Objective: The paper collects the settlement list data of a tertiary hospital in Jiangsu Province that was included in the DRG settlement of EB1 disease group, conducts cost influencing factor analysis and case mix optimization study, explores the potential value of different surgical methods within the disease group, establishes cost management ceilings, and provides a reference for policy formulation and hospital medical insurance management. Methods: A retrospective analysis was conducted on the settlement list data of 1613 inpatients undergoing major lung surgeries. Single-factor and multiple regression models were used to analyze the factors affecting the cost of major lung surgeries in the disease group. The selected influencing factors of hospitalization costs were used as the target variables and included in the decision tree model (QUEST) for case mix. Non-parametric tests were used for differences between groups, and coefficient of variation (CV) tests were used for differences within groups to evaluate the grouping effect and set cost ceilings. Results: Gender, age, length of stay, surgical method, and complication/comorbidity are the factors affecting the cost of major lung surgery. These five variables were included as classification nodes in the decision tree model analysis and ultimately divided into 8 case mixes. Conclusion: The optimization grouping results and cost standards of EB1 major lung surgery group based on decision tree models are scientific and reasonable. Segmentectomy has obvious advantages in terms of economic and medical value, which can be used as a reference for medical insurance departments and hospital management.