선행 질병력의 의료비 자료 분석을 통한 중대질병 발생 예측모형에 관한 연구

The burden of medical expenses has become one of the major issues in our society due to the problems of aging and low birth rates. Recently, as the healthcare paradigm shifts from a treatment-centered approach to one focused on disease prevention and health management, discussions and research on various predictive models for diseases that form the foundation of health management services have become more active. This study defines major diseases, which incur high medical costs, as serious diseases, identifies preceding diseases that significantly affect the occurrence of serious diseases, and proposes a model to assess the risk of serious disease occurrence based on the medical cost information of these preceding diseases. Using the cohort database of the National Health Insurance Service, a predictive model for serious disease occurrence was derived through logistic regression and principal component analysis. Additionally, based on this model, a scoring method to represent the risk of serious diseases and a grading system to categorize groups based on their risk levels were proposed. It is expected that utilizing individual medical cost information and the impact of preceding diseases on serious diseases will contribute to the prevention of serious diseases and provide a foundation for offering health-related services that help individuals lead healthy lives.