OBJECTIVE To optimize the clinical drug list of diagnosis-related group （DRG）， reduce the drug cost of patients， and increase the DRG settlement rate. METHODS By selecting BR23 disease group in the department of neurology of a hospital as the research object， data mining technology was used to explore the medication rule of the disease group， and the key monitored drugs were scored by comprehensive evaluation of drugs， thus optimizing the clinical drug list of disease groups. The hospitalization information of patients enrolled in the disease group in December 2022 was selected as the pre-optimization data， and the hospitalization information of patients enrolled in the disease group in September 2023 was selected as the post-optimization data. The implementation effect of the optimized list was evaluated by comparing the medical quality and drug cost data between the two groups. RESULTS After optimizing the clinical drug list， the settlement rate of this disease group increased from 84.36% before optimization to 104.70%； there was significant reduction in hospitalization drug cost and total hospitalization cost （P＜ 0.05）； the consumption of key monitored drugs significantly decreased. CONCLUSIONS Data mining technology helps explore the clinical medication rules of disease groups， which can be used by pharmacists to improve the settlement rate of DRG through effective pharmaceutical intervention.