Admission control of hospitalization with patient gender by using Markov decision process

Admission control of hospitalization considering patient gender is an interesting issue in the study of hospital bed management. This paper addresses the decision on the admission of patients who should immediately be admitted into a same‐gender room or rejected. Note that a patient is admitted depending on different conditions, such as his/her health condition, gender, the availability of beds, the length of stay, and the reward of hospitalization. Focusing on the key factor, patient gender, this paper sets up an infinite‐horizon total discounted reward Markov decision process model with the purpose to maximize the total expected reward for the hospital, which leads to an optimal dynamic policy. Then, the structural properties of the optimal policy are analyzed. Additionally, a value iteration algorithm is proposed to find the optimal policy. Finally, some numerical experiments are used to discuss how the optimal dynamic policy depends on some key parameters of the system. Furthermore, the performance of the optimal policy is discussed though comparison with the three other policies by means of simulating different scenarios.