND STUDY SETTING

All-payer ED and inpatient discharge data and hospital characteristics data from all non-federal, general, and acute care hospitals in the state of California from October 1, 2015 to December 31, 2017.

STUDY DESIGN

In retrospective data analysis, we examined whether ED census was associated with inpatient outcomes for all inpatients, including those not admitted through the ED. The main predictor variable was ED census on day of discharge, categorized based on hospital year and day of week. Separate linear regression models with robust SEs and hospital fixed effects examined the association of ED census on inpatient outcomes (length of stay, 3-day ED revisit, 30-day all-cause readmission, in-hospital mortality), controlling for patient and visit-level factors. We stratified analyses by whether admission was elective or unscheduled.

EXTRACTION METHODS

Inpatient discharges in non-federal, general medical hospitals with EDs.

PRINCIPAL FINDINGS

We examined 5,784,253 discharges. The adjusted model showed that, compared to when the ED was below the median, higher ED census on the day of discharge was associated with longer inpatient length of stay, lower readmissions, and higher in-hospital mortality (90th percentile for length of stay: +0.8% [95% confidence interval, CI: +0.6% to +1.1%]; readmissions: -0.59 percentage points [or -5.6%] [95% CI: -0.0071 to -0.0048]; mortality: +0.14 percentage points [or +5.4%] [95% CI: +0.0009 to +0.0018]). [Correction added on 18 November 2022, after first online publication: '[odds rato, OR -5.6%]' and '[OR +5.4%]' of the preceding sentence have been corrected to '[or -5.6%]' and '[or +5.4%]', respectively, in this version.] Results for length of stay were primarily driven by patients with elective admissions, while results for readmissions and in-hospital mortality were primarily driven by patients with unscheduled admissions.

CONCLUSIONS

This study suggests that ED crowding may affect inpatients throughout the hospital, even patients who are already admitted to the hospital.

Emergency department crowding and mortality: an observational multicenter study in Sweden

Background

Emergency department (ED) crowding is a serious problem worldwide causing decreased quality of care. It is reasonable to assume that the negative effects of crowding are at least partially due to high staff workload, but previous crowding metrics based on high workload have not been generalisable to Swedish EDs and have not been associated with increased mortality, in contrast to, e.g., occupancy rate. We recently derived and validated the modified Skåne Emergency Department Assessment of Patient Load model (mSEAL) that measures crowding based on staff workload in Swedish EDs, but its ability to identify situations with increased mortality is unclear. In this study, we aimed to investigate the association between ED crowding measured by mSEAL model, or occupancy rate, and mortality.

Methods

All ED patients from 2017-01-01 to 2017-06-30 from two regional healthcare systems (Skåne and Östergötland Counties with a combined population of approximately 1.8 million) in Sweden were included. Exposure was ED- and hour-adjusted mSEAL or occupancy rate. Primary outcome was mortality within 7 days of ED arrival, with one-day and 30-day mortality as secondary outcomes. We used Cox regression hazard ratio (HR) adjusted for age, sex, arrival by ambulance, hospital admission and chief complaint.

Results

We included a total of 122,893 patients with 168,900 visits to the six participating EDs. Arriving at an hour with a mSEAL score above the 95th percentile for that ED and hour of day was associated with an non-significant HR for death at 7 days of 1.04 (95% CI 0.96-1.13). For one- and 30-day mortality the HR was non-significant at 1.03 (95% CI 0.9-1.18) and 1.03 (95% CI 0.97-1.09). Similarly, occupancy rate above the 95th percentile with a HR of 1.04 (95% CI 0.9-1.19), 1.03 (95%CI 0.95-1.13) and 1.04 (95% CI 0.98-1.11) for one-, 7- and 30-day mortality, respectively.

Conclusion

In this multicenter study in Sweden, ED crowding measured by mSEAL or occupancy rate was not associated with a significant increase in short-term mortality.

Access block and overcrowding at the emergency department at Tupua Tamasese Meaole Hospital in Samoa

BACKGROUND

Access block and overcrowding are known to adversely impact on patient outcomes, service delivery, and patient experiences within emergency departments (ED) worldwide. There are no studies on access block or overcrowding from the Pacific Islands. The aim of the present study is to provide preliminary data on access block and overcrowding in the ED of the national tertiary hospital of Samoa.

METHODS

Mixed methods study design. Data collection was performed in March 2020. The quantitative strand calculated (1) the point prevalence of patients impacted by access block in the ED, and (2) the ED bed occupancy rate to assess for overcrowding. The qualitative strand used thematic analysis of two focus group interviews exploring access block and overcrowding with ED medical and nursing staff members.

RESULTS

On the day of data collection, a total of 60 patients presented through the ED triage system. Of the 20 patients who were admitted into ED, 80% were triaged as 'see without delay' (CAT1), 'emergency' (CAT2) or 'urgent' (CAT3). For patients requiring admission to hospital wards, 100% waited 4 + h in ED, and 100% waited 8 + h, suggesting the presence of access block. Overcrowding in the ED setting was also evident, with an ED bed occupancy rate of 0.95, and an adjusted bed occupancy rate of 1.43. The major themes emerging from the ED staff focus groups and individual in-depth interviews were (1) the adverse impacts of access block and overcrowding, i.e., violence towards ED staff members, (2) the preventable contributing factors, i.e., lack of physical beds in the ED, and (3) practical recommendations to improve patient flow through the ED, i.e., improved collaboration between ED, outpatient services, and the hospital wards.

CONCLUSIONS

Preliminary evidence suggested the presence of access block and overcrowding in the ED of the national tertiary hospital of Samoa. ED staff interviews provided insight into the ED frontline challenges and offered practical recommendations for ED health service improvement.

Five Level Triage vs. Four Level Triage in a Quaternary Emergency Department: National Analysis on Waiting Time, Validity, and Crowding-The CREONTE (Crowding and RE-Organization National TriagE) Study Group

Background and Objectives: Triage systems help provide the right care at the right time for patients presenting to emergency departments (EDs). Triage systems are generally used to subdivide patients into three to five categories according to the system used, and their performance must be carefully monitored to ensure the best care for patients. Materials and Methods: We examined ED accesses in the context of 4-level (4LT) and 5-level triage systems (5LT), implemented from 1 January 2014 to 31 December 2020. This study assessed the effects of a 5LT on wait times and under-triage (UT) and over-triage (OT). We also examined how 5LT and 4LT systems reflected actual patient acuity by correlating triage codes with severity codes at discharge. Other outcomes included the impact of crowding indices and 5LT system function during the COVID-19 pandemic in the study populations. Results: We evaluated 423,257 ED presentations. Visits to the ED by more fragile and seriously ill individuals increased, with a progressive increase in crowding. The length of stay (LOS), exit block, boarding, and processing times increased, reflecting a net raise in throughput and output factors, with a consequent lengthening of wait times. The decreased UT trend was observed after implementing the 5LT system. Conversely, a slight rise in OT was reported, although this did not affect the medium-high-intensity care area. Conclusions: Introducing a 5LT improved ED performance and patient care.

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.

A case study to investigate the impact of overcrowding indices in emergency departments

Background

Emergency department (ED) overcrowding is widespread in hospitals in many countries, causing severe consequences to patient outcomes, staff work and the system, with an overall increase in costs. Therefore, health managers are constantly looking for new preventive and corrective measures to counter this phenomenon. To do this, however, it is necessary to be able to characterize the problem objectively. For this reason, various indices are used in the literature to assess ED crowding. In this work, we explore the use of two of the most widespread crowding indices in an ED of an Italian national hospital, investigate their relationships and discuss their effectiveness.

Methods

In this study, two of the most widely used indices in the literature, the National Emergency Department Overcrowding Scale (NEDOCS) and the Emergency Department Working Index (EDWIN), were analysed to characterize overcrowding in the ED of A.O.R.N. “A. Cardarelli” of Naples, which included 1678 clinical cases. The measurement was taken every 15 minutes for a period of 7 days.

Results

The results showed consistency in the use of EDWIN and NEDOCS indices as measures of overcrowding, especially in severe overcrowding conditions. Indeed, in the examined case study, both EDWIN and NEDOCS showed very low rates of occurrence of severe overcrowding (2–3%). In contrast, regarding differences in the estimation of busy to overcrowded ED rates, the EDWIN index proved to be less sensitive in distinguishing these variations in the occupancy of the ED. Furthermore, within the target week considered in the study, the results show that, according to both EDWIN and NEDOCS, higher overcrowding rates occurred during the middle week rather than during the weekend. Finally, a low degree of correlation between the two indices was found.

Conclusions

The effectiveness of both EDWIN and NEDOCS in measuring ED crowding and overcrowding was investigated, and the main differences and relationships in the use of the indices are highlighted. While both indices are useful ED performance metrics, they are not always interchangeable, and their combined use could provide more details in understanding ED dynamics and possibly predicting future critical conditions, thus enhancing ED management.

Machine learning-based triage to identify low-severity patients with a short discharge length of stay in emergency department

BACKGROUND

Overcrowding in emergency departments (ED) is a critical problem worldwide, and streaming can alleviate crowding to improve patient flows. Among triage scales, patients labeled as "triage level 3" or "urgent" generally comprise the majority, but there is no uniform criterion for classifying low-severity patients in this diverse population. Our aim is to establish a machine learning model for prediction of low-severity patients with short discharge length of stay (DLOS) in ED.

METHODS

This was a retrospective study in the ED of China Medical University Hospital (CMUH) and Asia University Hospital (AUH) in Taiwan. Adult patients (aged over 20 years) with Taiwan Triage Acuity Scale level 3 were enrolled between 2018 and 2019. We used available information during triage to establish a machine learning model that can predict low-severity patients with short DLOS. To achieve this goal, we trained five models-CatBoost, XGBoost, decision tree, random forest, and logistic regression-by using large ED visit data and examined their performance in internal and external validation.

RESULTS

For internal validation in CMUH, 33,986 patients (75.9%) had a short DLOS (shorter than 4 h), and for external validation in AUH, there were 13,269 (82.7%) patients with short DLOS. The best prediction model was CatBoost in internal validation, and area under the receiver operating cha racteristic curve (AUC) was 0.755 (95% confidence interval (CI): 0.743-0.767). Under the same threshold, XGBoost yielded the best performance, with an AUC value of 0.761 (95% CI: 0.742- 0.765) in external validation.

CONCLUSIONS

This is the first study to establish a machine learning model by applying triage information alone for prediction of short DLOS in ED with both internal and external validation. In future work, the models could be developed as an assisting tool in real-time triage to identify low-severity patients as fast track candidates.

Analysis of Functional Layout in Emergency Departments (ED). Shedding Light on the Free Standing Emergency Department (FSED) Model

The ever-increasing number of hospital Emergency Department (ED) visits pose a challenge to the effective running of health systems in many countries globally and multiple strategies have been adopted over the years to tackle the plight. According to a systematic review of the available literature, of the numerous models of healthcare systems used to address the issue in western countries, the FSED Model has the greatest potential for reducing hospital ED overcrowding as it can reduce the additional load by diverting minor cases, freeing up space for more urgent cases. The aim of the study is to shed light on the Free Standing Emergency Department (FSED) model and compare it with the traditional Hospital Based Emergency Department (HBED) in international contexts. In this study, 23 papers have been collected in a literature review and the main features have been highlighted; 12 case studies have been analyzed from a layout point of view and data have been collected in terms of surfaces, functions, and flow patterns. The percentages of floor areas devoted to each function have been compared to define evolution strategies in the development of emergency healthcare models and analyses. The use of FSED models is an interesting way to face the overcrowding problem and a specific range for functional area layout has been identified. Further studies on its application in different contexts are encouraged.

Effect of a Boarding Restriction Protocol on Emergency Department Crowding

PURPOSE

Access block due to the lack of hospital beds causes crowding of emergency departments (ED). We initiated the "boarding restriction protocol" that limits the time of stay in the ED for patients awaiting hospitalization to 24 hours from arrival. The purpose of this study was to determine the effect of the boarding restriction protocol on ED crowding.

MATERIALS AND METHODS

The primary outcome was ED occupancy rate, which was calculated as the ratio of the number of occupying patients to the total number of ED beds. Time factors, such as length of stay (LOS), treatment time, and boarding time, were investigated.

RESULTS

The mean of the ED occupancy rate decreased from 1.532±0.432 prior to implementation of the protocol to 1.273±0.353 after (p<0.001). According to time series analysis, the absolute effect caused by the protocol was -0.189 (-0.277 to -0.110) (p=0.001). The proportion of patients with LOS exceeding 24 hours decreased from 7.6% to 4.0% (p<0.001). Among admitted patients, ED LOS decreased from 770.7 (421.4-1587.1) minutes to 630.2 (398.0-1156.8) minutes (p<0.001); treatment time increased from 319.6 (198.5-482.8) minutes to 344.7 (213.4-519.5) minutes (p<0.001); and boarding time decreased from 298.9 (109.5-1149.0) minutes to 204.1 (98.7-545.7) minutes (p<0.001). In pre-protocol period, boarding patients accumulated in the ED during the weekdays and resolved on Friday, but this pattern was alleviated in post-period.

CONCLUSION

The boarding restriction protocol was effective in alleviating ED crowding by reducing the accumulation of boarding patients in the ED during the weekdays.

A new approach for emergency department performance positioning: The quality-efficiency matrix

BACKGROUND

The crowding of emergency departments (EDs) is one of the major poor-quality factors for patients. Because of this, measuring ED performance in Healthcare Systems is a difficult but an important task needed to enhance quality and efficiency.

PURPOSE

(i) Development of a tool to observe and evaluate performance measurement, analysing two critical variables (quality and efficiency), verifying the change in performance due to the implementation of a new organizational model; (ii) the implementation of the tool in two EDs with comparable annual volumes of activity in the Italian context.

METHODS

A literature review on ED performance was conducted in order to identify acknowledged performance measurements used in this context that can be used in the development of a tool for the evaluation of EDs' performance. The goal is to have a matrix that is easily understood and that shows a simple relationship between quality and efficiency. This was possible by setting up a method that translates the ED annual performance data (in this case the data related to year 2018) into a graph with benchmarking purposes, also including an actual situation (AS-IS) view as compared to a TO-BE situation (i.e., before and after an organizational change occurred).

RESULTS

Two real EDs were compared and their results depicted; they can be easily related with each other to benchmark healthcare organisations. More precisely, a comparison can be used for two main tasks: - identifying different strategic areas and observing the positioning of a health organization at any given moment in time, seeing where it stands among its competitors in a matrix; - knowing how to best allocate available resources and where to divert investment. Results show that the tool depicts the situation of EDs, with a clear indication of how performance increases or decreases in the case of AS-IS and TO-BE evaluation, and also offers a quick understanding of the benchmarked EDs' situations.

PRACTICE IMPLICATIONS

The results can be shown on a graph that summarises the performance change for the AS-IS versus TO-BE conditions. This can be a useful tool for the ED and for the hospital decision makers, as it allows for an observation of performance by analysing two critical variables: the quality and the efficiency of the service provided. The former represents customer satisfaction, which in this work is the combination of two factors (i.e., appropriateness of assigning the triage code and patient satisfaction), and the latter represents the ED's efficiency in providing emergency care. The tool also helps the organizational changes to be easily evaluated.

Prevalence, Characteristics, and Outcomes of Emergency Department Discharge Among Patients With Sepsis

IMPORTANCE

Sepsis guidelines and research have focused on patients with sepsis who are admitted to the hospital, but the scope and implications of sepsis that is managed in an outpatient setting are largely unknown.

OBJECTIVE

To identify the prevalence, risk factors, practice variation, and outcomes for discharge to outpatient management of sepsis among patients presenting to the emergency department (ED).

DESIGN, SETTING, AND PARTICIPANTS

This cohort study was conducted at the EDs of 4 Utah hospitals, and data extraction and analysis were performed from 2017 to 2021. Participants were adult ED patients who presented to a participating ED from July 1, 2013, to December 31, 2016, and met sepsis criteria before departing the ED alive and not receiving hospice care.

EXPOSURES

Patient demographic and clinical characteristics, health system parameters, and ED attending physician.

MAIN OUTCOMES AND MEASURES

Information on ED disposition was obtained from electronic medical records, and 30-day mortality data were acquired from Utah state death records and the US Social Security Death Index. Factors associated with ED discharge rather than hospital admission were identified using penalized logistic regression. Variation in ED discharge rates between physicians was estimated after adjustment for potential confounders using generalized linear mixed models. Inverse probability of treatment weighting was used in the primary analysis to assess the noninferiority of outpatient management for 30-day mortality (noninferiority margin of 1.5%) while adjusting for multiple potential confounders.

RESULTS

Among 12 333 ED patients with sepsis (median [IQR] age, 62 [47-76] years; 7017 women [56.9%]) who were analyzed in the study, 1985 (16.1%) were discharged from the ED. After penalized regression, factors associated with ED discharge included age (adjusted odds ratio [aOR], 0.90 per 10-y increase; 95% CI, 0.87-0.93), arrival to ED by ambulance (aOR, 0.61; 95% CI, 0.52-0.71), organ failure severity (aOR, 0.58 per 1-point increase in the Sequential Organ Failure Assessment score; 95% CI, 0.54-0.60), and urinary tract (aOR, 4.56 [95% CI, 3.91-5.31] vs pneumonia), intra-abdominal (aOR, 0.51 [95% CI, 0.39-0.65] vs pneumonia), skin (aOR, 1.40 [95% CI, 1.14-1.72] vs pneumonia) or other source of infection (aOR, 1.67 [95% CI, 1.40-1.97] vs pneumonia). Among 89 ED attending physicians, adjusted ED discharge probability varied significantly (likelihood ratio test, P < .001), ranging from 8% to 40% for an average patient. The unadjusted 30-day mortality was lower in discharged patients than admitted patients (0.9% vs 8.3%; P < .001), and their adjusted 30-day mortality was noninferior (propensity-adjusted odds ratio, 0.21 [95% CI, 0.09-0.48]; adjusted risk difference, 5.8% [95% CI, 5.1%-6.5%]; P < .001). Alternative confounder adjustment strategies yielded odds ratios that ranged from 0.21 to 0.42.

CONCLUSIONS AND RELEVANCE

In this cohort study, discharge to outpatient treatment of patients who met sepsis criteria in the ED was more common than previously recognized and varied substantially between ED physicians, but it was not associated with higher mortality compared with hospital admission. Systematic, evidence-based strategies to optimize the triage of ED patients with sepsis are needed.

Wilhelms D. Differentiating properties of occupancy rate and workload to estimate crowding: A Swedish national cross-sectional study

BACKGROUND

Emergency department (ED) crowding causes increased patient morbidity and mortality. ED occupancy rate (OR; patients by treatment beds) is a common measure of crowding, but the comparability of ORs between EDs is unknown. The objective of this investigation was to investigate differences in ORs between EDs using staff-perceived workload as reference.

METHODS

This was a national cross-sectional study in Sweden. EDs provided data on census, treatment beds, staffing, and workload (1-6) at 5 time points. A baseline patient turnover was calculated as the average daily census by treatment beds, denoted turnover per treatment bed (TTB), for each ED. A census ratio (CR), current by daily census, was calculated to adjust for differences in the number of treatment beds.

RESULTS

Data were returned from 37 (51%) EDs. TTB varied considerably (mean = 4, standard deviation = 1.6; range, 2.1-9.2), and the OR was higher in EDs with TTB >4 compared with ≤4, 0.86 versus 0.43 (0.43; 95% confidence interval [CI], 0.27-0.59), but not workload, 2.75 versus 2.52 (0.23; 95% CI, -0.19 to 0.64). After adjusting for confounders, both TTB (k = -0.3; 95% CI, -0.49 to -0.14) and OR (k = 3.4; 95% CI, 1.76-5.03) affected workload. Correlation with workload was better for CR than for OR (r = 0.75 vs 0.60, respectively).

CONCLUSION

OR is affected by patient-to-treatment bed ratios that differ significantly between EDs and should be accounted for when measuring crowding. CR is not affected by baseline treatment beds and is a better comparable measure of crowding compared with OR in this national comparator study.

Measures of Emergency Department Crowding, a Systematic Review. How to Make Sense of a Long List

Emergency department (ED) crowding, a common and serious phenomenon in many countries, lacks standardized definition and measurement methods. This systematic review critically analyzes the most commonly studied ED crowding measures. We followed the Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) guidelines. We searched PubMed/Medline Database for all studies published in English from January 1st, 1990, until December 1st, 2020. We used the National Institute of Health (NIH) Quality Assessment Tool to grade the included studies. The initial search yielded 2293 titles and abstracts, of whom we thoroughly reviewed 109 studies, then, after adding seven additional, included 90 in the final analysis. We excluded simple surveys, reviews, opinions, case reports, and letters to the editors. We included relevant papers published in English from 1990 to 2020. We did not grade any study as poor and graded 18 as fair and 72 as good. Most studies were conducted in the USA. The most studied crowding measures were the ED occupancy, the ED length of stay, and the ED volume. The most heterogeneous crowding measures were the boarding time and number of boarders. Except for the National ED Overcrowding Scale (NEDOCS) and the Emergency Department Work Index (EDWIN) scores, the studied measures are easy to calculate and communicate. Quality of care was the most studied outcome. The EDWIN and NEDOCS had no studies with the outcome mortality. The ED length of stay had no studies with the outcome perception of care. ED crowding was often associated with worse outcomes: higher mortality in 45% of the studies, worse quality of care in 75%, and a worse perception of care in 100%. The ED occupancy, ED volume, and ED length of stay are easy to measure, calculate and communicate, are homogenous in their definition, and were the most studied measures.

Emergency department occupancy is useful as a simple real-time measure of crowding

INTRODUCTION

Emergency department (ED) crowding compromises patient outcomes. Existing crowding measures are complex and difficult to use in real-time. This study evaluated readily available single flow variables as crowding measures.

METHODS

Over 2 weeks in a tertiary Canadian ED, we recorded the following potential crowding measures during 168 consecutive two-hour study intervals: total ED patients (census), patients in beds, patients in waiting rooms, patients in treatment areas awaiting MD assessment; number of inpatients boarding, and ED occupancy. We also calculated four complex crowding scores-NEDOCS, EDWIN, ICMED, and a local modification of NEDOCS. We performed ROC analyses to assess the predictive validity of these measures against a reference standard of physician perception of crowding.

RESULTS

We gathered data for 144 (63.9%) of 168 study intervals. ED census correlated strongly with crowding (AUC = 0.82, 95% CI 0.76-0.89), as did ED occupancy (AUC = 0.75, 95% CI 0.66-0.83). Their performance was similar to NEDOCS (AUC = 0.80) and to the local modification of NEDOCS (AUC = 0.83).

CONCLUSION

ED occupancy as a single measure has similar predictive accuracy to complex crowding scores and is easily generalizable to diverse emergency departments. Real-time tracking of this simple indicator could be used to prompt investigation and implementation of crowding interventions.

Real-Time Measurement of Crowding in Pediatric Emergency Department: Derivation and Validation Using Consensual Perception of Crowding (SOTU-PED)

ABSTRACT

Our study aimed to develop and validate a real-time crowding composite scale for pediatric emergency department (PED). The study took place in one teaching PED for 2 months. The outcome was the perception of crowding evaluated by triage nurses and pediatricians on a 10-level Likert scale. Triage nurses evaluated crowding at each moment of a child's admission and pediatrician at each moment of a child's discharge. The outcome was the hourly mean of all evaluations of crowding (hourly crowding perception). For analysis, originally, we only selected hours during which more than 2 nurses and more than 2 pediatricians evaluated crowding and, moreover, during which evaluations were the most consensual. As predictors, we used hourly means of 10 objective crowding indicators previously selected as consensual in a published French national Delphi study and collected automatically in our software system. The model (SOTU-PED) was developed over a 1-month data set using a backward multivariable linear regression model. Then, we applied the SOTU-PED model on a 1-month validation data set. During the study period, 7341 children were admitted in the PED. The outcome was available for 1352/1392 hours, among which 639 were included in the analysis as "consensual hours." Five indicators were included in the final model, the SOTU-PED (R2 = 0.718). On the validation data set, the correlation between the outcome (perception of crowding) and the SOTU-PED was 0.824. To predict crowded hours (hourly crowding perception >5), the area under the curve was 0.957 (0.933-0.980). The positive and negative likelihood ratios were 8.16 (3.82-17.43) and 0.153 (0.111-0.223), respectively. Using a simple model, it is possible to estimate in real time how crowded a PED is.

Impact of Viral Seasonal Outbreaks on Crowding and Health Care Quality in Pediatric Emergency Departments

ABSTRACT

In pediatric emergency departments (PEDs), seasonal viral outbreaks are believed to be associated with an increase of workload, but no quantification of this impact has been published. A retrospective cross-sectional study aimed to measure this impact on crowding and health care quality in PED. The study was performed in 1 PED for 3 years. Visits related to bronchiolitis, influenza, and gastroenteritis were defined using discharge diagnoses. The daily epidemic load (DEL) was the proportion of visits related to one of these diagnoses. The daily mean of 8 crowding indicators (selected in a published Delphi study) was used. A total of 93,976 children were admitted (bronchiolitis, 2253; influenza, 1277; gastroenteritis, 7678). The mean DEL was 10.4% (maximum, 33.6%). The correlation between the DEL and each indicator was significant. The correlation was stronger for bronchiolitis (Pearson R from 0.171 for number of hospitalization to 0.358 for length of stay). Between the first and fourth quartiles of the DEL, a significant increase, between 50% (patients left without being seen) and 8% (patient physician ratio), of all the indicators was observed. In conclusion, seasonal viral outbreaks have a strong impact on crowding and quality of care. The evolution of "patients left without being seen" between the first and fourth quartiles of DEL could be used as an indicator reflecting the capacity of adaptation of an emergency department to outbreaks.

Hospital Occupancy and its Effect on Emergency Department Evaluation

STUDY OBJECTIVE

To examine whether hospital occupancy was associated with increased testing and treatment during emergency department (ED) evaluations, resulting in reduced admissions.

METHODS

We analyzed the electronic health records of an urban academic ED. We linked data from all ED visits from October 1, 2010, to May 29, 2015, with daily hospital occupancy (inpatients/total staffed beds). Outcome measures included the frequency of laboratory testing, advanced imaging, medication administration, and hospitalizations. We modeled each outcome using multivariable negative binomial or logistic regression, as appropriate, and examined their association with daily hospital occupancy quartiles, controlling for patient and visit characteristics. We calculated the adjusted outcome rates and relative changes at each daily hospital occupancy quartile using marginal estimating methods.

RESULTS

We included 270,434 ED visits with a mean patient age of 48.1 (standard deviation 19.8) years; 40.1% were female, 22.8% were non-Hispanic Black, and 51.5% were commercially insured. Hospital occupancy was not associated with differences in laboratory testing, advanced imaging, or medication administration. Compared with the first quartile, the third and fourth quartiles of daily hospital occupancy were associated with decreases of 1.5% (95% confidence interval [CI] -2.9 to -0.2; absolute change -0.6 percentage points [95% CI -1.2 to -0.1]) and 4.6% (95% CI -6.0 to -3.2; absolute change -1.9 percentage points [95% CI -2.5 to -1.3]) in hospitalizations, respectively.

CONCLUSION

The lack of association between hospital occupancy and laboratory testing, advanced imaging, and medication administration suggest that changes in ED testing or treatment did not facilitate the decrease in admissions during periods of high hospital occupancy.

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

Background

Emergency 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.

Methods

This 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.

Results

There 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).

Conclusion

The 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.

Forecasting emergency department hourly occupancy using time series analysis

STUDY OBJECTIVE

To develop a novel predictive model for emergency department (ED) hourly occupancy using readily available data at time of prediction with a time series analysis methodology.

METHODS

We performed a retrospective analysis of all ED visits from a large academic center during calendar year 2012 to predict ED hourly occupancy. Due to the time-of-day and day-of-week effects, a seasonal autoregressive integrated moving average with external regressor (SARIMAX) model was selected. For each hour of a day, a SARIMAX model was built to predict ED occupancy up to 4-h ahead. We compared the resulting model forecast accuracy and prediction intervals with previously studied time series forecasting methods.

RESULTS

The study population included 65,132 ED visits at a large academic medical center during the year 2012. All adult ED visits during the first 265 days were used as a training dataset, while the remaining ED visits comprised the testing dataset. A SARIMAX model performed best with external regressors of current ED occupancy, average department-wide ESI, and ED boarding total at predicting up to 4-h-ahead ED occupancy (Mean Square Error (MSE) of 16.20, and 64.47 for 1-hr- and 4-h- ahead occupancy, respectively). Our 24-SARIMAX model outperformed other popular time series forecasting techniques, including a 60% improvement in MSE over the commonly used rolling average method, while maintaining similar prediction intervals.

CONCLUSION

Accounting for current ED occupancy, average department-wide ESI, and boarding total, a 24-SARIMAX model was able to provide up to 4 h ahead predictions of ED occupancy with improved performance characteristics compared to other forecasting methods, including the rolling average. The prediction intervals generated by this method used data readily available in most EDs and suggest a promising new technique to forecast ED occupancy in real time.

Crowding is the strongest predictor of left without being seen risk in a pediatric emergency department

BACKGROUND

Emergency Department (ED) patients who leave without being seen (LWBS) are associated with adverse safety and medico-legal consequences. While LWBS risk has been previously tied to demographic and acuity related factors, there is limited research examining crowding-related risk in the pediatric setting. The primary objective of this study was to determine the association between LWBS risk and crowding, using the National Emergency Department Overcrowding Score (NEDOCS) and occupancy rate as crowding metrics.

METHODS

We performed a retrospective observational study on electronic health record (EHR) data from the ED of a quaternary care children's hospital and trauma center during the 14-month study period. NEDOCS and occupancy rate were calculated for 15-min windows and matched to patient arrival time. We leveraged multiple logistic regression analyses to demonstrate the relationship between patientlevel LWBS risk and each crowding metric, controlling for characteristics drawn from the pre-arrival state. We performed a chi-squared test to determine whether a difference existed between the receiver operating characteristic (ROC) curves in the two models. Finally, we executed a dominance analysis using McFadden's pseudo-R 2 to determine the relative importance of each crowding metric in the models.

RESULTS

A total of 54,890 patient encounters were studied, 1.22% of whom LWBS. The odds ratio for LWBS risk was 1.30 (95% CI 1.27-1.33) per 10-point increase in NEDOCS and 1.23 (95% CI 1.21-1.25). per 10% increase in occupancy rate. Area under the curve (AUC) was 86.9% for the NEDOCS model and 86.7% for the occupancy rate model. There was no statistically significant difference between the AUCs of the two models (p-value 0.27). Dominance analysis revealed that in each model, the most important variable studied was its respective crowding metric; NEDOCS accounted for 55.6% and occupancy rate accounted for 53.9% of predicted variance in LWBS.

CONCLUSION

Not only was ED overcrowding positively and significantly associated with individual LWBS risk, but it was the single most important factor that determined a patient's likelihood of LWBS in the pediatric ED. Because occupancy rate and NEDOCS are available in real time, each could serve as a monitor for individual LWBS risk in the pediatric ED.

Validation of the modified Skåne emergency department assessment of patient load (mSEAL) model for emergency department crowding and comparison with international models; an observational study

Background

Emergency Department crowding is associated with increased morbidity and mortality but no measure of crowding has been validated in Sweden. We have previously derived and internally validated the Skåne Emergency Department Assessment of Patient Load (SEAL) score as a measure of crowding in Emergency Departments (ED) in a large regional healthcare system in Sweden. Due to differences in electronic health records (EHRs) between health care systems in Sweden, all variables in the original SEAL-score could not be measured reliably nationally. We aimed to derive and validate a modified SEAL (mSEAL) model and to compare it with established international measures of crowding.

Methods

This was an observational cross sectional study at four EDs in Sweden. All clinical staff assessed their workload (1–6 where 6 is the highest workload) at 5 timepoints each day. We used linear regression with stepwise backward elimination on the original SEAL dataset to derive and internally validate the mSEAL score against staff workload assessments. We externally validated the mSEAL at four hospitals and compared it with the National Emergency Department Overcrowding Score (NEDOCS), the simplified International Crowding Measure in Emergency Department (sICMED), and Occupancy Rate. Area under the receiver operating curve (AuROC) and coefficient of determination was used to compare crowding models. Crowding was defined as an average workload of 4.5 or higher.

Results

The mSEAL score contains the variables Patient Hours and Time to physician and showed strong correlation with crowding in the derivation (r² = 0.47), internal validation (r² = 0.64 and 0.69) and in the external validation (r² = 0.48 to 0.60). AuROC scores for crowding in the external validation were 0.91, 0.90, 0.97 and 0.80 for mSEAL, Occupancy Rate, NEDOCS and sICMED respectively.

Conclusions

The mSEAL model can measure crowding based on workload in Swedish EDs with good discriminatory capacity and has the potential to systematically evaluate crowding and help policymakers and researchers target its causes and effects. In Swedish EDs, Occupancy Rate and NEDOCS are good alternatives to measure crowding based on workload.

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.

Does Telemedicine Reduce Emergency Room Congestion? Evidence from New York State

Overcrowding in emergency rooms (ERs) is a common yet nagging problem. It not only is costly for hospitals but also compromises care quality and patient experience. Our paper provides solid evidence that telemedicine can significantly improve ER care delivery, especially in the presence of demand and supply fluctuations. We believe such findings are critical for ERs, due to the special setting of unscheduled arrivals leading to high unpredictability of patient traffic. Additional evidence suggests that the efficiency gained from telemedicine does not come at the expense of lower care quality or higher medical expenditure, which points to telemedicine as a feasible solution to the ER overcrowding problem. For healthcare practitioners, our paper highlights the general applicability of telemedicine through the “hub and spoke” architecture. Besides increasing patients’ access to more immediate care from specialists who were not available otherwise, telemedicine enables flexible resource allocation for any hospitals, regardless of where hospitals are located. Our research also provides ground for policymakers to incentivize hospitals to adopt telemedicine in ER, which we believe is critical given the relatively low adoption rate, the lack of direct evidence on its effectiveness, and the current inflexibility of reimbursement policies regarding the application of ER telemedicine.

Prevalence of crowding, boarding and staffing levels in Swedish emergency departments - a National Cross Sectional Study

Background

Emergency Department (ED) crowding occurs when demand for care exceeds the available resources. Crowding has been associated with decreased quality of care and increased mortality, but the prevalence on a national level is unknown in most countries.

Method

We performed a national, cross-sectional study on staffing levels, staff workload, occupancy rate and patients waiting for an in-hospital bed (boarding) at five time points during 24 h in Swedish EDs.

Results

Complete data were collected from 37 (51% of all) EDs in Sweden. High occupancy rate indicated crowding at 12 hospitals (37.5%) at 31 out of 170 (18.2%) time points. Mean workload (measured on a scale from 1, no workload to 6, very high workload) was moderate at 2.65 (±1.25). Boarding was more prevalent in academic EDs than rural EDs (median 3 vs 0). There were an average of 2.6, 4.6 and 3.2 patients per registered nurse, enrolled nurse and physician, respectively.

Conclusion

ED crowding based on occupancy rate was prevalent on a national level in Sweden and comparable with international data. Staff workload, boarding and patient to staff ratios were generally lower than previously described.

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

Background

Emergency 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.

Methods

A 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.

Results

During 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.

Conclusion

Maximum 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.

Boarding is Associated with Reduced Emergency Department Efficiency that is not Mitigated by a Provider in Triage

INTRODUCTION

Boarding of patients in the emergency department (ED) is associated with decreased ED efficiency. The provider-in-triage (PIT) model has been shown to improve ED throughput, but it is unclear how these improvements are affected by boarding. We sought to assess the effects of boarding on ED throughput and whether implementation of a PIT model mitigated those effects.

METHODS

We performed a multi-site retrospective review of 955 days of ED operations data at a tertiary care academic ED (AED) and a high-volume community ED (CED) before and after implementation of PIT. Key outcome variables were door to provider time (D2P), total length of stay of discharged patients (LOSD), and boarding time (admit request to ED departure [A2D]).

RESULTS

Implementation of PIT was associated with a decrease in median D2P by 22 minutes or 43% at the AED (p < 0.01), and 18 minutes (31%) at the CED (p < 0.01). LOSD also decreased by 19 minutes (5.9%) at the AED and 8 minutes (3.3%) at the CED (p<0.01). After adjusting for variations in daily census, the effect of boarding (A2D) on D2P and LOSD was unchanged, despite the implementation of PIT. At the AED, 7.7 minutes of boarding increased median D2P by one additional minute (p < 0.01), and every four minutes of boarding increased median LOSD by one minute (p < 0.01). At the CED, 7.1 minutes of boarding added one additional minute to D2P (p < 0.01), and 4.8 minutes of boarding added one minute to median LOSD (p < 0.01).

CONCLUSION

In this retrospective, observational multicenter study, ED operational efficiency was improved with the implementation of a PIT model but worsened with boarding. The PIT model was unable to mitigate any of the effects of boarding. This suggests that PIT is associated with increased efficiency of ED intake and throughput, but boarding continues to have the same effect on ED efficiency regardless of upstream efficiency measures that may be designed to minimize its impact.

Trajectories of posttraumatic stress in patients with confirmed and rule-out acute coronary syndrome

Many patients evaluated in the emergency department (ED) for acute coronary syndrome (ACS) develop posttraumatic stress symptoms (PTSS), but little is known about symptom trajectories over time. We estimated longitudinal trajectories of PTSS from ED to 1 year after evaluation for suspected ACS (N = 1000), and the effect of threat perceptions and discharge diagnosis. Participants reported on threat perceptions in the ED, ongoing cardiac threat at 1 month, and PTSS at 1, 6, and 12 months. Latent growth mixture modeling identified 3 PTSS trajectories over 1 year: Resilient (81.75%), Chronic-Worsening (13.69%), and Acute-Recovering (4.56%). Chronic-Worsening and Acute-Recovering classes reported significantly higher ED and cardiac threat perceptions than Resilient class. Discharge diagnosis did not differ (χ²(2) = 2.93, p = .231). PTSS are common following evaluation for suspected ACS, and trajectories vary, but targeting threat perceptions may reduce PTSS and improve clinical course, whether or not patients are ultimately diagnosed with ACS.

Estrategias para la medición y el manejo de la sobreocupación de los servicios de urgencias de adultos en instituciones de alta complejidad con altos volúmenes de consulta. Revisión de la literatura

La sobreocupación de los servicios de urgencias es un problema global que cada vez afecta más las instituciones de salud que atienden pacientes de mediana y alta complejidad, haciendo que estos permanezcan más tiempo en una sala de espera con la consiguiente demora en los tiempos de atención, bajo nivel de satisfacción de los usuarios, retraso en la toma de ayudas diagnósticas, retrasos al definir altas del servicio y favorecimiento de complicaciones médicas, entre otros. Para mejorar esta situación se han desarrollado estrategias como la creación de unidades de observación, unidades fast track o asignación de citas prioritarias para los pacientes que no requieren una atención urgente, de modo adicional el triaje, los exámenes point of care y la vinculación de especialistas en medicina de urgencias. Todo esto con el fin de mejorar la calidad de la atención de los pacientes, evitar que se presenten eventos adversos durante su proceso y disminuir la sobreocupación del servicio.

The Application of GSCM in Eliminating Healthcare Waste: Hospital EDC as an Example

Eliminating unnecessary healthcare waste in hospitals and providing better healthcare quality are the core issues of green supply chain management (GSCM). Hence, this study used a hospital's emergency department crowding (EDC) problem to illustrate how to establish an emergency medicine service (EMS) simulation system to obtain a robust parameters setting for solving hospitals' EDC and waste problems, thereby increasing healthcare quality. Inappropriate resource allocation results in more serious EDC; more serious EDC results in increasing operating costs. Therefore, in the healthcare system, waste includes inappropriate costs and inappropriate resource allocation. The EMS of a medical center in central Taiwan was the object of the study. In this study, the dynamic Taguchi method was used to set the signal factor, noise factor, and control factors to simulate the EMS system to obtain the optimal parameters setting. The performance was set to Emergency Department Work Index (EDWINC) and system time (waiting time and service time) per patient. The signal factor was set to the number of physicians; the noise factor was set to patient arrival rate; the control factors included persuading Triage 4 and Triage 5 outpatients, checkup process, bed occupation rate in the emergency department (ED), and medical checkup sequence for Triage 4 and Triage 5 patients. This study makes two significant contributions. First, the study introduces the GSCM concept to the healthcare setting to bring green innovation to hospitals. Hospital administrators may hence design better GSCM activities to facilitate healthcare processes to provide better healthcare outcomes. Second, the study applied the dynamic Taguchi method to the EMS and neural network (NN) to construct a computational model revealing the cause (factors) and effect (performances) relationship. In addition, the genetic algorithm (GA), a solution method, was used to obtain the optimal parameters setting of the EDC in Taiwan. Hence, after obtaining the solutions, the unnecessary waste in EDC-inappropriate costs and inappropriate resource allocation-is reduced.

Ambulance diversions following public hospital emergency department closures

OBJECTIVE

To examine whether hospitals are more likely to temporarily close their emergency departments (EDs) to ambulances (through ambulance diversions) if neighboring diverting hospitals are public vs private.

DATA SOURCES/STUDY SETTING

Ambulance diversion logs for California hospitals, discharge data, and hospital characteristics data from California's Office of Statewide Health Planning and Development and the American Hospital Association (2007).

STUDY DESIGN

We match public and private (nonprofit or for-profit) hospitals by distance and size. We use random-effects models examining diversion probability and timing of private hospitals following diversions by neighboring public vs matched private hospitals.

DATA COLLECTION/EXTRACTION METHODS

N/A.

PRINCIPAL FINDINGS

Hospitals are 3.6 percent more likely to declare diversions if neighboring diverting hospitals are public vs private (P < 0.001). Hospitals declaring diversions have lower ED occupancy (P < 0.001) after neighboring public (vs private) hospitals divert. Hospitals have 4.2 percent shorter diversions if neighboring diverting hospitals are public vs private (P < 0.001). When the neighboring hospital ends its diversion first, hospitals terminate diversions 4.2 percent sooner if the neighboring hospital is public vs private (P = 0.022).

CONCLUSIONS

Sample hospitals respond differently to diversions by neighboring public (vs private) hospitals, suggesting that these hospitals might be strategically declaring ambulance diversions to avoid treating low-paying patients served by public hospitals.

Evaluating the impact of emergency department crowding on disposition patterns and outcomes of discharged patients

BACKGROUND

Crowding is a major challenge faced by EDs and is associated with poor outcomes.

OBJECTIVES

Determine the effect of high ED occupancy on disposition decisions, return ED visits, and hospitalizations.

METHODS

We conducted a retrospective analysis of electronic health records of patients evaluated at an adult, urban, and academic ED over 20 months between the years 2012 and 2014. Using a logistic regression model predicting admission, we obtained estimates of the effect of high occupancy on admission disposition, adjusted for key covariates. We then stratified the analysis based on the presence or absence of high boarder patient counts.

RESULTS

Disposition decisions during a high occupancy hour decreased the odds of admission (OR = 0.93, 95% CI: [0.89, 0.98]). Among those who were not admitted, high occupancy was not associated with increased odds of return in the combined (OR = 0.94, 95% CI: [0.87, 1.02]), with-boarders (OR = 0.96, 95% CI: [0.86, 1.09]), and no-boarders samples (OR = 0.93, 95% CI: [0.83, 1.04]). Among those who were not admitted and who did return within 14 days, disposition during a high occupancy hour on the initial ED visit was not associated with a significant increased odds of hospitalization in the combined (OR = 1.04, 95% CI: [0.87, 1.24]), the with-boarders (OR = 1.12, 95% CI: [0.87, 1.44]), and the no-boarders samples (OR = 0.98, 95% CI: [0.77, 1.24]).

CONCLUSION

ED crowding was associated with reduced likelihood of hospitalization without increased likelihood of 2-week return ED visit or hospitalization. Furthermore, high occupancy disposition hours with high boarder patient counts were associated with decreased likelihood of hospitalization.

The Impact of Cardiac-induced Post-traumatic Stress Disorder Symptoms on Cardiovascular Outcomes: Design and Rationale of the Prospective Observational Reactions to Acute Care and Hospitalizations (ReACH) Study

Aims:

As many as 1 in 8 acute coronary syndrome (ACS) patients develop posttraumatic stress disorder (PTSD) due to the ACS, and ACS-induced PTSD may increase secondary cardiovascular disease (CVD) risk. However, prior studies have been small and underpowered to test plausible behavioral or biological mechanisms of the hypothesized PTSD-secondary CVD risk association. In this paper, we describe the design and methods of a large prospective observational cohort study to estimate the prognostic significance of ACS-induced PTSD, mechanisms for its association with CVD risk, and emergency department (ED) factors that may increase PTSD risk, in a cohort of patients evaluated for acute coronary syndrome (ACS) in the ED of a large, urban academic medical center.

Methods:

The Reactions to Acute Care and Hospitalization (ReACH) study follows 1,741 racially, ethnically, and socioeconomically diverse patients initially presenting to the ED with ACS symptoms. Psychosocial factors are assessed at baseline. Medication adherence is monitored by electronic pill bottle (eCAP). Participants are contacted by phone at 1-, 6-, and 12-months post-hospitalization to assess PTSD symptoms, hospital readmission, and recurrent CVD events/mortality (proactively searched and confirmed by medical records).

Conclusion:

This study will provide the most accurate estimates to date of PTSD’s association with recurrent CVD events and mortality and will test whether medication adherence mediates that association. Further, it will provide estimates of the contribution of ED and hospital factors to PTSD risk in ACS patients. If our hypotheses are supported, we will have identified PTSD as a novel target for secondary risk reduction.

A challenge for psychocardiology: Addressing the causes and consequences of patients' perceptions of enduring somatic threat

The enduring somatic threat (EST) model of posttraumatic stress disorder (PTSD) due to life-threatening medical events suggests that PTSD-like symptoms represent patients' sensitization to cues of ongoing threat in the body. In this article, we review research on the prevalence and consequences of such reactions in cardiovascular disease patients, discuss early tests of the EST model, and then report a new test of the EST model in 143 patients enrolled during their first acute coronary syndrome (ACS; i.e., non-ST elevation myocardial infarction or unstable angina-colloquially, "heart attack"). Invasive coronary revascularization procedures are commonly used to reduce secondary ACS risk and may reduce patients' EST, as revascularized patients often report being "cured." We assessed ACS patients' initial threat perceptions during emergency department (ED) evaluation and followed them for 1 month for PTSD symptoms (specific for ACS, by telephone). We compared PTSD symptoms in participants who were revascularized (n = 65), catheterized but not revascularized (n = 35), and medically managed (n = 43). PTSD symptoms were lower for revascularized versus medically managed participants (B = -5.32, 95% confidence interval [-9.77, -0.87]), t(98.19) = -2.37, p = .020. In a multiple regression model adjusted for clinical and psychosocial covariates, the interaction of threat perception in the ED and ACS management group was significant (greater ED threat predicted greater 1-month PTSD symptoms only in medically managed participants). These findings offer further support for the EST model and suggest that psychological interventions to preempt patients' development of EST should be considered in the hospital. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Emergency Department Crowding Is Associated With Delayed Antibiotics for Sepsis

STUDY OBJECTIVE

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.

METHODS

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 to licensed ED beds. We defined ED overcrowding as an ED occupancy rate greater than or equal to 1. We used multivariable regression to measure 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.

RESULTS

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.

CONCLUSION

ED crowding was associated with increased sepsis antibiotic delay. Hospitals must devise strategies to optimize sepsis antibiotic administration during periods of ED crowding.

Predictors of Admission in Adult Unscheduled Return Visits to the Emergency Department

Introduction

The 72-hour unscheduled return visit (URV) of an emergency department (ED) patient is often used as a key performance indicator in emergency medicine. We sought to determine if URVs with admission to hospital (URVA) represent a distinct subgroup compared to unscheduled return visits with no admission (URVNA).

Methods

We performed a retrospective cohort study of all 72-hour URVs in adults across 10 EDs in the Edmonton Zone (EZ) over a one-year period (January 1, 2015 - December 31, 2015) using ED information-system data. URVA and URVNA populations were compared, and a multivariable analysis identified predictors of URVA.

Results

Analysis of 40,870 total URV records, including 3,363 URVAs, revealed predictors of URVA on the index visit including older age (>65 yrs, odds ratio [OR] 3.6), higher disease acuity (Canadian Emergency Department Triage and Acuity Scale [CTAS] 2, OR 2.6), gastrointestinal presenting complaint (OR 2.2), presenting to a referral hospital (OR 1.4), fewer annual ED visits (<4 visits, OR 2.0), and more hours spent in the ED (>12 hours, OR 2.0). A decrease in CTAS score (increase in disease acuity) upon return visit also increased the risk of admission (-1 CTAS level, OR 2.6). ED crowding at the index visit, as indicated by occupancy level, was not a predictor.

Conclusion

We demonstrate that URVA patients comprise a distinct subgroup of 72-hour URV patients. Risk factors for URVA are present at the index visit suggesting that patients at high risk for URVA may be identifiable prior to admission.

Significant changes in emergency department length of stay and case mix over eight years at a large Swedish University Hospital

OBJECTIVE

Describe the longitudinal development of crowding and patient/emergency department (ED) characteristics at a Swedish University Hospital.

METHODS

A retrospective longitudinal registry study based on all ED visits with adult patients during 2009-2016 (N = 1,063,806). Patient characteristics and measures of ED crowding (ED occupancy ratio, length-of-stay [LOS], patients/clinician's ratios) were extracted from the hospital's electronic health record. Non-parametric analyses were conducted.

RESULTS

The proportion of unstable patients (triage level 1-2) increased while the proportion of admitted patients decreased. All crowding variables were stable, except for LOS, which increased by 9 min/visit/year (95% CI: 8.8-9.1). LOS for visits by patients ≥ 80 years increased more compared to those 18-79 (248 min vs. 190 min, p < 0.001). Unstable patients increased their median LOS compared to stable patients (triage level 3-5). LOS for discharged patients increased with an average of 7.7 min/year (95% CI: 7.5-7.9) compared to 15.5 min/year (95% CI: 15.2-15.8) for those being admitted.

CONCLUSION

Fewer admissions, despite an increase of unstable patients, is likely related to lack of in-hospital beds and contributes to ED crowding. The increase in median ED LOS, especially for patients in the subgroups unstable, ≥80 years and admitted to in-hospital care reflects this problem.

Role of ED crowding relative to trauma quality care in a Level 1 Trauma Center

OBJECTIVE

Trauma Quality Improvement Program participation among all trauma centers has shown to improve patient outcomes. We aim to identify trauma quality events occurring during the Emergency Department (ED) phase of care.

METHODS

This is a single-center observational study using consecutively registered data in local trauma registry (Jan 1, 2016-Jun 30, 2017). Four ED crowding scores as determined by four different crowding estimation tools were assigned to each enrolled patient upon arrival to the ED. Patient related (age, gender, race, severity of illness, ED disposition), system related (crowding, night shift, ED LOS), and provider related risk factors were analyzed in a multivariate logistic regression model to determine associations relative to ED quality events.

RESULTS

Total 5160 cases were enrolled among which, 605 cases were deemed ED quality improvement (QI) cases and 457 cases were ED provider related. Similar percentages of ED QI cases (10-12%) occurred across the ED crowding status range. No significant difference was appreciated in terms of predictability of ED QI cases relative to different crowding status after adjustment for potential confounders. However, an adjusted odds ratio of 1.64 (95% CI, 1.17-2.30, p < 0.01) regarding ED LOS ≥2 h predictive of ED related quality issues was noted when analyzed using multivariate logistic regression.

CONCLUSION

Provider related issues are a common contributor to undesirable outcomes in trauma care. ED crowding lacks significant association with poor trauma quality care. Prolonged ED LOS (≥2 h) appears to be linked with unfavorable outcomes in ED trauma care.

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.

Making Improvements in the ED: Does ED Busyness Affect Time to Antibiotics in Febrile Pediatric Oncology Patients Presenting to the Emergency Department?

OBJECTIVES

Febrile neutropenic pediatric patients are at heightened risk for serious bacterial infections, and rapid antibiotic administration (in <60 minutes) improves survival. Our objectives were to reduce the time-to-antibiotic (TTA) administration and to evaluate the effect of overall emergency department (ED) busyness on TTA.

METHODS

This study was a quality improvement initiative with retrospective chart review to reduce TTA in febrile children with underlying diagnosis of cancer or hematologic immunodeficiency who visited the pediatric ED. A multidisciplinary clinical practice guideline (CPG) was implemented to improve TTA. The CPG's main focus was delivery of antibiotics before availability of laboratory data. We collected data on TTA during baseline and intervention periods. Concurrent patient arrivals to the ED per hour served as a proxy of busyness. Time to antibiotic was compared with the number of concurrent arrivals per hour. Analyses included scatter plot and regression analysis.

RESULTS

There were 253 visits from October 1, 2010 to March 30, 2012. Median TTA administration dropped from 207 to 89 minutes (P < 0.001). Eight months after completing all intervention periods, the median had dropped again to 44 minutes with 70% of patients receiving antibiotics within 60 minutes of ED arrival. There was no correlation between concurrent patient arrivals and TTA administration during the historical or intervention periods.

CONCLUSIONS

Implementation of a CPG and process improvements significantly reduced median TTA administration. Total patient arrivals per hour as a proxy of ED crowding did not affect TTA administration. Our data suggest that positive improvements in clinical care can be successful despite fluctuations in ED patient volume.

Reduction in laboratory turnaround time decreases emergency room length of stay

Objective

Laboratory tests are an important contributor to treatment decisions in the emergency department (ED). Rapid turnaround of laboratory tests can optimize ED throughout by reducing the length of stay (LOS) and improving patient outcomes. Despite evidence supporting the effect of shorter turnaround time (TAT) on LOS and outcomes, there is still a lack of large retrospective studies examining these associations. Here, we evaluated the effect of a reduction in laboratory TAT on ED LOS using retrospective analysis of Electronic Health Records (EHR).

Materials and methods

Retrospective analysis of ED encounters from a large, US-based, de-identified EHR database and a separate analysis of ED encounters from the EHR of an ED at a top-tier tertiary care center were performed. Additionally, an efficiency model calculating the cumulative potential LOS time savings and resulting financial opportunity due to laboratory TAT reduction was created, assuming other factors affecting LOS are constant.

Results

Multivariate regression analysis of patients from the multisite study showed that a 1-minute decrease in laboratory TAT was associated with 0.50 minutes of decrease in LOS. The single-site analysis confirmed our findings from the multisite analysis that a positive correlation between laboratory TAT and ED LOS exists in the ED population as a whole, as well as across different patient acuity levels. In addition, based on the calculations from the efficiency model, for a 5-, 10- and 15-minute TAT reduction, the single-site ED can potentially admit a total of 127, 256 and 386 additional patients, respectively, annually.

Conclusion

A positive correlation between laboratory TAT and ED LOS was observed in a broad patient population and across distinct acuity levels.

Code Help: Can This Unique State Regulatory Intervention Improve Emergency Department Crowding?

Introduction

Emergency department (ED) crowding adversely affects multiple facets of high-quality care. The Commonwealth of Massachusetts mandates specific, hospital action plans to reduce ED boarding via a mechanism termed "Code Help." Because implementation appears inconsistent even when hospital conditions should have triggered its activation, we hypothesized that compliance with the Code Help policy would be associated with reduction in ED boarding time and total ED length of stay (LOS) for admitted patients, compared to patients seen when the Code Help policy was not followed.

Methods

This was a retrospective analysis of data collected from electronic, patient-care, timestamp events and from a prospective Code Help registry for consecutive adult patients admitted from the ED at a single academic center during a 15-month period. For each patient, we determined whether the concurrent hospital status complied with the Code Help policy or violated it at the time of admission decision. We then compared ED boarding time and overall ED LOS for patients cared for during periods of Code Help policy compliance and during periods of Code Help policy violation, both with reference to patients cared for during normal operations.

Results

Of 89,587 adult patients who presented to the ED during the study period, 24,017 (26.8%) were admitted to an acute care or critical care bed. Boarding time ranged from zero to 67 hours 30 minutes (median 4 hours 31 minutes). Total ED LOS for admitted patients ranged from 11 minutes to 85 hours 25 minutes (median nine hours). Patients admitted during periods of Code Help policy violation experienced significantly longer boarding times (median 20 minutes longer) and total ED LOS (median 46 minutes longer), compared to patients admitted under normal operations. However, patients admitted during Code Help policy compliance did not experience a significant increase in either metric, compared to normal operations.

Conclusion

In this single-center experience, implementation of the Massachusetts Code Help regulation was associated with reduced ED boarding time and ED LOS when the policy was consistently followed, but there were adverse effects on both metrics during violations of the policy.

Depressive Symptoms and Perceptions of ED Care in Patients Evaluated for Acute Coronary Syndrome

INTRODUCTION

Posttraumatic stress disorder (PTSD) develops in 1 out of 8 survivors of acute coronary syndrome (ACS) events, and these persons have a doubling of risk for recurrent ACS and mortality. Overcrowding in the emergency department during ACS evaluation has been associated with increased risk for PTSD, and depressed patients have been found to be particularly vulnerable. Little is known about the mechanisms by which overcrowding increases PTSD risk in depressed patients. Our aim was to evaluate one possible mechanism, patient perception of crowding and care, in depressed and nondepressed ED patients evaluated for ACS.

METHODS

We enrolled 912 participants in the REactions to Acute Care and Hospitalization study, an ongoing observational cohort study assessing patients evaluated for ACS. Participants completed the Emergency Department Perceptions questionnaire. Depressive symptoms were screened using the Personal Health Questionnaire Depression Scale. Objective ED crowding was calculated using the Emergency Department Work Index (EDWIN).

RESULTS

EDWIN scores did not significantly differ between groups. Although perceptions of ED crowding did not differ between groups, depressed patients perceived the emergency department as more stressful [t = 4.45, P < .001] and perceived poorer care [t = 3.03, P = .003]. Multiple regression modeling found a significant interaction between EDWIN scores and depression, predicting participants' perception of stress in the emergency department (F[7,904] = 7.93, P < .001).

DISCUSSION

We found that depressed patients experienced the emergency department as more stressful as objectively measured crowding increased. Our study highlights the complex interplay between cardiovascular disease and mental health in impacting patient health outcomes in the emergency department.

Robustness and Effectiveness of the Triage System in the Pediatric Context

BACKGROUND

The increasing use of emergency departments (EDs) potentially compromises their effectiveness and quality. The evaluation of the performance of the triage code system in a pediatric context is important because waiting time affects the quality of care for acutely ill patients.

OBJECTIVE

In this study, we aimed to assess the effectiveness and robustness of the triage code system in a pediatric context and identify the determinants of waiting times for urgent and non-urgent patients.

METHODS

Data regarding 37,767 pediatric patients who accessed the ED of a major Italian pediatric hospital in 2015 were investigated in order to study patient numbers and waiting times. The determinants of waiting times for urgent and non-urgent patients, as well as variables referring to the "supply side," such as periods of staff shortage, were analyzed using a survival analysis framework.

RESULTS

For urgent patients, the waiting time between triage and the first physician assessment is generally below the standard threshold of 15 min and this is not affected by the number of non-urgent patients waiting for care. Conversely, the waiting time for non-urgent patients is affected by ED flow, periods of staff shortage, and non-clinical variables (age and nationality).

CONCLUSION

Our results suggest that the triage level assignation system is effective in terms of safety for urgent patients. The current ED organization adequately fulfills its primary goal of providing healthcare for acutely ill patients.