Evolutionary Game Analysis of the Mutual Trust Dilemma in Health Data Circulation: A Symmetry Perspective on Supply and Demand

In the circulation of health data, the mutual trust dilemma leads to the symmetric problems of “inadequate supply” on the supply side and “impeded flow” on the demand side, which hinder the realization of data value. This paper analyzes the formation mechanism of this dilemma and its resolution pathways from a symmetry perspective. First, based on a literature review, we extract the manifestations of the mutual trust dilemma and construct a two-stage decision-making “vicious circle” model of mutual trust. Unlike conventional single-stage game models, this framework captures the sequential nature of trust decisions—entry in Stage 1 and compliance in Stage 2. Second, we establish a tripartite evolutionary game model involving data suppliers, demanders, and regulators, and employ MATLAB simulations to examine the impact of key parameters on strategic evolution. The findings reveal that: (1) beneficial data utilization scenarios are the prerequisite for participation; (2) strong regulation is the fundamental guarantee for mutual trust; and (3) while increasing penalties, reducing compliance costs, and enhancing trust-related gains can promote compliance, regulatory measures must be carefully balanced to avoid suppressing participation willingness. Accordingly, we propose a four-step progressive mutual trust mechanism comprising motivation activation, cooperation facilitation, performance guarantee, and trust reinforcement. Policy recommendations are offered regarding high-benefit scenarios, trusted data spaces, incentive policies, and data standardization, with the aim of building a trusted health data circulation ecosystem.