Optimal ICU Admission Control With Premature Discharge

The intensive care unit (ICU) delivers care to critically ill patients with high resource intensity. Stochastic patient arrival and uncertain length of stay in ICUs present tremendous challenge to establish the admission and discharge policy to maximize the number of surviving patients and improve operational efficiency. In practice, ICU schedulers reserve some beds for potential patients with most critical conditions. Moreover, they prematurely discharge current ICU patients who are in stable status to accommodate for new and more urgent arrivals. We develop an analytical framework to quantify the impact of the number of reserved beds and suggest when to prematurely discharge current patients. A Markov decision process model is established to strike a balance between the rejection of incoming patient and the premature discharge in the near future. Monotonicity, concavity, and structural properties of the optimal control policy are presented. Using the inpatient record at a tertiary-level hospital in China, we conduct a case study and propose an effective threshold policy. Extensive numerical experiments are performed to analyze the effect of each parameter on the total survival benefits and compare different policies.
Note to Practitioners
—The intensive care unit (ICU) is the most resource intensive unit in the hospital, which has a significant impact on patient safety and care quality. Due to the increasing and aging population, the contradiction between the increasing demand and the insufficient ICU resources puts eligible ICU candidates at risk of lacking timely ICU care. Given the important role of the ICU in surviving lives of most critical patients, it is of paramount significance to improve ICU resource utilization and maximize the number of ICU survivors. Therefore, the objective of this paper is to develop a mathematical model to study ICU admission policies and premature discharge decisions. Based on our analytical framework, the ICU admission director can evaluate performance measures of ICU admission control system and investigate the impact of different policies on care quality of patients. By using an effective threshold admission policy proposed in this paper, the ICU admission director can be equipped with a decision support tool for the ICU admission control decisions with quantitative measures of potential impact.