Evaluating intensive care unit admission and discharge policies using a discrete event simulation model

Abstract

The efficient utilization and management of a scarce resource such as the intensive care unit (ICU) is critical to the smooth functioning of a hospital. This study investigates the impact of a set of operational policies on ICU behavior and performance. Specifically, the implemented policies are (a) wait time thresholds on how long patients can wait for an ICU bed, (b) the time windows during which patient discharges and transfers take place, and (c) different patient mix combinations. The average waiting time of patients for ICU beds and the admission ratio, the ratio of admitted patients to total ICU bed requests, are the performance measures under consideration. Using discrete event simulation, followed by analysis of variance and post hoc tests (Tukey multiple comparison), it is shown that increasing discharge windows has a statistically significant impact on the total number of admissions and average patient wait times. Moreover, average waiting time increased when wait time thresholds increased, especially when the number of emergency surgeries in the mix increased. In addition, larger proportions of elective surgery patients in the patient mix population can lead to significantly reduced ICU performance.