Analysis of factors influencing length of stay in the emergency department.
OBJECTIVE
Length of stay (LOS) is a key measure of emergency department (ED) throughput and a marker of overcrowding. Time studies that assess key ED processes will help clarify the causes of patient care delays and prolonged LOS. The objectives of this study were to identify and quantify the principal ED patient care time intervals, and to measure the impact of important service processes (laboratory testing, imaging and consultation) on LOS for patients in different triage levels.


METHODS
In this retrospective review, conducted at a large urban tertiary care teaching hospital and trauma centre, investigators reviewed the records of 1047 consecutive patients treated during a continuous 7-day period in January 1999. Key data were recorded, including patient characteristics, ED process times, tests performed, consultations and overall ED LOS. Of the 1047 patient records, 153 (14.6%) were excluded from detailed analysis because of incomplete documentation. Process times were determined and stratified by triage level, using the Canadian Emergency Department Triage and Acuity Scale (CTAS). Multiple linear regression analysis was performed to determine which factors were most strongly associated with prolonged LOS.


RESULTS
Patients in intermediate triage Levels III and IV generally had the longest waiting times to nurse and physician assessment, and the longest ED lengths of stay. CTAS triage levels predicted laboratory and imaging utilization as well as consultation rate. The use of diagnostic imaging and laboratory tests was associated with longer LOS, varying with the specific tests ordered. Specialty consultation was also associated with prolonged LOS, and this effect was highly variable depending on the service consulted.


CONCLUSIONS
Triage level, investigations and consultations are important independent variables that influence ED LOS. Future research is necessary to determine how these and other factors can be incorporated into a model for predicting LOS. Improved information systems will facilitate similar ED time studies to assess key processes, lengths of stay and clinical efficiency.
Yoon
Philip
P
Division of Emergency Medicine and Department of Family Medicine, University of Alberta, Edmonton, Alberta, Canada.
Steiner
Ivan
I
Reinhardt
Gilles
G