Health expenditure trajectories of general population in Korea: National Sample Cohort 2008–2019

Abstract Background Health expenditure is a widely used measure of healthcare utilization and plays a critical role in policy formulation and resource allocation. However, previous studies often focused on single time points or cross-sectional analyses, failing to capture the temporal dynamics of healthcare utilization. This study aimed to identify trajectories of medical expenses across all age groups. Methods We analyzed from 1,121,532 individuals in the National Health Insurance Service-National Sample Cohort (2008-2019). Latent Class Growth Mixture Modeling identified health expenditure trajectories based on 12 years. Multinomial logistic regression analyzed associations between trajectories and participant characteristics, and GEE assessed their association on medical costs. Mortality risks were evaluated using time-dependent Cox models and logistic regression, with sensitivity analyses. Results Four distinct expenditure trajectories were identified: low (58.6%), moderate increasing (21.8%), steep increasing (16.0%), and high (3.5%). Females, medical-aid beneficiaries, and those with higher comorbidity were more likely to belong to higher expenditure groups. The steep increasing group showed a sharp rise in costs after age 60, surpassing the high group, which declined after age 75. Higher expenditure groups had significantly increased risks of all-cause mortality, with the high group showing the highest risk (HR: 3.17; 95% CI: 3.14-3.20). Conclusions Healthcare expenditure trajectories are strongly linked to health status and mortality. These findings suggest that expenditure patterns can serve as indicators for identifying high-risk populations. Public health strategies should enhance preventive care and chronic disease management for groups with rising expenditures. Integrating these trajectories into surveillance systems can support early intervention, efficient resource allocation, and sustainable health planning. Key messages • Healthcare spending patterns predict future mortality and can identify vulnerable groups. • Early intervention in high-expenditure trajectories can improve outcomes and policy efficiency.