Cooperation through Competition: Applications of Evolutionary Game Theory to Better Healthcare Decision Making

Abstract

Health insurance decisions in the United States are largely influenced by accessibility, affordability and expected health benefits. While the national health expenditure has steadily increased, more than 28 million Americans are still uninsured and patient satisfaction rates remain low. These problems involve complex interactions between the government (public), private insurers (private), and consumers (civil) within the health industry. These sectors are constantly considering costs, benefits, and the actions of those around them in their decision-making. In this way, evolutionary game theory (EGT) can be used to model the strategies employed by these three sectors as well as the interactions within each population. Tripartite games have been used to look at pathways to cooperation in multi-population games. This model applies the tripartite game model to find potential for cooperation in healthcare. The results suggest that i) competition, punishment, and coordination can lead to increased cooperation between these three populations, ii) informed markets are essential in improving health outcomes, and iii) the public sector plays a significant role in initiating cooperation. Policymakers can use these models of population dynamics and social learning to determine the effectiveness of intervention strategies.