Correlation of Measures of Patient Acuity With Measures of Crowding in a Pediatric Emergency Department

Pediatr Emerg Care. 2011 Aug;27(8):706-9. doi: 10.1097/PEC.0b013e318226c7dd.

Abstract

Objective: Emergency department (ED) crowding is an increasingly common problem in the United States. Crowding can lead to ED closure and diversion, poor patient satisfaction, and patient safety issues. The purpose of this study was to examine measures of ED census and measures of crowding to determine if a correlation exists in a pediatric ED setting.

Methods: Arkansas Children's Hospital is a major pediatric referral center. Measures of ED acuity (including total census, admission rate, total number of admissions, and proportion of triage category nonurgent patients) and measures of throughput (left-without-being-seen [LWBS] rate and ED length of stay [LOS]) data for 11 years (1996-2006) were plotted, and correlation coefficients were calculated.

Results: Annual ED census varied between 35,415 and 40,711 during the 11-year study period. The total number of admissions increased from 4179 in 1996 to 6539 in 2006. When total census was plotted against LWBS rate and ED LOS, a poor correlation was found (R² = 0.007 for total census vs LWBS rate). However, a strong correlation was found when the relationship between the total number of admissions and LWBS rate was examined (R² = 0.89). Similarly, a strong relationship between the admission rate and LWBS rate was seen (R² = 0.75). In addition, a strong correlation was seen between admissions (total and percentage) versus ED LOS.

Conclusions: There is a strong correlation between the number of patients admitted and measures of overcrowding in this pediatric ED, but there is a poor correlation between the total census and overcrowding measures. Targeting process improvement on hospital-wide patient flow may help reduce ED crowding.

MeSH terms

  • Arkansas
  • Child
  • Crowding*
  • Emergency Service, Hospital / statistics & numerical data*
  • Health Services Accessibility
  • Humans
  • Quality of Health Care
  • Triage / statistics & numerical data*