Decreased health care quality associated with emergency department overcrowding

Avoidable visits to the paediatric emergency department: associated factors and lessons learned from the pandemic

PURPOSE

The main goal of this study is to identify the associated factors with avoidable admissions in ED, comparing pre-COVID and COVID periods.

METHODS

This was retrospective study that took place in a Paediatric Emergency Department of a metropolitan, university-affiliated hospital in Portugal. All visits to paediatric emergency department between 2014 and 2020 were considered.

RESULTS

There was a decrease of 7.2% points in avoidable visits between pre-COVID and COVID periods. Considering both periods, this study identifies older ages, being admitted to the paediatric emergency department between 4 and 7 a.m., referral and having visited the emergency department previously within 72 h as major factors associated with a reduced likelihood for avoidable visits. On the other hand, it identifies an increased likelihood of avoidable visits in the 3 to 5 years old age group, visits that occurred during the Summer and visits that occurred between 8 and 11 p.m. When considering what changed between pre-COVID and COVID periods, while having visited the paediatric emergency department 72 h prior made it less likely for the patient to be an avoidable visit during the pandemic period, this tendency has inverted, making it more likely for return visits to be avoidable.

CONCLUSIONS

The relatively low decrease in avoidable visits' ratios between pre-COVID and COVID periods, associated with the similar distribution of attendance during the day and lower odds ratio of avoidable visits during periods when primary care is available, suggests that avoidable visits are a chronical problem of the National Health system's structure and its usage, not having a single factor nor a combination of factors as a driving force. Nevertheless, this study identified several factors associated with avoidable visits to the emergency department. Therefore, it can aid policy makers to create targeted interventions to mitigate this problem.

Machine learning outperforms the Canadian Triage and Acuity Scale (CTAS) in predicting need for early critical care

STUDY OBJECTIVE

This study investigates the potential to improve emergency department (ED) triage using machine learning models by comparing their predictive performance with the Canadian Triage Acuity Scale (CTAS) in identifying the need for critical care within 12 h of ED arrival.

METHODS

Three machine learning models (LASSO regression, gradient-boosted trees, and a deep learning model with embeddings) were developed using retrospective data from 670,841 ED visits to the Jewish General Hospital from June 2012 to Jan 2021. The model outcome was the need for critical care within the first 12 h of ED arrival. Metrics, including the areas under the receiver-operator characteristic curve (ROC) and precision-recall curve (PRC) were used for performance evaluation. Shapley additive explanation scores were used to compare predictor importance.

RESULTS

The three machine learning models (deep learning, gradient-boosted trees and LASSO regression) had areas under the ROC of 0.926 ± 0.003, 0.912 ± 0.003 and 0.892 ± 0.004 respectively, and areas under the PRC of 0.27 ± 0.01, 0.24 ± 0.01 and 0.23 ± 0.01 respectively. In comparison, the CTAS score had an area under the ROC of 0.804 ± 0.006 and under the PRC of 0.11 ± 0.01. The predictors of most importance were similar between the models.

CONCLUSIONS

Machine learning models outperformed CTAS in identifying, at the point of ED triage, patients likely to need early critical care. If validated in future studies, machine learning models such as the ones developed here may be considered for incorporation in future revisions of the CTAS triage algorithm, potentially improving discrimination and reliability.

Clinical support system for triage based on federated learning for the Korea triage and acuity scale

Background and aims

This study developed a clinical support system based on federated learning to predict the need for a revised Korea Triage Acuity Scale (KTAS) to facilitate triage.

Methods

This was a retrospective study that used data from 11,952,887 patients in the Korean National Emergency Department Information System (NEDIS) from 2016 to 2018 for model development. Separate cohorts were created based on the emergency medical center level in the NEDIS: regional emergency medical center (REMC), local emergency medical center (LEMC), and local emergency medical institution (LEMI). External and temporal validation used data from emergency department (ED) of the study site from 2019 to 2021. Patient features obtained during the triage process and the initial KTAS scores were used to develop the prediction model. Federated learning was used to rectify the disparity in data quality between EDs. The patient's demographic information, vital signs in triage, mental status, arrival information, and initial KTAS were included in the input feature.

Results

3,626,154 patients' visits were included in the regional emergency medical center cohort; 8,278,081 patients' visits were included in the local emergency medical center cohort; and 48,652 patients' visits were included in the local emergency medical institution cohort. The study site cohort, which is used for external and temporal validation, included 135,780 patients visits. Among the patients in the REMC and study site cohorts, KTAS level 3 patients accounted for the highest proportion at 42.4% and 45.1%, respectively, whereas in the LEMC and LEMI cohorts, KTAS level 4 patients accounted for the highest proportion. The area under the receiver operating characteristic curve for the prediction model was 0.786, 0.750, and 0.770 in the external and temporal validation. Patients with revised KTAS scores had a higher admission rate and ED mortality rate than those with unaltered KTAS scores.

Conclusions

This novel system might accurately predict the likelihood of KTAS acuity revision and support clinician-based triage.

Impact of iodinated contrast allergies on emergency department operations

OBJECTIVES

Adverse reactions to intravenous (IV) iodinated contrast media are classified by the American College of Radiology (ACR) Manual on Contrast Media as either allergic-like (ALR) or physiologic (PR). Premedication may be beneficial for patients who have prior documented mild or moderate ALR. We sought to perform a retrospective analysis of patients who received computed tomography (CT) imaging in our emergency department (ED) to establish whether listing of an iodinated contrast media allergy results in a delay in care, increases the use of non-contrast studies, and to quantify the incidence of listing iodinated contrast allergies which do not necessitate premedication.

METHODS

We performed a retrospective analysis of CT scans performed in our academic medical center ED during a 6-month period. There were 12,737 unique patients of whom 454 patients had a listed iodinated contrast allergy. Of these, 106 received IV contrast and were categorized as to whether premedication was necessary. Descriptive statistics were used to evaluate patient demographics, clinical characteristics, and operational outcomes. A multivariate linear regression model was used to predict time from order to start (OTS time) of CT imaging while controlling for co-variates.

RESULTS

Non-allergic patients underwent contrast-enhanced CT imaging at a significantly higher rate than allergic patients (45.9% vs. 23.3%, p < 0.01). The OTS time for allergic patients who underwent contrast-enhanced CT imaging was 360 min and significantly longer than the OTS time for non-allergic patients who underwent contrast-enhanced CT imaging (118 min, p < 0.001). Of the 106 allergic patients who underwent contrast-enhanced CT imaging, 27 (25.5%) did not meet ACR criteria for necessitating premedication. The average OTS time for these 27 patients was 296 min, significantly longer than the OTS for non-allergic patients (118 min, p < 0.01) and did not differ from the OTS time for the 79 patients who did meet premedication criteria (382 min, p = 0.23). A multivariate linear regression showed that OTS time was significantly longer if a contrast allergy was present (p < 0.001).

CONCLUSION

A chart-documented iodinated contrast allergy resulted in a significant increase in time to obtain a contrast-enhanced CT study. This delay persisted among patients who did not meet ACR criteria for premedication. Appropriately deferring premedication could potentially reduce the ED length-of-stay by over 4 h for these patients.

The impact of COVID-19 on Emergency Department length of stay for urgent and life-threatening patients

OBJECTIVES

To determine the impact of the Coronavirus disease-2019 (COVID-19) pandemic on the length of stay (LOS) and prognosis of patients in the resuscitation area.

METHODS

A retrospective analysis of case data of patients in the resuscitation area during the early stages of the COVID-19 pandemic (January 15, 2020- January 14, 2021) was performed and compared with the pre-COVID-19 period (January 15, 2019 - January 14, 2020) in the First Affiliated Hospital of Soochow University. The patients' information, including age, sex, length of stay, and death, was collected. The Wilcoxon Rank sum test was performed to compare the LOS difference between the two periods. Fisher's Exact test and Chi-Squared test were used to analyze the prognosis of patients. The LOS and prognosis in different departments of the resuscitation area (emergency internal medicine, emergency surgery, emergency neurology, and other departments) were further analyzed.

RESULTS

Of the total 8278 patients, 4159 (50.24%) were enrolled in the COVID-19 pandemic period group, and 4119 (49.76%) were enrolled pre-COVID-19 period group. The length of stay was prolonged significantly in the COVID-19 period compared with the pre-COVID-19 period (13h VS 9.8h, p < 0.001). The LOS in the COVID-19 period was prolonged in both emergency internal medicine (15.3h VS 11.3h, p < 0.001) and emergency surgery (8.7h VS 4.9h, p < 0.001) but not in emergency neurology or other emergency departments. There was no significant difference in mortality between the two cohorts (4.8% VS 5.3%, p = 0.341).

CONCLUSION

The COVID-19 pandemic was associated with a significant increase in the length of resuscitation area stay, which may lead to resuscitation area crowding. The influence of the COVID-19 pandemic on patients of different departments was variable. There was no significant impact on the LOS of emergency neurology. According to different departments of the resuscitation area, the COVID-19 pandemic didn't significantly impact the prognosis of patients.

Improving Emergency Department Throughput Using Audit-and-Feedback With Peer Comparison Among Emergency Department Physicians

INTRODUCTION

We sought to determine if audit-and-feedback with peer comparison among emergency physicians is associated with improved emergency department (ED) throughput and decreased variation in physician performance.

METHODS

We implemented an audit-and-feedback with peer comparison tool at a single urban academic ED from March 1, 2013, to July 1, 2018. In the first study period, physicians received no reports. In the second period, they received daily reports. In the third period, they received daily, quarterly, and annual reports. Outcomes included patients per hour, admission rate, time to admission, and time to discharge.

RESULTS

A total of 272,032 patient visits and 36 ED physicians were included. The mean admission rate decreased 6.8%; the mean time to admission decreased 43.8 minutes; and the mean time to discharge decreased 40.6 minutes. Variation among physicians decreased for admission rate, time to admission, and time to discharge. Low-performing outliers showed disproportionately larger improvements in patients per hour, admission rate, time to admission, and time to discharge.

CONCLUSIONS

Automated peer comparison reports for academic emergency physicians was associated with lower admission rates, shorter times to admission, and shorter times to discharge at the departmental level, as well as decreased practice variation at the individual level.

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.

In-hospital mortality in the emergency department: clinical and etiological differences between early and late deaths among patients awaiting admission

OBJECTIVE

Given that there are no studies on diseases that occur by waiting for hospitalization, we aimed to evaluate the main causes of death in the emergency room (ER) and their relationship with overcrowding.

METHODS

Patients who died in the ER in the past 2 years (pediatrics and trauma victims excluded) were divided into two groups: patients who died within 6 hours of arrival (emergency department [ED] group) and patients who died later (LD group). We compared the causes of death, total vital signs, diagnostic tests performed, and therapy between the groups. We assessed for possible correlation between the number of monthly deaths per group and four variables of overcrowding: number of patients treated per month, waiting time before medical visit (W-Time), mean intervention time (I-Time), and number of patients admitted to the ward per month (NPA).

RESULTS

During the two years, 175 patients had died in our ER (52% in ED group and 48% in LD group). The total time spent in the ER was, respectively, 2.9±0.2 hours for ED group and 17.9± 1.5 hours for LD group. The more frequent cause of death was cardiovascular syndrome (30%) in ED group and sepsis (27%) and acute respiratory failure (27%) in LD group. Positive correlations between number of monthly deaths and W-Time (R2 0.51, P<0.001), I-Time (R2 0.73, P< 0.0001), and NPA (R2 0.37, P<0.01) were found only in LD group.

CONCLUSION

Patients with sepsis and acute respiratory failure die after a long stay in the ER, and the risk increases with overcrowding. A fast-track pathway should be considered for hospital admission of critical patients.

Increased Length of Stay of Critically Ill Patients in the Emergency Department Associated with Higher In-hospital Mortality

Objectives

Emergency department (ED) length of stay (LOS) is defined as the time a patient is registered to the time the patient is shifted to a hospital bed or discharged. Increasing demand for quality emergency care has resulted in increased wait times due to demand and supply mismatch. It is perceived that longer LOS in the ED of critical patients leads to poor outcomes. Our goal was to study the impact of LOS in the ED on the patients who required critical care admissions.

Methods

This was a retrospective study conducted in the ED of a tertiary center. Data were collected using electronic health records (EHR) for patients admitted to the intensive care units (ICUs). Patient's LOS in ED was divided into 0–4, 4–8, 8–12, 12–24, and >24 hours. ED LOS was calculated from the registration time to the time patient was handed over in the ICU. Patients were divided into four categories (1–4) based on their criticality. LOS in ED, mortality, and total hospital LOS were analyzed in the study.

Results

Three thousand four hundred and twenty-nine patients were enrolled in the study. Mean age was 62.69 years (95% CI 62.11–63.26). A total of 42.09% (95% CI 40.5–43.8) were Category 1 patients. Overall mortality rate was 52.46% (95% CI 50.79–54.13). LOS of 48.15% (95% CI 46.54–49.88) patients in the ED was between 0 and 4 hours, 19.90% (95% CI 18.62–21.29) between 4 and 8 hours, 8.21% (95% CI 7.35–9.19) between 8 and 12 hours, 15.50% (95% CI 14.34–16.77) between 12 and 24 hours, and 8.13% (95% CI 7.27–9.10) >24 hours. Mortality for LOS of 0–4 hours was 51.30% (95% CI 48.89–53.70), 54.03% (95% CI 50.28–57.73) for 4–8 hours, 48.94% (95% CI 43.16–54.75) for 8–12 hours, 51.50% (95% CI 47.26–55.72) for 12–24 hours, and 60.57% (95% CI 54.73–66.13) for >24 hours.

Conclusion

We concluded that the longer the critically ill patients are boarded in the ED, the higher is the chance for mortality. Processes should be implemented to ease the throughput from the ED.

How to cite this article

Verma A, Shishodia S, Jaiswal S, Sheikh WR, Haldar M, Vishen A, et al. Increased Length of Stay of Critically Ill Patients in the Emergency Department Associated with Higher In-hospital Mortality. Indian J Crit Care Med 2021;25(11):1221–1225.

Modification and Validation of a Complaint-Oriented Emergency Department Triage System: A Multicenter Observational Study

PURPOSE

The objective of this study was to modify and validate an emergency department (ED) triage system with improved prediction performance on hospital outcomes by modifying the Korean Triage and Acuity Scale (KTAS).

MATERIALS AND METHODS

We performed a retrospective observational study at three academic universities in South Korea. The KTAS code, determined by the chief complaint and the selected modifier of a patient, was used to derive the Modified KTAS (MKTAS). We calculated the area under the receiver operating characteristics curve (AUC) and the test characteristics to evaluate the performance of MKTAS to predict hospital mortality, critical outcome, and admission.

RESULTS

A total of 272402 and 128831 ED visits were used for the derivation and validation of MKTAS, respectively. Compared to KTAS, MKTAS had significantly higher AUC values for the prediction of hospital mortality [MKTAS 0.826 (0.818-0.835) vs. KTAS 0.794 (0.784-0.803)], critical outcome [MKTAS 0.836 (0.830-0.841) vs. 0.798 (0.792-0.804)], and admission [MKTAS 0.725 (0.723-0.728) vs. KTAS 0.685 (0.682-0.688)]. The sensitivity for predicting hospital mortality and critical outcome, as well as the specificity for predicting admission, were significantly improved.

CONCLUSION

MKTAS was derived by modifying the KTAS, and then validated. Compared with KTAS, MKTAS showed better discriminating ability to predict hospital outcomes. Continuous efforts to evaluate and modify widely used triage systems are required to improve their performance.

Patient Experiences With Transfer for Community Hospital Inpatient Admission From an Academic Emergency Department

Emergency department (ED) crowding continues to be a major challenge and has important ramifications for patient care quality. One strategy to decrease ED crowding has been to implement alternative pathways to traditional hospital admission. Through a survey-based retrospective cohort study, we aimed to assess the patient experience for those who agreed to transfer and admission to an affiliated community hospital from a large, academic center’s ED. In all, 85% of participants rated their overall experience as either great or good, 92% did not find it hard to make the decision to be transferred, and 95% found the transfer process itself to be easy.

Characteristics of low-acuity paediatric emergency department consultations in two tertiary hospitals in Switzerland: a retrospective observational study

BACKGROUND

Low-acuity paediatric emergency department (PED) visits are common in high-income countries and are an increasing burden for the healthcare system and quality of care. Little is known about low-acuity PED visits in Switzerland. This study shows frequency and characteristics of such visits in two large PEDs in German-speaking and French-speaking regions of Switzerland.

METHODS

We conducted a retrospective observational study in the PED of two Swiss tertiary care hospitals, Bern and Lausanne. We extracted standardised administrative and medical data from the clinic information system for all PED visits of children aged 0-17 years from January to December 2018. We defined low-acuity visits as those meeting all of the following criteria: (1) triage category 4 or 5 on the Australasian Triage Scale, (2) no imaging or laboratory test performed and (3) discharge home. We used a binary multiple logistic regression model to identify factors associated with low-acuity visits.

RESULTS

We analysed 53 089 PED visits. The proportion of low-acuity visits was 54% (95% CI 53% to 54%, 28 556 visits). Low-acuity visits were associated with age younger than 5 years (adjusted OR, aOR 1.87, 95% CI 1.81 to 1.94), living within a 5 km radius of PED (aOR 1.27, 95% CI 1.22 to 1.32), and after hour presentations (weekends: aOR 1.14, 95% CI 1.10 to 1.18, nights: aOR 1.10, 95% CI 1.23 to 1.36).

CONCLUSION

Low-acuity visits are frequent in our PEDs and associated with younger age and convenience factors (proximity of residency and after hour presentation), pointing to a high demand for paediatric urgent care services in Switzerland not currently covered by the primary healthcare system.

The effects of unexpected changes in demand on the performance of emergency departments

Crowding in emergency departments (EDs) is increasing in many health systems. Previous studies of the relationship between crowding and care quality are limited by the use of data from single hospitals, a focus on particular patient groups, a focus on a narrow set of quality measures, and use of crowding measures which induce bias from unobserved hospital and patient characteristics. Using data from 139 hospitals covering all major EDss in England, we measure crowding using quasi-exogenous variation in the volume of EDs attendances and examine its impacts on indicators of performance across the entire EDs care pathway. We exploit variations from expected volume estimated using high-dimensional fixed effects capturing hospital-specific variation in attendances by combinations of month and hour-of-the-week. Unexpected increases in attendance volume result in substantially longer waiting times, lower quantity and complexity of care, more patients choosing to leave without treatment, changes in referral and discharge decisions, but only small increases in reattendances and no increase in mortality. Causal bounds under potential omitted variable bias are narrow and exclude zero for the majority of outcomes. Results suggest that physician and patient responses may largely mitigate the impacts of demand increases on patient outcomes in the short-run.

Emergency Department Mean Physician Time per Patient and Workload Predictors ED-MPTPP

One key element for emergency department (ED) staff calculation is the mean physician time per patient (MPTPP) and its influencing factors. The aims of this study were measuring the MPTPP, identifying factors with significant influence on the MPTPP, and developing a model to predict the MPTPP. This study was a prospective trial conducted at the ED of a university hospital in Germany. The MPTPP was measured with a specifically developed app. The influence of different factors on MPTPP were first tested in univariate analysis. Then, all significant factors were used in a multivariant regression model to minimize collinearities and to develop a prediction model. In total, 202 patients treated by 32 different physicians were observed within one year. The MPTPP was 47 min (standard deviation: 34 min). Relevant factors influencing the MPTPP were treatment area, Emergency Severity Index (ESI) triage level, guiding symptom category, and physician level (all p < 0.001). This model predicted 45% of the variance in the MPTPP (p < 0.001), which corresponds to a large effect size. We developed an effective prediction model for ED MPTPP, resulting in an MPTPP of 47 min. Future studies are needed to validate our model, which could serve as a benchmark for other EDs where the MPTPP is not available.

A multicenter mixed-effects model for inference and prediction of 72-h return visits to the emergency department for adult patients with trauma-related diagnoses

Objective

Emergency department (ED) return visits within 72 h may be a sign of poor quality of care and entail unnecessary use of healthcare resources. In this study, we compare the performance of two leading statistical and machine learning classification algorithms, and we use the best performing approach to identify novel risk factors of ED return visits.

Methods

We analyzed 3.2 million ED encounters with at least one diagnosis under “injury, poisoning and certain other consequences of external causes” and “external causes of morbidity.” These encounters included patients 18 years or older from across 128 emergency room facilities in the USA. For each encounter, we calculated the 72-h ED return status and retrieved 57 features from demographics, diagnoses, procedures, and medications administered during the process of administration of medical care. We implemented a mixed-effects model to assess the effects of the covariates while accounting for the hierarchical structure of the data. Additionally, we investigated the predictive accuracy of the extreme gradient boosting tree ensemble approach and compared the performance of the two methods.

Results

The mixed-effects model indicates that certain blunt force and non-blunt trauma inflates the risk of a return visit. Notably, patients with trauma to the head and patients with burns and corrosions have elevated risks. This is in addition to 11 other classes of both blunt force and non-blunt force traumas. In addition, prior healthcare resource utilization, patients who have had one or more prior return visits within the last 6 months, prior ED visits, and the number of hospitalizations within the 6 months are associated with increased risk of returning to the ED after discharge. On the one hand, the area under the receiver characteristic curve (AUROC) of the mixed-effects model was 0.710 (0.707, 0.712). On the other hand, the gradient boosting tree ensemble had a lower AUROC of 0.698 CI (0.696, 0.700) on the independent test model.

Conclusions

The proposed mixed-effects model achieved the highest known AUC and resulted in the identification of novel risk factors. The model outperformed one of the leading machine learning ensemble classifiers, the extreme gradient boosting tree in terms of model performance. The risk factors we identified can assist emergency departments to decrease the number of unplanned return visits within 72 h.

The Association Between Hospital Occupancy and Mortality Among Medicare Patients

BACKGROUND

Hospital crowding is a major challenge facing US health care systems, but few studies have evaluated the association between inpatient occupancy and patient mortality. The objective of this study was to determine how increasing hospital occupancy is associated with the likelihood of inpatient and 30-day out-of-hospital mortality using a novel measure of inpatient occupancy.

METHODS

The researchers conducted a retrospective, observational study using secondary data from the California Office of Statewide Health Planning and Development, including nonfederal, acute care facilities from 1998 to 2012. Using measures of relative hospital occupancy, the researchers ran logistic regressions to assess the relationship between increasing hospital occupancy and inpatient mortality and 30-day out-of-hospital mortality among Medicare patients age 65 years and older with myocardial infarction, heart failure, or pneumonia.

RESULTS

Higher admission day occupancy (odds ratio [OR] = 0.96, 95% confidence interval [CI]: 0.94-0.99) and higher discharge day occupancy (OR = 0.62, 95% CI: 0.60-0.64) were associated with decreased inpatient mortality. Thirty-day out-of-hospital mortality increased with higher discharge day occupancy (OR=1.28, 95% CI: 1.24-1.32) but was unrelated to admission day occupancy.

CONCLUSION

This study found a counterintuitive relationship between admission and discharge day occupancy and inpatient mortality. Higher discharge day occupancy appears to displace deaths into the outpatient setting. Understanding why higher inpatient occupancy is associated with lower overall mortality merits investigation to inform best practices for inpatient care in busy hospitals.

Strategies to measure and improve emergency department performance: a scoping review

BACKGROUND

Over the last two decades, Emergency Department (ED) crowding has become an increasingly common occurrence worldwide. Crowding is a complex and challenging issue that affects EDs' capacity to provide safe, timely and quality care. This review aims to map the research evidence provided by reviews to improve ED performance.

METHODS AND FINDINGS

We performed a scoping review, searching Cochrane Database of Systematic Reviews, Scopus, EMBASE, CINAHL and PubMed (from inception to July 9, 2019; prospectively registered in Open Science Framework https://osf.io/gkq4t/). Eligibility criteria were: (1) review of primary research studies, published in English; (2) discusses a) how performance is measured in the ED, b) interventions used to improve ED performance and their characteristics, c) the role(s) of patients in improving ED performance, and d) the outcomes attributed to interventions used to improve ED performance; (3) focuses on a hospital ED context in any country or healthcare system. Pairs of reviewers independently screened studies' titles, abstracts, and full-texts for inclusion according to pre-established criteria. Discrepancies were resolved via discussion. Independent reviewers extracted data using a tool specifically designed for the review. Pairs of independent reviewers explored the quality of included reviews using the Risk of Bias in Systematic Reviews tool. Narrative synthesis was performed on the 77 included reviews. Three reviews identified 202 individual indicators of ED performance. Seventy-four reviews reported 38 different interventions to improve ED performance: 27 interventions describing changes to practice and process (e.g., triage, care transitions, technology), and a further nine interventions describing changes to team composition (e.g., advanced nursing roles, scribes, pharmacy). Two reviews reported on two interventions addressing the role of patients in ED performance, supporting patients' decisions and providing education. The outcomes attributed to interventions used to improve ED performance were categorised into five key domains: time, proportion, process, cost, and clinical outcomes. Few interventions reported outcomes across all five outcome domains.

CONCLUSIONS

ED performance measurement is complex, involving automated information technology mechanisms and manual data collection, reflecting the multifaceted nature of ED care. Interventions to improve ED performance address a broad range of ED processes and disciplines.

Lessons learned from an evaluation of referrals to the emergency department

BACKGROUND

Emergency department (ED) crowding is an international phenomenon dependent on input, throughput, and output factors. This study aims to determine whether patterns of potentially unnecessary referrals from either primary care physicians (PCPs) or urgent care centers (UCCs) can be identified, thereby to reduce ED visits by patients who could be treated elsewhere. Literature from the United States reports up to 35% unnecessary referrals from UCCs.

METHODS

A retrospective cohort study was conducted of patients referred to an ED in Jerusalem by either their PCP or a group of UCCs with a full range of laboratory tests and basic imaging capabilities between January 2017 and December 2017. The data were analyzed to identify referrals involving diagnoses, specialist consultations, and examinations unavailable in the PCP's office or UCC (e.g., ultrasound, CT, echocardiogram, or stress test); these referrals were considered necessary for completion of the patient work-up. If patients were evaluated by an ED physician and sent home after an examination or laboratory test available at least in the UCC, the referrals were considered potentially unnecessary.

RESULTS

Significantly more referrals were made by PCPs than UCCs (1712 vs. 280, p < 0.001). Significant differences were observed for orthopedics, general surgery, and obstetrics/gynecology referrals (p = 0.039, p < 0.001, p = 0.003). A higher percentage of patients referred by PCPs had potentially unnecessary visits compared to patients referred by UCCs (13.9% vs. 7.9%, p = 0.005).

CONCLUSION

A robust UCC system may help further reduce potentially unnecessary visits (including complex patients) to the ED.

An Integrated Approach of Machine Learning and Systems Thinking for Waiting Time Prediction in an Emergency Department

OBJECTIVE

The objective of this study is to apply machine learning algorithms for real-time and personalized waiting time prediction in emergency departments. We also aim to introduce the concept of systems thinking to enhance the performance of the prediction models.

METHODS

Four popular algorithms were applied: (i) stepwise multiple linear regression; (ii) artificial neural networks; (iii) support vector machines; and (iv) gradient boosting machines. A linear regression model served as a baseline model for comparison. We conducted computational experiments based on a dataset collected from an emergency department in Hong Kong. Model diagnostics were performed, and the results were cross-validated.

RESULTS

All the four machine learning algorithms with the use of systems knowledge outperformed the baseline model. The stepwise multiple linear regression reduced the mean-square error by almost 15%. The other three algorithms had similar performances, reducing the mean-square error by approximately 20%. Reductions of 17 - 22% in mean-square error due to the utilization of systems knowledge were observed.

DISCUSSION

The multi-dimensional stochasticity arising from the ED environment imposes a great challenge on waiting time prediction. The introduction of the concept of systems thinking led to significant enhancements of the models, suggesting that interdisciplinary efforts could potentially improve prediction performance.

CONCLUSION

Machine learning algorithms with the utilization of the systems knowledge could significantly improve the performance of waiting time prediction. Waiting time prediction for less urgent patients is more challenging.

The impact of pediatric emergency department crowding on patient and health care system outcomes: a multicentre cohort study

BACKGROUND

Emergency department overcrowding has been associated with increased odds of hospital admission and mortality after discharge from the emergency department in predominantly adult cohorts. The objective of this study was to evaluate the association between crowding and the odds of several adverse outcomes among children seen at a pediatric emergency department.

METHODS

We conducted a retrospective cohort study involving all children visiting 8 Canadian pediatric emergency departments across 4 provinces between 2010 and 2014. We analyzed the association between mean departmental length of stay for each index visit and hospital admission within 7 days or death within 14 days of emergency department discharge, as well as hospital admission at index visit and return visits within 7 days, using mixed-effects logistic regression modelling.

RESULTS

A total of 1 931 465 index visits occurred across study sites over the 5-year period, with little variation in index visit hospital admission or median length of stay. Hospital admission within 7 days of discharge and 14-day mortality were low across provinces (0.8%-1.5% and < 10 per 100 000 visits, respectively), and their association with mean departmental length of stay varied by triage categories and across sites but was not significant. There were increased odds of hospital admission at the index visit with increasing departmental crowding among visits triaged to Canadian Triage and Acuity Scale (CTAS) score 1-2 (odds ratios [ORs] ranged from 1.01 to 1.08) and return visits among patients with a CTAS score of 4-5 discharged at the index visit at some sites (ORs ranged from 1.00 to 1.06).

INTERPRETATION

Emergency department crowding was not significantly associated with hospital admission within 7 days of the emergency department visit or mortality in children. However, it was associated with increased hospital admission at the index visit for the sickest children, and with return visits to the emergency department for those less sick.

Role of Point-of-Care Testing in Reducing Time to Treatment Decision-Making in Urgency Patients: A Randomized Controlled Trial

INTRODUCTION

Shortening emergency department (ED) visit time can reduce ED crowding, morbidity and mortality, and improve patient satisfaction. Point-of-care testing (POCT) has the potential to decrease laboratory turnaround time, possibly leading to shorter time to decision-making and ED length of stay (LOS). We aimed to determine whether the implementation of POCT could reduce time to decision-making and ED LOS.

METHODS

We conducted a randomized control trial at the Urgency Room of Siriraj Hospital in Bangkok, Thailand. Patients triaged as level 3 or 4 were randomized to either the POCT or central laboratory testing (CLT) group. Primary outcomes were time to decision-making and ED LOS, which we compared using Mann-Whitney-Wilcoxon test.

RESULTS

We enrolled a total of 248 patients: 124 in the POCT and 124 in the CLT group. The median time from arrival to decision was significantly shorter in the POCT group (106.5 minutes (interquartile [IQR] 78.3-140) vs 204.5 minutes (IQR 165-244), p <0.001). The median ED LOS of the POCT group was also shorter (240 minutes (IQR 161.3-410) vs 395.5 minutes (IQR 278.5-641.3), p <0.001).

CONCLUSION

Using a point-of-care testing system could decrease time to decision-making and ED LOS, which could in turn reduce ED crowding.

Emergency department overcrowding : Analysis and strategies to manage an international phenomenon

Overcrowding in emergency departments is a common and worldwide phenomenon, which is widely reported even in the lay press. Strategies to address this incriminating situation for patients, nurses, physicians and hospital administrators are urgently needed. The current review presents an analysis of the overcrowding problem as well as strategies to answer overcrowding situations.

Attitudes and Behavior of Health Care Workers Before, During, and After Implementation of Real-Time Location System Technology

Objective

To assess how staff attitudes before, during, and after implementation of a real-time location system (RTLS) that uses radio-frequency identification tags on staff and patient identification badges and on equipment affected staff’s intention to use and actual use of an RTLS.

Participants and Methods

A series of 3 online surveys were sent to staff at an emergency department with plans to implement an RTLS between June 1, 2015, and November 29, 2016. Each survey corresponded with a different phase of implementation: preimplementation, midimplementation, and postimplementation. Multiple logistic regression with backward elimination was used to assess the relationship between demographic variables, attitudes about RTLSs, and intention to use or actual use of an RTLS.

Results

Demographic variables were not associated with intention to use or actual use of the RTLS. Before implementation, poor perceptions about the technology’s usefulness and lack of trust in how employers would use tracking data were associated with weaker intentions to use the RTLS. During and after implementation, attitudes about the technology’s use, not issues related to autonomy and privacy, were associated with less use of the technology.

Conclusion

Real-time location systems have the potential to assess patterns of health care delivery that could be modified to reduce costs and improve the quality of care. Successful implementation, however, may hinge on how staff weighs attitudes and concerns about their autonomy and personal privacy with organizational goals. With the large investments required for new technology, serious consideration should be given to address staff attitudes about privacy and technology in order to assure successful implementation.

Use of Computer Modeling to Streamline Care in a Psychiatric Emergency Room: A Case Report

Computer simulation using JaamSim tested the impact of changing the number of providers, proportion of independent to supervised providers, shift provider added, time to hospitalization, and the number of beds in order to identify bottlenecks in a psychiatric emergency department. Adding an independent provider from 4 p.m. to midnight produced the largest improvements: reductions in time to bed, time to provider, and length of stay by 82%, 68%, and 31%, respectively. Decreasing time to hospitalization and adding beds achieved modest improvements. Modeling allows simulated changes to one parameter at a time and provides bespoke analysis for a variety of clinical settings.

Internet search query data improve forecasts of daily emergency department volume

OBJECTIVE

Emergency departments (EDs) are increasingly overcrowded. Forecasting patient visit volume is challenging. Reliable and accurate forecasting strategies may help improve resource allocation and mitigate the effects of overcrowding. Patterns related to weather, day of the week, season, and holidays have been previously used to forecast ED visits. Internet search activity has proven useful for predicting disease trends and offers a new opportunity to improve ED visit forecasting. This study tests whether Google search data and relevant statistical methods can improve the accuracy of ED volume forecasting compared with traditional data sources.

MATERIALS AND METHODS

Seven years of historical daily ED arrivals were collected from Boston Children's Hospital. We used data from the public school calendar, National Oceanic and Atmospheric Administration, and Google Trends. Multiple linear models using LASSO (least absolute shrinkage and selection operator) for variable selection were created. The models were trained on 5 years of data and out-of-sample accuracy was judged using multiple error metrics on the final 2 years.

RESULTS

All data sources added complementary predictive power. Our baseline day-of-the-week model recorded average percent errors of 10.99%. Autoregressive terms, calendar and weather data reduced errors to 7.71%. Search volume data reduced errors to 7.58% theoretically preventing 4 improperly staffed days.

DISCUSSION

The predictive power provided by the search volume data may stem from the ability to capture population-level interaction with events, such as winter storms and infectious diseases, that traditional data sources alone miss.

CONCLUSIONS

This study demonstrates that search volume data can meaningfully improve forecasting of ED visit volume and could help improve quality and reduce cost.

Association entre mortalité et attente aux urgences chez les adultes à hospitaliser pour étiologies médicales

Introduction : Notre objectif principal est de comparer, dans un centre hospitalier universitaire (CHU) français et chez les patients hospitalisés pour étiologies médicales à partir de la structure des urgences (SU), le taux de mortalité intrahospitalière entre ceux qui n’attendent pas faute de place en service et ceux en attente (boarding).

Méthode : Il s’agit d’une étude quasi expérimentale, monocentrique, observationnelle, rétrospective, par recueil d’informations à partir des dossiers patients informatisés. Nous avons appliqué un score de propension pour ajuster les critères de jugement aux variables mesurées dans les deux groupes, c’est-à-dire les données : 1) démographiques (âge et sexe) ; 2) médicales (niveau de triage) ; 3) biologiques (numération leucocytaire, hémoglobinémie, natrémie, kaliémie, taux sérique de CRP, créatininémie) ; 4) d’imageries (réalisation ou non de radiographie, d’échographie, d’imagerie par résonance magnétique, de tomodensitométrie).

Résultats : En 2017, la SU du CHU a admis 60 062 patients adultes. Sur les 15 496 patients hospitalisés après admission en SU, 6 997 l’ont été pour une étiologie médicale, dont 2 546 (36 %) sans attente et 4 451 (64 %) après une attente. Après pondération, le taux de mortalité intrahospitalière était plus important dans le groupe en attente : 7,8 vs 6,3 % ; p < 0,05. De même, la durée médiane d’hospitalisation était plus importante dans le groupe en attente : 7,6 [4,7– 12,0] vs 7,1 j [4,3–11,5] ; p < 0,01.

Discussion : Les taux de mortalité et de la durée de séjour intrahospitaliers sont plus importants chez les patients étudiés qui attendent en SU faute de place en service. Nos résultats sont concordants avec la littérature internationale. Il est nécessaire de trouver des solutions pour réduire cette surmortalité.

Analysis of the citation of articles published in the European Journal of Emergency Medicine since its foundation

OBJECTIVES

The aim of this study was to evaluate the evolution of the citation of articles from the European Journal of Emergency Medicine (EJEM) from 1994 (EJEM foundation) to 2015 and identify highly cited articles and their principal characteristics and determine a possible correlation between the citations counted in different databases.

MATERIALS AND METHODS

We obtained the articles published in EJEM from 1994 to 2015 in ISI-WoS (main source) and Scopus, Google Scholar, and Medline databases (accessory sources). The citations were quantified and their annual evolution and the bibliometric indices derived (impact factor and SCImago Journal Rank) were evaluated. We identified and analyzed the highly cited EJEM articles and evaluated the possible correlation between the citations counted for these articles in the databases.

RESULTS

Overall, 1705 EJEM articles were cited 9422 times in 8122 different articles. The evolution of the global citation, impact factor, and SCImago Journal Rank from 1994 to 2015 increased significantly. The h-index of EJEM was 30, and 31 articles were considered highly cited (≥30 citations), 16.1% of them being clinical trials. By subjects, 22.5% corresponded to cardiology, 19.3% to emergency department management, and 12.9% to pediatrics; by countries, 81% were from Europe, with Belgian authors publishing four (12.9%) highly cited articles, and French, Spanish, British, and Swedish authors having three (9.7%) each. Two studies in the EJEM achieved the definition of 'citation classics' (more than 100 citations). The number of citations in all the databases, except Medline, showed statistically significant correlations.

CONCLUSION

Citation of EJEM articles has progressively increased and EJEM bibliometric indicators have improved; most highly cited articles are mainly by European authors.

Characteristics of ED crowding in the Lazio Region (Italy) and short-term health outcomes

The effect of emergency department (ED) crowding on patient care has been studied for several years in the scientific literature. We evaluate the association between ED crowding and short-term mortality and hospitalization in the Lazio region (Italy) using two different measures. A cohort of visits in the Lazio region ED during 2012-2014 was enrolled. Only discharged patients were selected. ED crowding was estimated using two measures, length of stay (LOS), and Emergency Department volume (EDV). LOS was defined as the interval of time from entrance to discharge; EDV was defined at the time of each new entrance in ED. The outcomes under study were mortality and hospitalization within 7 days from ED discharge. A multivariate logistic model was performed (Odds Ratios, ORs, 95% CI). The cohort includes 2,344,572 visits. ED crowding is associated with an increased risk of short-term hospitalization using both LOS and EDV as exposures (LOS 1-2 h: OR = 1.71, 95% CI 1.66-1.76, LOS 2-5 h: OR = 1.38, 95% CI 1.34-1.43, LOS > 5 h OR = 1.45 95% CI 1.40-1.50 compared to patients with 1 h of LOS; EDV 75°-95° percentile: OR = 1.02, 95% CI 0.99-1.05 and EDV > 95° percentile: OR = 1.06, 95% CI 1.01-1.11 compared to patients with a EDV < 75° percentile upon arrival). Increased risk of short-term mortality is found with increasing level of LOS. High levels of EDV at the time of patients' arrival and longer LOS in ED are associated with greater risks of hospitalization for patients discharged 7 days before. LOS in ED is also associated with an increased risk of mortality.

Long length of stay at the emergency department is mostly caused by organisational factors outside the influence of the emergency department: A root cause analysis

Background

Emergency department (ED) crowding is common and associated with increased costs and negative patient outcomes. The aim of this study was to conduct an in-depth analysis to identify the root causes of an ED length of stay (ED-LOS) of more than six hours.

Methods

An observational retrospective record review study was conducted to analyse the causes for ED-LOS of more than six hours during a one-week period in an academic hospital in the Netherlands. Basic administrative data were collected for all visiting patients. A root cause analysis was conducted using the PRISMA-method for patients with an ED-LOS > 6 hours, excluding children and critical care room presentations.

Results

568 patients visited the ED during the selected week (January 2017). Eighty-four patients (15%) had an ED-LOS > 6 hours and a PRISMA-analysis was performed in 74 (88%) of these patients. 269 root causes were identified, 216 (76%) of which were organisational and 53 (22%) patient or disease related. 207 (94%) of the organisational factors were outside the influence of the ED. Descriptive statistics showed a mean number of 2,5 consultations, 59% hospital admissions or transfers and a mean age of 57 years in the ED-LOS > 6 hours group. For the total group, there was a mean number of 1,9 consultations, 29% hospital admissions or transfers and a mean age of 43 years.

Conclusions

This study showed that the root causes for an increased ED-LOS were mostly organisational and beyond the control of the ED. These results confirm that interventions addressing the complete acute care chain are needed in order to reduce ED-LOS and crowding in ED’s.

Non-urgent use of emergency departments: populations most likely to overestimate illness severity

Patients' overestimation of their illness severity appears to contribute to the national epidemic of emergency department (ED) overcrowding. This study aims to elucidate which patient populations are more likely to have a higher estimation of illness severity (EIS). The investigator surveyed demographic factors of all non-urgent patients at an academic ED. The patients and physicians were asked to estimate the patients' illness severity using a 1-10 scale with anchors. The difference of these values was taken and compared across patient demographic subgroups using a 2-sample t-test. One hundred and seventeen patients were surveyed. The mean patient EIS was 5.22 (IQR 4), while the mean physician EIS was less severe at 7.57 (IQR 3), a difference of 2.35 (p < 0.0001). Patient subgroups with the highest EIS compared to the physicians' EIS include those who were self-referred (difference of 2.65, p = 0.042), with income ≤ $25,000 (difference of 2.96, p = 0.004), with less than a college education (difference of 2.83, p = 0.018), and with acute-on-chronic musculoskeletal pain (difference of 4.17, p = 0.001). If we assume the physicians' EIS is closer to the true illness severity, patients with lower socioeconomic status, lower education status, who were self-referred, and who suffered from acute-on-chronic musculoskeletal pain are more likely to overestimate their illness severity and may contribute to non-urgent use of the ED. They may benefit from further education or resources for care to prevent ED misuse. The large difference of acute-on-chronic musculoskeletal pain may reflect a physician's bias to underestimate the severity of a patients' illness in this particular population.

Barriers and enablers to a physician-delivered educational initiative to reduce low-acuity visits to the pediatric emergency department

BACKGROUND

Use of the pediatric emergency department (PED) for low-acuity health issues is a growing problem, contributing to overcrowding, longer waits and higher health system costs. This study examines an educational initiative aimed at reducing low-acuity PED visits. The initiative, implemented at an academic pediatric hospital, saw PED physicians share a pamphlet with caregivers to educate them about appropriate PED use and alternatives. Despite early impacts, the initiative was not sustained. This study analyzes the barriers and enablers to physician participation in the initiative, and offers strategies to improve implementation and sustainability of similar future initiatives.

METHODS

Forty-two PED physicians were invited to participate in a semi-structured individual interview assessing their views about low-acuity visits, their pamphlet use, barriers and enablers to pamphlet use, and the initiative's potential for reducing low-acuity visits. Suggestions were solicited for improving the initiative and reducing low-acuity visits. Constant comparative method was used during analysis. Codes were developed inductively and iteratively, then grouped according to the Theoretical Domains Framework (TDF). Efforts to ensure study credibility included seeking participant feedback on the findings.

RESULTS

Twenty-three PED physicians were interviewed (55%). Barriers and enablers for pamphlet use were identified and grouped according to five of the 14 TDF domains: social/professional role and identity; beliefs about consequences; environmental context and resources; social influences; and emotions.

CONCLUSIONS

The TDF provided an effective approach to identify the key elements influencing physician participation in the educational initiative. This information will help inform behavior change interventions to improve the implementation of similar future initiatives that involve physicians as the primary educators of caregivers.

Emergency Department Misuse and Administrative Interventions

Introduction

Notwithstanding the primary mission of managing sudden unexpected illnesses, major injuries and life-threatening conditions, emergency departments have been forced to deal with primary care and even social problems nowadays. Emergency department (ED) overcrowding is a worldwide problem. Hong Kong is not immune, although the causes may be somewhat different. Excessive and unlimited patient volume threatens quality and timely emergency care. A review of the epidemiology of local ED attendance, causes of ED overcrowding and possible solutions may guide the future direction of healthcare in Hong Kong.

Methods

Medical literature on ED overcrowding and ED misuse were searched from the Medline, HealthSTAR and EMBASE. Relevant full text articles were retrieved through hospital library network. Local emergency medicine publications including the Hong Kong Journal of Emergency Medicine and Emergi-News were reviewed. Local statistics were obtained from the Hong Kong Government information website, Hospital Authority Executive Information System (EIS) and Hospital Authority Accident & Emergency Service data files.

Results

There has been a steadily rising trend of ED attendance per thousand population. Causes of ED overcrowding include easy access, quality emergency care, barriers to primary care, barriers to specialist care, patient education, human right and free service. There are two approaches to the problem - decreasing the demand or increasing the funding. Usual administrative measures aim at reducing inappropriate use of ED service. These include improved community and primary care, improved specialist support, patient education, financial barriers, patient refusal and even lowering ED service standard. Another approach is augmenting the resources and productivity of emergency departments to cater for the increasing demand.

Conclusions

There is no single effective solution that will apply in all circumstances. Broadly speaking, overcrowding is the result of inadequate funding for emergency health care services during a period of increasing demand.

Can different physicians providing urgent and non-urgent treatment improve patient flow in emergency department?

BACKGROUND

Emergency Department (ED) overcrowding is a worldwide problem, and it might be caused by prolonged patient stay in the ED. This study tried to analyze if different practice models influence patient flow in the ED.

MATERIALS AND METHODS

A retrospective, 1-year cohort study was conducted across two EDs in the largest healthcare system in Taiwan. A total of 37,580 adult non-trauma patients were involved in the study. The clinical practice between two ED practice models was compared. In one model, urgent and non-urgent patients were treated by different emergency physicians (EPs) separately (separated model). In the other, EPs treated all patients assigned randomly (merged model). The ED length of stay (LOS), diagnostic tool use (including laboratory examinations and computed tomography scans), and patient dispositions (including discharge, general ward admission, intensive care unit (ICU) admissions, and ED mortality) were selected as outcome indicators.

RESULT

Patients discharged from ED had 0.4h shorter ED LOS in the separated model than in merged model. After adjusting for the potential confounding factors through regression model, there was no difference of patient disposition of the two practice models. However, the separated model showed a slight decrease in laboratory examination use (adjusted odds ratio, 0.9; 95% confidence interval, 0.83-0.96) compared with the merged model.

CONCLUSION

The separated model had better patient flow than the merged model did. It decreased the ED LOS in ED discharge patients and laboratory examination use.

Paediatric emergency department overcrowding and adverse patient outcomes

Background

General emergency department crowding negatively impacts patient care, and increases patient morbidity.

Objectives

This study seeks to determine if markers of paediatric emergency department (PED) flow are independently associated with negative outcomes and increased health care utilization.

Methods

We conducted a retrospective cohort study of PED visits from 2008 to 2012. Data were pulled from an electronic administrative database. Using multivariate logistic regression models, we measured the association between odds of adverse outcomes (hospital/paediatric intensive care unit [PICU] admission, unscheduled return visits and mortality) with markers of PED flow (shift mean length of stay [LOS] and daily rate of patients leaving without being seen [LWBS]).

Results

We found an association between the daily LWBS proportion and the odds of being admitted to the hospital (odds ratio [OR]: 2.1; 95% confidence interval [CI]: 1.2, 3.7), as well as admission to the PICU (OR: 8.9; 95% CI: 1.1, 71.3). We found a statistically significant increase in the odds of admission if seen during shifts in the third or fourth quartile mean shift LOS. We observed lower odds of returning to the PED with increased daily LWBS proportions (OR: 0.4; 95% CI: 0.2, 0.7), but found no association between the odds of returning to the PED and mean shift LOS.

Conclusion

While we found an association between our pre-defined measures of adverse outcomes and markers of PED flow (or crowding), further studies are needed to determine whether PED overcrowding is the cause or effect of increased hospital and PICU admissions.

Applying Systems Engineering Reduces Radiology Transport Cycle Times in the Emergency Department

INTRODUCTION

Emergency department (ED) crowding is widespread, and can result in care delays, medical errors, increased costs, and decreased patient satisfaction. Simultaneously, while capacity constraints on EDs are worsening, contributing factors such as patient volume and inpatient bed capacity are often outside the influence of ED administrators. Therefore, systems engineering approaches that improve throughput and reduce waste may hold the most readily available gains. Decreasing radiology turnaround times improves ED patient throughput and decreases patient waiting time. We sought to investigate the impact of systems engineering science targeting ED radiology transport delays and determine the most effective techniques.

METHODS

This prospective, before-and-after analysis of radiology process flow improvements in an academic hospital ED was exempt from institutional review board review as a quality improvement initiative. We hypothesized that reorganization of radiology transport would improve radiology cycle time and reduce waste. The intervention included systems engineering science-based reorganization of ED radiology transport processes, largely using Lean methodologies, and adding no resources. The primary outcome was average transport time between study order and complete time. All patients presenting between 8/2013-3/2016 and requiring plain film imaging were included. We analyzed electronic medical record data using Microsoft Excel and SAS version 9.4, and we used a two-sample t-test to compare data from the pre- and post-intervention periods.

RESULTS

Following the intervention, average transport time decreased significantly and sustainably. Average radiology transport time was 28.7 ± 4.2 minutes during the three months pre-intervention. It was reduced by 15% in the first three months (4.4 minutes [95% confidence interval [CI] 1.5-7.3]; to 24.3 ± 3.3 min, P=0.021), 19% in the following six months (5.4 minutes, 95% CI [2.7-8.2]; to 23.3 ± 3.5 min, P=0.003), and 26% one year following the intervention (7.4 minutes, 95% CI [4.8-9.9]; to 21.3 ± 3.1 min, P=0.0001). This result was achieved without any additional resources, and demonstrated a continual trend towards improvement. This innovation demonstrates the value of systems engineering science to increase efficiency in ED radiology processes.

CONCLUSION

In this study, reorganization of the ED radiology transport process using systems engineering science significantly increased process efficiency without additional resource use.

Minimizing Spatial Variability of Healthcare Spatial Accessibility-The Case of a Dengue Fever Outbreak

Outbreaks of infectious diseases or multi-casualty incidents have the potential to generate a large number of patients. It is a challenge for the healthcare system when demand for care suddenly surges. Traditionally, valuation of heath care spatial accessibility was based on static supply and demand information. In this study, we proposed an optimal model with the three-step floating catchment area (3SFCA) to account for the supply to minimize variability in spatial accessibility. We used empirical dengue fever outbreak data in Tainan City, Taiwan in 2015 to demonstrate the dynamic change in spatial accessibility based on the epidemic trend. The x and y coordinates of dengue-infected patients with precision loss were provided publicly by the Tainan City government, and were used as our model's demand. The spatial accessibility of heath care during the dengue outbreak from August to October 2015 was analyzed spatially and temporally by producing accessibility maps, and conducting capacity change analysis. This study also utilized the particle swarm optimization (PSO) model to decrease the spatial variation in accessibility and shortage areas of healthcare resources as the epidemic went on. The proposed method in this study can help decision makers reallocate healthcare resources spatially when the ratios of demand and supply surge too quickly and form clusters in some locations.

Association Between the Opening of Retail Clinics and Low-Acuity Emergency Department Visits

STUDY OBJECTIVE

We assess whether the opening of retail clinics near emergency departments (ED) is associated with decreased ED utilization for low-acuity conditions.

METHODS

We used data from the Healthcare Cost and Utilization Project State Emergency Department Databases for 2,053 EDs in 23 states from 2007 to 2012. We used Poisson regression models to examine the association between retail clinic penetration and the rate of ED visits for 11 low-acuity conditions. Retail clinic "penetration" was measured as the percentage of the ED catchment area that overlapped with the 10-minute drive radius of a retail clinic. Rate ratios were calculated for a 10-percentage-point increase in retail clinic penetration per quarter. During the course of a year, this represents the effect of an increase in retail clinic penetration rate from 0% to 40%, which was approximately the average penetration rate observed in 2012.

RESULTS

Among all patients, retail clinic penetration was not associated with a reduced rate of low-acuity ED visits (rate ratio=0.999; 95% confidence interval=0.997 to 1.000). Among patients with private insurance, there was a slight decrease in low-acuity ED visits (rate ratio=0.997; 95% confidence interval=0.994 to 0.999). For the average ED in a given quarter, this would equal a 0.3% reduction (95% confidence interval 0.1% to 0.6%) in low-acuity ED visits among the privately insured if retail clinic penetration rate increased by 10 percentage points per quarter.

CONCLUSION

With increased patient demand resulting from the expansion of health insurance coverage, retail clinics may emerge as an important care location, but to date, they have not been associated with a meaningful reduction in low-acuity ED visits.

Correlates of Length of Stay and Boarding in Florida Emergency Departments for Patients With Psychiatric Diagnoses

OBJECTIVE

Length of stay (LOS) and boarding in the emergency department (ED) for psychiatric patients have been the subject of concern, given the problems with crowding and excessive wait times in EDs. This investigation examined correlates of LOS and boarding in Florida EDs for patients presenting with psychiatric complaints from 2010 to 2013.

METHODS

Utilizing the Florida ED discharge database, the authors examined the association of LOS and boarding with hospital and encounter factors for adult patients presenting with a primary psychiatric diagnosis (N=597,541).

RESULTS

The mean LOS was 7.77 hours. Anxiety disorders were the most frequent psychiatric complaint and were associated with the lowest mean LOS compared with other diagnoses (p<.05). Patient encounters resulting in a presentation of intentional self-harm and suicidality or schizophrenia were associated with significantly longer stays compared with other psychiatric diagnoses. Commercial insurance was associated with the shortest average LOS. African Americans, Hispanics, and patients age 45 and older were associated with a longer average LOS. Smaller hospital size, for-profit ownership, and rural designation were associated with a shorter average LOS. Teaching status was not associated with LOS. Furthermore, 73% of encounters resulting in transfers qualified as episodes of boarding (a stay of more than six or more hours in the ED).

CONCLUSIONS

Extended LOS was endemic for psychiatric patients in Florida EDs.

Trends in Emergency Department Resource Utilization for Poisoning-Related Visits, 2003-2011

In recent years, there has been an increase in poisoning-related emergency department (ED) visits. This study examines trends in ED resource utilization for poisoning-related visits over time. A retrospective review of data from the National Hospital Ambulatory Medical Care Survey, 2003-2011, was conducted. All ED visits with a reason for visit or ICD-9 code related to poisoning were included. We examined the number of ED visits and resources used including diagnostic studies and procedures performed, medications provided, admission rates, and length of stay. The proportion of visits involving resource use was tabulated and trends analyzed using survey-weighted logistic regression, grouping into 2-year periods to ensure adequate sample size. Of an estimated 843 million ED visits between 2003 and 2011, 8 million (0.9 %) were related to poisoning. Visits increased from 1.8 million (0.8 %) visits in 2003-2004 to 2.9 million (1.1 %) visits in 2010-2011, p = 0.001. Use of laboratory studies, EKGs, plain radiographs, and procedures remained stable across the study period. CT use was more than doubled, increasing from 5.2 to 13.7 % of visits, p = 0.001. ED length of stay increased by 35.5 % from 254 to 344 min, p = 0.001. Admission rates increased by 45.3 %, from 15.0 to 21.8 %, p = 0.046. Over the entire study period, 52.0 % of poisoned patients arrived via ambulance, and 3.0 % of patients had been discharged from the hospital within the previous 7 days. Poisoning-related ED visits increased over the 8-year study period; poisonings are resource-intensive visits and require increasingly longer lengths of ED stay or hospital admission.

Variability and Overcrowding Management

Emergency department (ED) overcrowding has become a common situation with significant negative effects on the quality of care. The aim of this study is to detail the flow of patients and their variability and determine the existence of stable patterns that allow better planning of resources.

We performed a retrospective descriptive observational study of emergencies attended from 2008 to 2010 in the ‘Juan Ramón Jiménez’ General Hospital (Huelva, Spain), with a sample of 343,233 visits. The time between consecutive arrivals of patients and the arrival patterns according to severity and clinical area was calculated using Microsoft Excel and Stat::Fit. Quarterly differences were determined using the Kruskal–Wallis test.

The mean value of the inter-arrival time, independent of the quarter ( p < 0.05), was 2–4 minutes from 10:00 am to 10:00 pm and 15–20 minutes from midnight to 8:00 am. The Priority (P) I Patients arrived every 119.05 ± 136.71 minutes, the PII patients every 75.96 ± 97.58 minutes, the PIII patients every 22.62 ± 33.47 minutes and the PIV patients every 6.37 ± 10.53 minutes. PIV had a fluctuating pattern. The arrival rate peaks at 1:00 pm on Monday in the medical–surgical area, at 10:00 pm on Monday for the trauma area, and at 1:00 pm on Sunday for the paediatric area.

The study shows that inter-arrival times and average arrival rates of patients have a defined and reproducible pattern for each level of severity and clinical area, which forces us to rethink the fixed capacity model and oriented towards flexibility of resources to reduce the overcrowding.