Original ContributionNational ED crowding and hospital quality: results from the 2013 Hospital Compare data
Introduction
Emergency department (ED) crowding is a common issue in many hospitals in the United States and around the world [1]. Nationally, the number of ED visits is increasing faster than population growth, whereas patients presenting to EDs receive more resource intensive care than in previous years [2], [3]. Increased ED use has negative effects on a variety of ED processes and patient-oriented outcomes. Emergency department crowding is associated with poorer pain care [4], delayed antibiotics in pneumonia [5], [6], increased in-hospital mortality [7], [8], and an increased likelihood of patients leaving without being seen [9], [10], [11].
Recently, there has been an increased focus on quality measurement and improvement in US hospitals. Organizations including governmental agencies, such as the Center for Medicare and Medicaid Services (CMS) and nongovernmental entities, such as the National Quality Forum, have supported quality measures, including several measures of ED crowding, with the goal of improving care. Measurement data are made publicly available on a Department of Health and Human Services (HHS) website called Hospital Compare (www.medicare.gov/hospitalcompare/) and includes data from a variety of sources, including patient-completed surveys, readmission, complication, and mortality rates in hospitals and both timeliness and effectiveness measures. In March 2013, Hospital Compare publicly released ED crowding data for thousands of hospitals for the first time in the United States in the form of several measures: left-without-being-seen rates, separate measures of ED length of stay for discharged and admitted patients, and ED boarding times and waiting times.
In this study, we explored Hospital Compare data related to ED crowding measures in US hospitals in a variety of ways. First, we assessed whether there were measurable hospital factors associated with hospitals that reported the measures. Second, we investigated whether an assessment of hospital quality in the popular press (US News Best Hospitals 2012-2013) was associated with differences in ED crowding. Finally, we explored the relationship among crowding measures and the relationship between ED crowding measures and other quality metrics, specifically process and outcome measures.
Section snippets
Study design and setting
We conducted an ecological study using data from the downloadable Hospital Compare data files found on the Medicare Hospital Compare website. Our goal was to explore data from the hospital-level ED crowding measures: median time from ED arrival to ED departure for admitted ED, admit decision time to ED departure time for admitted patients, median time from ED arrival to ED departure for discharged ED patients, time from door to diagnostic evaluation by a qualified medical professional, and
Average US ED crowding levels
The national median for “median time from ED arrival to ED departure for admitted ED patients” was 262 minutes (IQR, 215-326), whereas the national median for the time between decision to admit and ED departure time for admitted patients was 88 minutes (IQR, 60-128). For discharged patients, the national median time between arrival and discharge was 139 minutes (IQR, 114-168). The national median time between ED arrival and diagnostic evaluation by a qualified medical professional was 30
Discussion
From these data, we confirm that ED crowding is a common national phenomenon in US hospitals, with the average US patient spending more than 4 hours in the ED before being transferred to an in-patient bed. However, crowding varies to a large degree between hospitals, where some EDs are more efficient with shorter lengths of stay and lower left-without-being-seen rates. These data are also similar to data reported in other national surveys, such as the National Hospital Ambulatory Care Survey,
Limitations
This study has several important limitations. As an exploratory ecological study, concluding any causal relationships between variables is not possible. In addition, because the associations did not adjust for other factors, there is a reasonable likelihood that many of the results may be confounded. In addition, the measures we investigated were influenced by significant reporting bias, with smaller rural hospitals potentially underrepresented. Furthermore, many of these measures were not
Conclusion
This study represents the first exploratory investigation of Hospital Compare’s ED crowding metrics. We demonstrate considerable variation in reporting rates across hospital types and regional differences in reporting as well as variation in the measures themselves. Emergency department crowding was related to several measures of in-patient quality, which further suggests that ED crowding should be a hospital-wide priority for quality improvement efforts.
The following are the supplementary
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