A Simulated Discrete-Event and Queuing Model to Reduce Transfers from the Emergency Department and to Optimize Hospital Bed Management

Abstract

Objectives . Emergency departments (EDs) and elective hospitalizations compete for beds. Our aim was to reduce hospital transfers using a queuing-model study. Methods . Macros were created to simulate four priority groups of patients according to hospitalization mode (elective, ED) and age (≥75 and <75 years), with randomization of number of admissions and length of stay (LOS). Those priorities were assigned regarding usual situations (ED admission with less priority than scheduled admission) not regarding clinical contexts. Simulations were based on actual data from an academic hospital. Models simulated ED boarder queue according to different scenarios based on number of hospital beds, LOS, and preventable hospitalizations. Results . Observed hospital-LOS was longer for patients ≥75 years (12.2 ± 3.6 days versus 11.4 ± 3.8 days; P < 0.01 ) and for ED admissions (12.2 ± 0.6 versus 9.7 ± 0.6 days; P < 0.01 ). In simulation models, two scenarios stabilized the beds demand after admissions: limitation of LOS to 30 days or 20% decrease in elective admissions among older patients. With these scenarios, the queue would be 25.2 patients for 361 beds (+2%) and 16.7 patients for 354 beds. Conclusions . Queuing models offer an interesting approach to bed management. A significant reduction in ED transfers is feasible, by limiting LOS to <30 days or by reducing elective hospitalizations of patients by 20%.