The 2025 project primarily integrates retrospective thematic databases, clinical data from medical generations, and information from the existing Center for Health and Welfare Data Science and the Central Health Insurance Administration. Students from Taiwan and Thailand will jointly analyze and research cross-border comparative health big data, hoping to further understand health disparities and health services between the two countries and foster mutual exchange. The project team will design metadata for integration and use a comparative approach to plan targeted data comparisons. Dataset filters and tools will be provided to search and explore interoperable health datasets, effectively improving user data retrieval efficiency. The 2026 proposal uses a random forest model in machine learning to predict and classify raw data, followed by preprocessing and feature engineering. The results effectively evaluate the effectiveness of the program. After model training, comparisons with Thai data will be conducted to test the feasibility of applying machine learning to evaluate the effectiveness of specific disease management programs based on predictive performance. This will also provide a clearer