Article

The Effect of Emergency Department Crowding on Clinically Oriented Outcomes

Department of Emergency Medicine, Albert Einstein College of Medicine, Bronx, NY, USA.
Academic Emergency Medicine (Impact Factor: 2.2). 12/2008; 16(1):1-10. DOI: 10.1111/j.1553-2712.2008.00295.x
Source: PubMed

ABSTRACT An Institute of Medicine (IOM) report defines six domains of quality of care: safety, patient-centeredness, timeliness, efficiency, effectiveness, and equity. The effect of emergency department (ED) crowding on these domains of quality has not been comprehensively evaluated.
The objective was to review the medical literature addressing the effects of ED crowding on clinically oriented outcomes (COOs).
We reviewed the English-language literature for the years 1989-2007 for case series, cohort studies, and clinical trials addressing crowding's effects on COOs. Keywords searched included "ED crowding,"ED overcrowding,"mortality,"time to treatment,"patient satisfaction,"quality of care," and others.
A total of 369 articles were identified, of which 41 were kept for inclusion. Study quality was modest; most articles reflected observational work performed at a single institution. There were no randomized controlled trials. ED crowding is associated with an increased risk of in-hospital mortality, longer times to treatment for patients with pneumonia or acute pain, and a higher probability of leaving the ED against medical advice or without being seen. Crowding is not associated with delays in reperfusion for patients with ST-elevation myocardial infarction. Insufficient data were available to draw conclusions on crowding's effects on patient satisfaction and other quality endpoints.
A growing body of data suggests that ED crowding is associated both with objective clinical endpoints, such as mortality, as well as clinically important processes of care, such as time to treatment for patients with time-sensitive conditions such as pneumonia. At least two domains of quality of care, safety and timeliness, are compromised by ED crowding.

Download full-text

Full-text

Available from: Jesse Pines, Jun 24, 2015
1 Follower
 · 
176 Views
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Objectives To describe and compare characteristics and process outcomes of patient presentations made to a public hospital Emergency Department (ED) for mental health (MH) and nonmental health (NMH) diagnoses. Methods This was a descriptive, retrospective cross-sectional study of patients who presented to an Australian hospital ED between September 2011 and September 2012. Demographic, clinical and outcomes data were extracted from the ED information system. MH presentations were compared to NMH presentations. Results Nearly 5% of the 66,678 ED presentations were classified as MH. Compared to the NMH group, a lower proportion in the MH group were seen by a physician within the recommended time frame (39.1% vs. 42.1%, p<0.001); had a higher admission rate (36.6% vs 20.1%, p<0.001); shorter ED length of stay (LoS) if admitted (369 vs, 490 mins, p<0.001) and longer ED LoS if not admitted (241 vs.187 mins, p<0.001). Conclusion Time constraints in the busy ED environment are a potential barrier to the delivery of care for all patients who have the right to timely access to health care. Targeted improvements at the front end of the ED system and output processes between ED, community and inpatient admission are recommended for this site.
    International emergency nursing 01/2013; 22(3). DOI:10.1016/j.ienj.2013.12.002 · 0.72 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: With the rapid outstripping of limited health care resources by the demands on hospital care, it is of critical importance to find more effective and efficient methods of managing care. Our research addresses the problem of emergency department (ED) crowding by building classification models using various types of pre-admission information to help predict the hospital admission of individual patients. We have developed a framework of hospital admission prediction and proposed two novel approaches that capture semantic information in chief complaints to enhance prediction. Our experiments on an ED data set demonstrate that our proposed models outperformed several benchmark methods for admission prediction. These models can potentially be used as decision support tools at hospitals to improve ED throughput rate and enhance patient care.
    12/2012; 1(4). DOI:10.1007/s13721-012-0014-6
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Using a simplified model of an emergency department (ED), we illustrate a 2-step methodology for determining the optimal mix of resources (beds, clerks, triage nurses, registered nurses, and physicians) for different arrival rates. These arrival rates cover the range of annual visit volumes typically observed in EDs in the United States. We also use the model to test a widely recommended process change in EDs: bedside registration. Rather than perform registration immediately after triage, registration is now performed only after the patient is placed in an ED bed and assessed by a nurse and physician. Our results show that bedside registration is efficient only when sufficient beds are available; when an ED is crowded and bed availability is low it actually leads to an increased length of stay. We view our model as a first step in the development of a more elaborate, multiple-acuity ED model.
    Simulation Conference (WSC), Proceedings of the 2009 Winter; 01/2010