Elsevier

Annals of Emergency Medicine

Volume 60, Issue 6, December 2012, Pages 679-686.e3
Annals of Emergency Medicine

Health policy/original research
National Trends in Emergency Department Occupancy, 2001 to 2008: Effect of Inpatient Admissions Versus Emergency Department Practice Intensity

https://doi.org/10.1016/j.annemergmed.2012.05.014Get rights and content

Study objective

We evaluate recent trends in emergency department (ED) crowding and its potential causes by analyzing ED occupancy, a proxy measure for ED crowding.

Methods

We analyzed data from the annual National Hospital Ambulatory Medical Care Surveys from 2001 to 2008. The surveys abstract patient records from a national sample of hospital EDs to generate nationally representative estimates of visits. We used time of ED arrival and length of ED visit to calculate mean and hourly ED occupancy.

Results

During the 8-year study period, the number of ED visits increased by 1.9% per year (95% confidence interval 1.2% to 2.5%), a rate 60% faster than population growth. Mean occupancy increased even more rapidly, at 3.1% per year (95% confidence interval 2.3% to 3.8%), or 27% during the 8 study years. Among potential factors associated with crowding, the use of advanced imaging increased most, by 140%. But advanced imaging had a smaller effect on the occupancy trend than other more common throughput factors, such as the use of intravenous fluids and blood tests, the performance of any clinical procedure, and the mention of 2 or more medications. Of patient characteristics, Medicare payer status and the age group 45 to 64 years accounted for small disproportionate increases in occupancy.

Conclusion

Despite repeated calls for action, ED crowding is getting worse. Sociodemographic changes account for some of the increase, but practice intensity is the principal factor driving increasing occupancy levels. Although hospital admission generated longer ED stays than any other factor, it did not influence the steep trend in occupancy.

Introduction

Since 1992, the number of emergency department (ED) visits in the United States has increased at roughly twice the rate of the population growth,1, 2 whereas the number of nonrural EDs has declined by 27%.3 In 2006, the Institute of Medicine conducted a comprehensive review of hospital-based emergency care and concluded that it is “at the breaking point.”4 The Institute of Medicine cited several factors that contribute to ED crowding, including relentless growth in ED visits, a shortage of on-call specialists, and lengthy delays before admitted ED patients are moved to inpatient beds, a practice commonly referred to as “boarding.” Similar conclusions were reached by the US General Accountability Office5, 6 in 2003 and 2009.

ED crowding contributes to increased waiting times and dissatisfaction with care.7 It has also been linked to adverse outcomes, including delays in the provision of critical treatments such as antibiotics for pneumonia and analgesia for acute, painful conditions.8, 9, 10 Crowding has been associated with higher rates of medical errors, more frequent complications, and increased mortality rates among critically ill patients.8, 11, 12, 13, 14, 15, 16 When ED crowding reaches crisis levels, many hospitals opt to divert inbound ambulances, a practice that contributes to community-wide delays in care for acute myocardial infarction and perhaps other time-critical conditions.15, 16, 17

Recently, researchers have identified the ED occupancy rate—defined as the number of patients in an ED at a single point in time divided by the number of standard treatment spaces—as a simple and valid measure of ED crowding.18, 19

We explored changes in mean ED occupancy from 2001 to 2008 in the United States, using a nationally representative sample of ED visits. We hypothesized that mean ED occupancy was increasing even faster than the annual increase in ED visits, principally because of longer stays for admitted patients.

Section snippets

Theoretical Model of the Problem

Because crowding is a property of individual EDs at a point in time, the ideal causal model would use the ED as the unit of analysis, crowding as the dependent variable, and various ED-level characteristics as potential causal factors (eg, teaching hospital status, annual ED volume, number of ED treatment spaces, percentage of Medicaid visits). However, because the identity and characteristics of individual EDs are not publicly disclosed in national surveys, we used mean hourly occupancy

Results

During the 8-year study interval, hourly levels of national ED occupancy cycled in a sinusoidal pattern similar to the pattern observed in studies of single EDs.23 Following a daily nadir at around 7 am, mean levels of the national ED occupancy increased sharply at midmorning and peaked around 8 pm, an increase sometimes called the daily surge (Figure 1). The daily surge in ED occupancy lags the surge in ED arrivals by approximately 2 hours. Averaged over all hours and all study years (the

Limitations

The absence of ED identifiers in the public-use data set prevented us from assigning causes in a multivariable analysis with ED occupancy as the dependent variable. Furthermore, this analysis is subject to the “atomistic fallacy,” which describes the potential bias that can occur when individual-level data are used to make inferences at the group level.28 It is possible that long visit duration and high resource use occurred in different hospitals, leading to an overestimate of the strength of

Discussion

We hypothesized that increased boarding of hospital admissions in the ED would be the most important cause of increasing levels of occupancy. This was not the case. Instead, the factors most strongly associated with growth in ED occupancy were throughput factors, most notably an increasing level of both diagnostic and treatment intensity. Although the time required to perform clinical tests and interventions did not change out of proportion, and even decreased somewhat in the case of advanced

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    Supervising editor: Brendan G. Carr, MD, MS

    Author contributions: SRP, MTH, and ALK conceived the study. SRP obtained the data, developed the study design, and performed the analysis. SRP wrote the initial draft, and JMP, MTH, and ALK contributed substantially to its revision. SRP 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 as per ICMJE conflict of interest guidelines (see www.icmje.org). The authors have stated that no such relationships exist. Dr. Pitts performed this work under contract with the Emergency Care Coordination Center, Office of the Assistant Secretary for Preparedness and Response.

    Publication date: Available online June 20, 2012.

    Please see page 680 for the Editor's Capsule Summary of this article.

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    Current affiliation: Provider Compliance Group, Centers for Medicare and Medicaid Services.

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