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J Korean Med Sci.  2016 Aug;31(8):1331-1336. 10.3346/jkms.2016.31.8.1331.

Emergency Department Crowding Disparity: a Nationwide Cross-Sectional Study

Affiliations
  • 1Department of Emergency Medicine, Samsung Medical Center, Seoul, Korea.
  • 2Department of Emergency Medicine, Seoul National University Hospital, Seoul, Korea. arendt75@gmail.com
  • 3Department of Emergency Medicine, Gachon University Gil Hospital, Incheon, Korea.
  • 4Laboratory of Emergency Medical Service, Biomedical Research Institute, Seoul National University Hospital, Seoul, Korea.

Abstract

In this study, we evaluated national differences in emergency department (ED) crowding to identify factors significantly associated with crowding in institutes and communities across Korea. This was a cross-sectional nationwide observational study using data abstracted from the National Emergency Department Information System (NEDIS). We calculated mean occupancy rates to quantify ED crowding status and divided EDs into three groups according to their occupancy rates (cutoffs: 0.5 and 1.0). Factors potentially related to ED crowding were collected from the NEDIS. We performed a multivariate regression analysis to identify variables significantly associated with ED crowding. A total of 120 EDs were included in the final analysis. Of these, 73 were categorized as 'low crowded' (LC, occupancy rate < 0.50), 37 as 'middle crowded' (MC, 0.50 ≤ occupancy rate < 1.00), 10 EDs as 'high crowded' (HC, 1.00 ≤ occupancy rate). The mean ED occupancy rate varied widely, from 0.06 to 2.33. The median value was 0.39 with interquartile ranges (IQRs) from 0.20 to 0.71. Multivariate analysis revealed that after adjustment, ED crowding was significantly associated with the number of visits, percentage of patients referred, number of nurses, and ED disposition. This nationwide study observed significant variety in ED crowding. Several input, throughput, and output factors were associated with crowding.

Keyword

Emergency Service; Hospital; Crowding; National Health Program

MeSH Terms

Adolescent
Adult
Aged
Child
Child, Preschool
Cross-Sectional Studies
Databases, Factual
Emergency Service, Hospital/*statistics & numerical data
Female
Hospitalization
Humans
Male
Middle Aged
Nurses/statistics & numerical data
Patient Transfer/statistics & numerical data
Republic of Korea
Young Adult
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