Earticle

This study investigates the structural challenges of public care systems in regions experiencing severe population outflow, conceptualized as the 'Care Desert Paradox'. Utilizing a balanced panel data of 224 municipalities in South Korea from 2011 to 2023, we employ an entity fixed-effects model to empirically analyze the lagged effect of net population outflow on long-term care recognition rates. The results reveal that net outflow significantly suppresses the care recognition rate with a 5-year lag, suggesting a collapse of informal care networks and formal service infrastructure. To address this, we propose an Intelligent Decision Support System (DSS) architecture that calculates a Care Desert Vulnerability Index (CDVI). This system shifts the policy paradigm from a reactive application-based approach to a proactive detection system, enabling timely interventions.