Patient Routing Game with Wait Time Information

Abstract

In a public health care system, how to balance the patients to the hospitals so that shorten the total wait time in the system is a difficult problem. In order to trigger patients’ self-adaptively selecting hospitals (as referred to as routing in this paper) with the wait time information, this work attempts to investigate how different patient types in terms of their sensitivities to wait time, and how historical wait-time information at different levels affects patients’ routing. Specifically, this work (1) Models the process of patients’ routing as a repeated routing game on a bipartite network; (2) Proposes two routing strategies based on wait time information at different levels; (3) Examines the effects of wait time information on the patients’ routing based on the developed model. The preliminary analysis and experiments show that the distribution of patient flows to hospitals may reach an equilibrium state, no matter the patients are homogeneous or heterogeneous in terms of the sensitivity to wait time. The patient type has effects on the convergence speed and the fluctuation of patient flows. In addition, the experiments show that a long-term historical wait time information may encourage a health care system reach the equilibrium of patient flows.