Abstract for: Agent-Based Modeling to Simulate Complex Quality Dynamics Leading to Patient Outmigration in South Korea

Cancer patients’ outmigration imposes significant and persistent challenges on the South Korean healthcare system. Existing policy interventions have largely failed to address the underlying factors driving outmigration, particularly individual perceptions and trust in the regional healthcare system. Despite ongoing policy efforts aimed at mitigating this phenomenon, outmigration persists, highlighting a dynamic dilemma. To investigate the mechanisms underlying cancer patients’ outmigration at both individual and regional levels, we developed an agent-based model (ABM) that integrates both objective and perceived quality factors. We established a framework to capture the dynamics among different quality metrics and employed a Genetic Algorithm (GA) to calibrate the initial parameters. Quality dynamics and agent interactions revealed several key findings characterized by nonlinearity, emergence, and resistance. In particular, discrepancies between objective and perceived quality measures drove the persistent concentration of patients in a small number of hospitals within the Seoul Metropolitan Area. Three core phenomena emerged: the formation of hub hospitals, divergence between objective and perceived quality, and biased realization of quality. Our study introduces a novel agent‐based model that simulates the complex processes of hospital choice and outmigration driven by quality dynamics. The model is grounded in theoretical frameworks of healthcare quality and incorporates soft variables. We plan to rigorously validate and refine the model, as well as conduct further simulation runs that reflect South Korea’s policy context. Grammar and sentence structure revision of the manuscript