Disequilibrium between admitted and discharged hospitalized patients affects emergency department length of stay.
OBJECTIVE
Most patients are admitted to the hospital through the emergency department (ED), and ED waiting times partly reflect the availability of inpatient beds. We test whether the balance between daily hospital admissions and discharges affects next-day ED length of stay.


METHODS
We conducted a cross-sectional study of hospitals in metropolitan Toronto, served by a single emergency medical services provider in a publicly funded system. During a 3-year period, we evaluated the daily ratio of admissions to discharges at each hospital and the next-day median ED length of stay in the same hospital by using linear regression.


RESULTS
Across hospitals, the daily mean (SD) 50th percentile ED length of stay averaged 218 (51) minutes. As the inpatient admission-discharge ratio increased or decreased, next-day ED length of stay changed accordingly. Compared with ratios of 1.0, those less than 0.6 were associated with an 11-minute (95% confidence interval [CI] 5 to 16 minutes) shorter next-day median ED length of stay; at admission-discharge ratios of 1.3 to 1.4, ED length of stay was significantly prolonged by 5 minutes (95% CI 3 to 6 minutes). Admission-discharge ratios on weekends and among medical inpatients had a stronger influence on next-day ED length of stay; effects were also greater among higher-acuity and admitted ED patients.


CONCLUSIONS
Disequilibrium between the number of admitted and discharged inpatients significantly affects next-day ED length of stay. Better matching of daily hospital discharges and admissions could reduce ED waiting times and may be more amenable to intervention than reducing admissions alone. The admission-discharge ratio may also provide a simple way of tracking and enhancing hospital system performance.
Vermeulen
Marian J
MJ
Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada.
Ray
Joel G
JG
Bell
Chaim
C
Cayen
Barry
B
Stukel
Therese A
TA
Schull
Michael J
MJ
D003430:Cross-Sectional Studies; D003625:Data Collection / Q000379:methods*; D017598:Efficiency, Organizational; D004636:Emergency Service, Hospital / Q000458:organization & administration*; D005544:Forecasting; D006742:Hospital Bed Capacity / Q000706:statistics & numerical data*; D006801:Humans; D007902:Length of Stay / Q000706:statistics & numerical data*; D016014:Linear Models; D015999:Multivariate Analysis; D009864:Ontario; D010343:Patient Admission / Q000706:statistics & numerical data; D010351:Patient Discharge / Q000706:statistics & numerical data; D010934:Planning Techniques