Health Promotion and Data Science – Cultivating Talent in Chronic Disease Care

This program focuses on transforming diabetes assessment through data science to promote better health outcomes.
In 2023, using a human-centered strategy, we developed a complication risk prediction model for diabetes based on individual health data. This approach not only helps reduce the likelihood of developing diabetes but also lowers the risk of related comorbidities.

To raise awareness of diabetes education on campus, a team-based general education course was introduced. The course deepens students’ understanding of disease pathology and strengthens their experience in health product design through hands-on projects.

1. Diabetes Complication Risk Assessment Model (SDG 3 – Good Health and Well-being)
   In partnership with the Taiwan Diabetes Health Promotion Association, we revised the existing risk assessment system to better meet the needs of health educators. New indicators—such as urea levels, waist circumference, presence of hypertension, and medication types—were added based on practitioner feedback, improving the model’s accuracy and usability.
2. General Education Course (SDG 4 – Quality Education)
   A new course, Medical Risk Data and Healthcare Management, was offered to enhance faculty and student understanding of diabetes. The course covers diabetes epidemiology, predictive modeling, and cross-disciplinary learning. With contributions from professors, medical researchers, physicians, and health educators, the course provides students with a systematic understanding of diabetes and its healthcare implications.
3. Online Course Modules (SDG 10 – Reduced Inequalities)
   In collaboration with NCCU’s Center for Teaching and Learning Development, we launched a modular online course in March 2022 via the NCCU Open Course Video Platform. Each module runs 7–15 minutes, with a total of 112 modules. The course introduces the concepts and applications of health databases, helping prepare future professionals with a solid foundation in health data science.