The influence of emergency department crowding on the efficiency of care for acute stroke patients

Development of a machine learning-based clinical decision support system to predict clinical deterioration in patients visiting the emergency department

This study aimed to develop a machine learning-based clinical decision support system for emergency departments based on the decision-making framework of physicians. We extracted 27 fixed and 93 observation features using data on vital signs, mental status, laboratory results, and electrocardiograms during emergency department stay. Outcomes included intubation, admission to the intensive care unit, inotrope or vasopressor administration, and in-hospital cardiac arrest. eXtreme gradient boosting algorithm was used to learn and predict each outcome. Specificity, sensitivity, precision, F1 score, area under the receiver operating characteristic curve (AUROC), and area under the precision-recall curve were assessed. We analyzed 303,345 patients with 4,787,121 input data, resampled into 24,148,958 1 h-units. The models displayed a discriminative ability to predict outcomes (AUROC > 0.9), and the model with lagging 6 and leading 0 displayed the highest value. The AUROC curve of in-hospital cardiac arrest had the smallest change, with increased lagging for all outcomes. With inotropic use, intubation, and intensive care unit admission, the range of AUROC curve change with the leading 6 was the highest according to different amounts of previous information (lagging). In this study, a human-centered approach to emulate the clinical decision-making process of emergency physicians has been adopted to enhance the use of the system. Machine learning-based clinical decision support systems customized according to clinical situations can help improve the quality of care.

The effects of an emergency department length-of-stay management system on severely ill patients' treatment outcomes

PURPOSE

This study aimed to compare the length of stay (LOS) and treatment outcomes based on the application and achievement of a newly developed emergency department (ED) LOS management system for severely ill patients.

METHODS

Data were retrospectively collected from electronic medical records (EMRs) for the system evaluation and research purpose. The study subjects are severely ill patients whose diagnosis codes are designated by the Ministry of Health and Welfare and who visited the ED of a tertiary hospital from January to December 2019. The control group (Group 1) refers to those who have neither applied nor achieved the goal (5 hours or less) of the ED LOS management system even after it was applied, and the experimental group (Group 2) refers to those who have achieved the 5-hour goal after applying the system.

RESULTS

A total of 2034 severely ill patients applied the ED LOS management system. Group 1 included 837 patients and Group 2 included 1197 patients. Thirty days in-hospital mortality corresponded to 10.6% in Group 1 and 6.6% in Group 2 (χ2 = 10.58, p = .001). The total duration of hospitalization was 14.66 ± 18.26 days in Group 1 and 10.19 ± 16.00 days in Group 2 (t = 9.03, p < .001). Six hundred forty-two patients (76.6%) in Group 1 were discharged to their home (normal discharge) and 979 patients (81.7%) were discharged to their home in Group 2, but the discharge-as-death rate was 14.1% in Group 1 and 7.5% in Group 2 (χ2 = 29.80, p < .001).

CONCLUSION

With the application and attainment of the ED LOS management system for severely ill patients, we have concluded the new system produced a lower LOS in the ED, 30 days in-hospital mortality, length of the hospitalization, mortality rate, and a higher rate of normal discharge.

Structural Inequities for Historically Underserved Communities in the Adoption of Stroke Certification in the United States

Importance

Stroke centers are associated with better outcomes. There is substantial literature surrounding disparities in stroke outcomes for underserved populations. However, the existing literature has focused primarily on discrimination at the individual or institutional level, and studies of structural discrimination in stroke care are scant.

Objective

To examine differences in hospitals' likelihood of adopting stroke care certification between historically underserved and general communities.

Design, Setting, and Participants

This study combined a data set of hospital stroke certification from all general acute nonfederal hospitals in the continental US from January 1, 2009, to December 31, 2019, with national, hospital, and census data to define historically underserved communities by racial and ethnic composition, income distribution, and rurality. For all categories except rurality, communities were categorized by the composition and degree of segregation of each characteristic. Cox proportional hazard models were then estimated to compare the hazard of adopting stroke care certification between historically underserved and general communities, adjusting for population size and hospital bed capacity. Data were analyzed from June 2021 to April 2022.

Main Outcomes and Measures

Hospitals' likelihood of adopting stroke care certification.

Results

A total of 4984 hospitals were included. From 2009 to 2019, the total number of hospitals with stroke certification grew from 961 to 1763. Hospitals serving Black, racially segregated communities had the highest hazard of adopting stroke care certification (hazard ratio [HR], 1.67; 95% CI, 1.41-1.97) in models not accounting for population size, but their hazard was 26% lower than among those serving non-Black, racially segregated communities (HR, 0.74; 95% CI, 0.62-0.89) in models controlling for population and hospital size. Adoption hazard was lower in low-income communities compared with high-income communities, regardless of their level of economic segregation, and rural hospitals were much less likely to adopt any level of stroke care certification relative to urban hospitals (HR, 0.43; 95% CI, 0.35-0.51).

Conclusions and Relevance

In this analysis of stroke certification adoption across acute care hospitals in the US from 2009 to 2019, hospitals in low-income and rural communities had a lower likelihood of receiving stroke certification than hospitals in general communities. Hospitals operating in Black, racially segregated communities had the highest likelihood of adopting stroke care, but because these communities had the largest population, patients in these communities had the lowest likelihood of access to stroke-certified hospitals when the model controlled for population size. These findings provide empirical evidence that the provision of acute neurological services is structurally inequitable across historically underserved communities.

Developing a conceptual model for studying various points of delays and underlying factors in the emergency healthcare system

To review various literature related to emergency healthcarerelated delays and synthesize a conceptual framework for future research. Critical Interpretative Synthesis is employed to analyze and develop themes from selected articles. A total of 25 articles were selected for analysis after the careful selection process. Diseases including acute heart disease, stroke, pneumonia, infections, and gastrointestinal disorders were included. During analysis, three major phases of delays emerged: pre-hospital delay, inhospital delay, and ambulance off-load delay. Various factors, including socioeconomic factors, health system factors, organizational level factors, etc., are related to delays in emergency care settings. The model evolved from this literature analysis is similar to the 3 delays model. This review identified three significant delay segments related to emergency health care management.

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.

Central Venous Catheter Adverse Events Are not Associated with Crowding Indicators

Objective

Crowding in the emergency department (ED) impacts a number of important quality and safety metrics. We studied ED crowding measures associated with adverse events (AE) resulting from central venous catheters (CVC) inserted in the ED, as well as the relationship between crowding and the frequency of CVC insertions in an ED cohort admitted to the intensive care unit (ICU).

Methods

We conducted a retrospective observational study from 2008–2010 in an academic tertiary care center. Participants undergoing CVC in the ED or admitted to an ICU were categorized by quartile based on the following: National Emergency Department Overcrowding Scale (NEDOCS); waiting room patients (WR); ED patients awaiting inpatient beds (boarders); and ED occupancy (EDO). Main outcomes were the occurrence of an AE during CVC insertion in the ED, and deferred procedures assessed by frequency of CVC insertions in ED patients admitted to the ICU.

Results

Of 2,284 ED patients who had a CVC inserted, 293 (13%) suffered an AE. There was no association between AEs from ED CVCs and crowding scales when comparing the highest crowding level or quartile to all other quartiles: NEDOCS (dangerous crowding [13.1%] vs other levels [13.0%], P = 0.98); number of WR patients (14.0% vs 12.7%, P = 0.81); EDO (13.0% vs 12.9%, P = 0.99); and number of boarding patients (12.0% vs 13.3%), P = 0.21). In a cohort of ED patients admitted to the ICU, there was no association between CVC placement rates in the ED and crowding scales comparing the highest vs all other quartiles: NEDOCS (dangerous crowding 16% vs all others 16%, P = 0.97); WR patients (16% vs 16%, P = 0.82), EDO (15% vs. 17%, P = 0.15); and number of boarding patients (17% vs 16%, P = 0.08).

Conclusion

In a large, academic tertiary-care center, frequency of CVC insertion in the ED and related AEs were not associated with measures of crowding. These findings add to the evidence that the negative effects of crowding, which impact all ED patients and measures of ED performance, are less likely to impair the delivery of prioritized time-critical interventions.

Impact of ED Organization with a Holding Area and a Dedicated Team on the Adherence to International Guidelines for Patients with Acute Pulmonary Embolism: Experience of an Emergency Department Organized in Areas of Intensity of Care

Background: Adherence to guidelines by physicians of an emergency department (ED) depends on many factors: guideline and environmental factors; patient and practitioner characteristics; the social-political context. We focused on the impact of the environmental influence and of the patients’ characteristics on adherence to the guidelines. It is our intention to demonstrate how environmental factors such as ED organization more affect adherence to guidelines than the patient’s clinical presentation, even in a clinically insidious disease such as pulmonary embolism (PE). Methods: A single-center observational study was carried out on all patients who were seen at our Department of Emergency and Acceptance from 1 January to 31 December 2017 for PE. For the assessment of adherence to guidelines, we used the European guidelines 2014 and analyzed adherence to the correct use of clinical decision rule (CDR as Wells, Geneva, and YEARS); the correct initiation of heparin therapy; and the management of patients at high risk for short-term mortality. The primary endpoint of our study was to determine whether adherence to the guidelines as a whole depends on patients’ management in a holding area. The secondary objective was to determine whether adherence to the guidelines depended on patient characteristics such as the presence of typical symptoms or severe clinical features (massive pulmonary embolism; organ damage). Results: There were significant differences between patients who passed through OBI and those who did not, in terms of both administration of heparin therapy alone (p = 0.007) and the composite endpoints of heparin therapy initiation and observation/monitoring (p = 0.004), as indicated by the guidelines. For the subgroups of patients with massive PE, organ damage, and typical symptoms, there was no greater adherence to the decision making, administration of heparin therapy alone, and the endpoints of heparin therapy initiation and guideline-based observation/monitoring. Conclusions: Patients managed in an ED holding area were managed more in accordance with the guidelines than those who were managed only in the visiting ED rooms and directly hospitalized from there.

Impact of Emergency Department Crowding on Delays in Acute Stroke Care

Introduction

Delays in identification and treatment of acute stroke contribute to significant morbidity and mortality. Multiple clinical factors have been associated with delays in acute stroke care. We aimed to determine the relationship between emergency department (ED) crowding and the delivery of timely emergency stroke care.

Methods

We used prospectively collected data from our institutional Get with the Guidelines-Stroke registry to identify consecutive acute ischemic stroke patients presenting to our urban academic ED from July 2016–August 2018. We used capacity logs to determine the degree of ED crowding at the time of patients’ presentation and classified them as ordinal variables (normal, high, and severe capacity constraints). Outcomes of interest were door-to-imaging time (DIT) among patients potentially eligible for alteplase or endovascular therapy on presentation, door-to-needle time (DTN) for alteplase delivery, and door-to-groin puncture (DTP) times for endovascular therapy. Bivariate comparisons were made using t-tests, chi-square, and Wilcoxon rank-sum tests as appropriate. We used regression models to examine the relationship after accounting for patient demographics, transfer status, arrival mode, and initial stroke severity by the National Institutes of Health Stroke Scale.

Results

Of the 1379 patients with ischemic stroke presenting during the study period, 1081 (78%) presented at times of normal capacity, 203 (15%) during high ED crowding, and 94 (7%) during severe crowding. Median DIT was 26 minutes (interquartile range [IQR] 17–52); DTN time was 43 minutes (IQR 31–59); and median DTP was 58.5 minutes (IQR 56.5–100). Treatment times were not significantly different during periods of higher ED utilization in bivariate or in multivariable testing.

Conclusion

In our single institution analysis, we found no significant delays in stroke care delivery associated with increased ED crowding. This finding suggests that robust processes of care may enable continued high-quality acute care delivery, even during times with an increased capacity burden.

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.

Emergency department crowding: A systematic review of causes, consequences and solutions

BACKGROUND

Emergency department crowding is a major global healthcare issue. There is much debate as to the causes of the phenomenon, leading to difficulties in developing successful, targeted solutions.

AIM

The aim of this systematic review was to critically analyse and summarise the findings of peer-reviewed research studies investigating the causes and consequences of, and solutions to, emergency department crowding.

METHOD

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. A structured search of four databases (Medline, CINAHL, EMBASE and Web of Science) was undertaken to identify peer-reviewed research publications aimed at investigating the causes or consequences of, or solutions to, emergency department crowding, published between January 2000 and June 2018. Two reviewers used validated critical appraisal tools to independently assess the quality of the studies. The study protocol was registered with the International prospective register of systematic reviews (PROSPERO 2017: CRD42017073439).

RESULTS

From 4,131 identified studies and 162 full text reviews, 102 studies met the inclusion criteria. The majority were retrospective cohort studies, with the greatest proportion (51%) trialling or modelling potential solutions to emergency department crowding. Fourteen studies examined causes and 40 investigated consequences. Two studies looked at both causes and consequences, and two investigated causes and solutions.

CONCLUSIONS

The negative consequences of ED crowding are well established, including poorer patient outcomes and the inability of staff to adhere to guideline-recommended treatment. This review identified a mismatch between causes and solutions. The majority of identified causes related to the number and type of people attending ED and timely discharge from ED, while reported solutions focused on efficient patient flow within the ED. Solutions aimed at the introduction of whole-of-system initiatives to meet timed patient disposition targets, as well as extended hours of primary care, demonstrated promising outcomes. While the review identified increased presentations by the elderly with complex and chronic conditions as an emerging and widespread driver of crowding, more research is required to isolate the precise local factors leading to ED crowding, with system-wide solutions tailored to address identified causes.

Effect of Emergency Department and ICU Occupancy on Admission Decisions and Outcomes for Critically Ill Patients

OBJECTIVES

ICU admission delays can negatively affect patient outcomes, but emergency department volume and boarding times may also affect these decisions and associated patient outcomes. We sought to investigate the effect of emergency department and ICU capacity strain on ICU admission decisions and to examine the effect of emergency department boarding time of critically ill patients on in-hospital mortality.

DESIGN

A retrospective cohort study.

SETTING

Single academic tertiary care hospital.

PATIENTS

Adult critically ill emergency department patients for whom a consult for medical ICU admission was requested, over a 21-month period.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Patient data, including severity of illness (Mortality Probability Model III on Admission), outcomes of mortality and persistent organ dysfunction, and hourly census reports for the emergency department, for all ICUs and all adult wards were compiled. A total of 854 emergency department requests for ICU admission were logged, with 455 (53.3%) as "accept" and 399 (46.7%) as "deny" cases, with median emergency department boarding times 4.2 hours (interquartile range, 2.8-6.3 hr) and 11.7 hours (3.2-20.3 hr) and similar rates of persistent organ dysfunction and/or death 41.5% and 44.6%, respectively. Those accepted were younger (mean ± SD, 61 ± 17 vs 65 ± 18 yr) and more severely ill (median Mortality Probability Model III on Admission score, 15.3% [7.0-29.5%] vs 13.4% [6.3-25.2%]) than those denied admission. In the multivariable model, a full medical ICU was the only hospital-level factor significantly associated with a lower probability of ICU acceptance (odds ratio, 0.55 [95% CI, 0.37-0.81]). Using propensity score analysis to account for imbalances in baseline characteristics between those accepted or denied for ICU admission, longer emergency department boarding time after consult was associated with higher odds of mortality and persistent organ dysfunction (odds ratio, 1.77 [1.07-2.95]/log10 hour increase).

CONCLUSIONS

ICU admission decisions for critically ill emergency department patients are affected by medical ICU bed availability, though higher emergency department volume and other ICU occupancy did not play a role. Prolonged emergency department boarding times were associated with worse patient outcomes, suggesting a need for improved throughput and targeted care for patients awaiting ICU admission.