An evolutionary game approach for information sharing within medical consortium based on complex network

Abstract

Sharing medical information has the potential to improve the efficiency of communication and collaboration within a medical consortium and enhance the overall medical service level in a region. However, it is important to consider that the process of sharing often encounters a situation similar to the prisoner’s dilemma due to information asymmetry. Additionally, the long-term dynamic interaction within a medical consortium is difficult to model using traditional game theory. Therefore, we develop an evolutionary game model among core hospitals and member hospitals within a medical consortium. Firstly, we compute replication dynamic equations to understand the strategic interactions and evolutionary dynamics of information sharing within a medical consortium. Secondly, we analyze the local stability of the game model evolution and derive the evolutionary stability strategy (ESS) under different parameter constraints. Thirdly, to analyze the parameter sensitivity, we construct a scale-free network for numerical simulation experiments. As the network evolves, the edges among nodes and the strategy choices of nodes in this network likewise change. Based on this work, we can uncover the impact of different factors on the willingness of nodes to share information. Finally, some management implications derived from findings can help medical consortium members make better sharing decisions in the future.