“Allocation of Intensive Care Unit Beds in Periods of High Demand” by Dr. Huiyin Ouyang
Dr. Huiyin Ouyang
Postdoctoral researcher in Department of Industrial Engineering and Management Sciences Northwestern University
We consider a stylized, discrete-time model for an Intensive Care Unit (ICU) in which patients’ health conditions change over time according to a Markov chain. At any point in time, each patient is in one of two possible health stages, one representing the critical and the other representing the highly critical health stage. The ICU has limited bed availability and therefore when a patient arrives, a decision needs to be made as to whether the patient should be admitted to the ICU and if so which patient in the ICU should be transferred to the general ward when there are no empty beds. Our objective is to maximize the long-run average rate with which patients survive or equivalently minimize the mortality rate. We show that the optimal patient admission/discharge policy depends on the composition of the patients currently in the ICU. Specifically, when a decision needs to be made as to whether a critical or highly critical patient should be admitted to the ICU, the optimal policy calls for admitting
a highly critical patient if and only if the number of highly critical patients in the ICU is below a threshold value. However, through a numerical study, we find that a carefully designed state-independent policy, particularly a policy we propose in this paper, may
perform quite well.