Predictive modeling of corporate financial risk and its implications for health economics and public health efficiency.

Introduction: This study investigates the relationship between corporate financial risk and public health efficiency by developing a unified analytical framework that integrates financial risk prediction with health economic outcomes. We first establish a conceptual mechanism through which corporate financial instability affects public health systems via three primary pathways: direct effects through reduced healthcare funding and resource constraints, indirect effects through employment instability and changes in insurance coverage, and systemic effects through broader macroeconomic disruptions. Methods: Building on this framework, we propose the Risk Economic Health Nexus Model (REHNM), which combines probabilistic modeling, latent variable inference, and multimodal data integration to capture the complex and uncertain relationships between financial indicators and health outcomes. To account for temporal dynamics and external influences, we further introduce the Dynamic Risk Assessment Model (DRAM), enabling the model to track evolving financial conditions and their downstream health impacts. The Strategic Risk Health Integration Approach (SRHIA) is developed to translate predictive outputs into actionable insights for policymakers and health economists. Results and discussion: Empirical results demonstrate that the proposed framework improves predictive performance while providing interpretable insights into the linkage between financial risk and public health efficiency. Importantly, the model is designed as a decision support tool that can assist in early risk detection, resource allocation, and health system planning, thereby contributing to improved economic resilience and public health outcomes.