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.
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

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.
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

PURPOSE: In this study, we determined the long-term effects of the Independent Capacity Protocol (ICP), in which the emergency department (ED) is temporarily used to stabilize patients, followed by transfer of patients to other facilities when necessary, on crowding metrics. MATERIALS AND METHODS: A before and after study design was used to determine the effects of the ICP on patient outcomes in an academic, urban, tertiary care hospital. The ICP was introduced on July 1, 2007 and the before period included patients presenting to the ED from January 1, 2005 to June 31, 2007. The after period began three months after implementing the ICP from October 1, 2007 to December 31, 2010. The main outcomes were the ED length of stay (LOS) and the total hospital LOS of admitted patients. The mean number of monthly ED visits and the rate of inter-facility transfers between emergency departments were also determined. A piecewise regression analysis, according to observation time intervals, was used to determine the effect of the ICP on the outcomes. RESULTS: During the study period the number of ED visits significantly increased. The intercept for overall ED LOS after intervention from the before-period decreased from 8.51 to 7.98 hours [difference 0.52, 95% confidence interval (CI): 0.04 to 1.01] (p=0.03), and the slope decreased from -0.0110 to -0.0179 hour/week (difference 0.0069, 95% CI: 0.0012 to 0.0125) (p=0.02). CONCLUSION: Implementation of the ICP was associated with a sustainable reduction in ED LOS and time to admission over a six-year period.
Aged ; *Clinical Protocols ; *Crowding ; Efficiency, Organizational ; Emergency Service, Hospital/*organization & administration/utilization ; Female ; Hospital Planning/*methods ; Hospitals, Urban/*organization & administration/utilization ; Humans ; Length of Stay/*statistics & numerical data ; Male ; Outcome and Process Assessment (Health Care) ; Patient Admission/statistics & numerical data ; Patient Transfer/statistics & numerical data ; Regression Analysis ; Time ; Time Factors ; Triage