Analysing the Value of Intensive Care Unit Length of Stay Information Through Its Operational Performance

Abstract

The increasing demand for Intensive Care Unit (ICU) beds requires efficient admission, discharge, and care processes. Although all such efforts require predictions of Length of Stay (LOS) values, it is unclear how accurate those predictions need to be. This study aims to investigate the relationship between accuracy level of LOS predictions and operational performance indicators. To model the ICU patient flows, a discrete event simulation model is developed. 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 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 average waiting time of patients for an ICU bed and overall admission rates. The gaps increased when more elective patients were included in the patient mix. Moreover, higher waiting thresholds (i.e. maximum amount of time a patient will wait for an ICU bed) yielded higher values in both performance indicators.