The relationship between Intensive Care Unit Length of Stay information and its operational performance
Esmaeil Bahalkeh, Imran Hasan, Yuehwern Yih
Abstract
The increasing demand for Intensive Care Unit (ICU) beds requires efficient admission, discharge, and care processes. These efforts require predictions of Length of Stay (LOS) values; however, it is unclear how accurate these predictions need to be. This study investigates the relationship between the accuracy level of LOS predictions and operational performance indicators. A discrete event simulation model is developed to model the ICU patient flows. A linear function of actual and simulated LOS values is used to measure the accuracy level of the predictions. Multiple configurations of patient mix and patient waiting threshold were included in the simulation scenarios. Performance indicators are the average waiting time of patients for an ICU bed and overall admission ratios. Further statistical tests were carried out to evaluate the significance of the results. Results suggest that inaccurate LOS predictions overestimated both the average waiting time of patients for an ICU bed and overall admission rates which can have several quality and performance implications for hospitals. The gaps increased when more elective patients were included in the patient mix. Moreover, higher waiting thresholds (i.e., the maximum amount of time a patient will wait for an ICU bed) yielded higher values in both performance indicators.