Health policy and clinical practice/original researchCrowding Delays Treatment and Lengthens Emergency Department Length of Stay, Even Among High-Acuity Patients
Introduction
Length of stay is an important measure of quality of care in the emergency department (ED).1, 2, 3 Several studies have found that crowding is associated with increased ED length of stay.4, 5 Rathlev et al4 observed that daily ED length of stay was positively associated with the hospital occupancy rate and number of emergency admissions at their institution. Asaro et al5 found that at their ED, crowding factors increased wait time and boarding time but not treatment time. In contrast, Schull et al6 investigated the effect of the number of low-complexity patients on the length of stay of higher-complexity patients treated at EDs in Ontario, Canada, and found that increasing numbers of low-complexity patients did not significantly lengthen the wait time or ED length of stay of higher-complexity patients.
Many hospital-based EDs across the country have been struggling with crowding for more than a decade.7, 8 Until recently, there were few objective measures of crowding and modest evidence of the negative effects of crowding on patient care and outcomes. However, advances in crowding measures during the past 5 years have resulted in a growing number of studies that quantify the negative consequences of crowding, especially on delays in care for time-sensitive conditions.7, 9, 10, 11, 12, 13 One of the major limitations of crowding studies conducted to date is that they measure crowding in a static way, either at a point in time (eg, patient arrival) or by averaging crowding during a specific interval (eg, a shift). However, many studies have shown that crowding is dynamic and can fluctuate substantially during the course of a patient's ED stay.14, 15, 16, 17
The purpose of this study was to quantify the relationship between crowding and ED length of stay at 4 hospital EDs and to compare the effect across EDs and patient acuity levels. We measured crowding at regular intervals throughout each patient's ED stay and estimated the cumulative effect of crowding on ED waiting room time, treatment time, and boarding time, using discrete-time survival analysis, which allowed us to include time-varying crowding covariates. We stratified the analysis by shift, site, and patient acuity and determined whether crowding, adjusted for other factors, significantly delayed completion of each phase of ED care.
Section snippets
Study Design
This investigation was based on a retrospective cohort design that included all ED visits to one of 4 hospital EDs during a 1-year period. Patient visit information was abstracted from the information system of each ED and combined with inpatient medicine occupancy and ED staffing data. The institutional review board of each site approved the study by expedited review.
Setting
The selection of the 4 study sites was based on previous collaboration and feasibility of aggregating electronic medical record
Results
The patient populations of the 4 study sites differ substantially from one another, particularly in terms of insurance status, admission rate, and acuity level (Table 2). Site A treats more patients who are uninsured (37%) compared with the other sites (range 5% to 21%). Site D admits proportionately fewer patients (19%) than the other EDs (range 23% to 30%). Site D also treats fewer highly acute patients (ie, Emergency Severity Index levels 1 and 2) (13%) compared with the other sites (range
Limitations
The results of this study must be interpreted in the context of the following limitations. First, this study did not attempt to connect the different phases of care and determine how the completion of care in one phase affects the completion of care in another.
Second, our models did not include all potential covariates that affect ED length of stay, such as orders for diagnostic tests, treatments, or specialty consultations. Although overall treatment times were not significantly delayed by
Discussion
To our knowledge, this is the first study to measure crowding dynamically and to examine its effect on ED length of stay. We found that crowding was associated with substantial delays in ED length of stay across 4 ED sites. Moreover, crowding prolonged the ED length of stay of high-acuity level 2 patients. Output factors, such as the number of patients boarding and the inpatient medicine occupancy rate, were associated with large delays in ED care. Crowding negatively affected ED patients'
References (43)
- et al.
Time series analysis of variables associated with daily mean emergency department length of stay
Ann Emerg Med
(2007) - et al.
Emergency department crowding is associated with poor care for patients with severe pain
Ann Emerg Med
(2008) - et al.
The impact of emergency department crowding measures on time to antibiotics for patients with community-acquired pneumonia
Ann Emerg Med
(2007) - et al.
Attrition in longitudinal studies: how to deal with missing data
J Clin Epidemiol
(2002) - et al.
Determinants of patient satisfaction and willingness to return with emergency care
Ann Emerg Med
(2000) - et al.
Validating a model of patient satisfaction with emergency care
Ann Emerg Med
(2001) - et al.
Patient satisfaction in the emergency department: a review of the literature and implications for practice
J Emerg Med
(2004) - et al.
Factors associated with longer ED lengths of stay
Am J Emerg Med
(2007) Measuring crowding: time for a paradigm shift
Acad Emerg Med
(2006)- et al.
Optimizing Patient Flow: Moving Patients Smoothly Through Acute Care Settings
(2003)
The Joint Commission requirements
The impact of input and output factors on emergency department throughput
Acad Emerg Med
The effect of low-complexity patients on emergency department waiting times
Ann Emerg Med
Hospital-Based Emergency Care: At the Breaking Point
Hospital Emergency Departments: Crowded Conditions Vary Among Hospitals and Communities
The effect of emergency department crowding on clinically oriented outcomes
Acad Emerg Med
Systematic review of emergency department crowding: causes, effects and solutions
Ann Emerg Med
Effect of emergency department crowding on time to antibiotics in patients admitted with community-acquired pneumonia
Ann Emerg Med
The challenge of predicting demand for emergency department services
Acad Emerg Med
The emergency department occupancy rate: a simple measure of emergency department crowding?
Ann Emerg Med
Advanced statistics: developing a formal model of emergency department census and defining operational efficiency
Acad Emerg Med
Cited by (262)
Forecasting emergency department occupancy with advanced machine learning models and multivariable input
2024, International Journal of ForecastingRepatriation of Transferred Patients: A Solution for Hospital Capacity Concerns?
2023, Joint Commission Journal on Quality and Patient SafetyLeaving Without Being Seen From the Pediatric Emergency Department: A New Baseline
2023, Journal of Emergency MedicineThe effect of increased emergency department demand on throughput times and disposition status for pediatric psychiatric patients
2023, American Journal of Emergency MedicineImpact of iodinated contrast allergies on emergency department operations
2022, American Journal of Emergency Medicine
Provide feedback on this article at the journal's Web site, www.annemergmed.com.
Supervising editor: Donald M. Yealy, MD
Author contributions: All of the authors were involved in the study concept and design, drafting of the article, and critical revision of the article for important intellectual content. The objectives, data collection protocol, review of the analysis, and findings were discussed by teleconference calls with all of the investigators. MLM, JSD, JL, and DA were responsible for acquiring the data from their sites and obtaining institutional review board approval. RD performed the data analysis under the supervision of MLM and SLZ. However, all of the authors had input into the variables considered for the analysis and how it was conducted. MLM drafted the article, and all authors contributed substantially to its revision. MLM takes responsibility for the paper as a whole.
Funding and support: By Annals policy, all authors are required to disclose any and all commercial, financial, and other relationships in any way related to the subject of this article that might create any potential conflict of interest. The authors have stated that no such relationships exist. See the Manuscript Submission Agreement in this issue for examples of specific conflicts covered by this statement.
Earn CME Credit: Continuing Medical Education is available for this article at: www.ACEP-EMedHome.com.
Publication date: Available online May 6, 2009.