Abstract: OBJECTIVE To assess the impact of health care-associated infections (HAIs) on overrun costs of the diagnosis related group (DRG) cases of neurosurgery department based on DRG. METHODS A total of 2 059 who were discharged from neurosurgery department and settled on DRG in Jiangyin People's Hospital from Jan. 2023 to Dec. 2024 were enrolled in the study and were grouped based on the status of HAIs. Univariate analysis and logistic regression analysis were performed for the impact of HAIs on the overrun risk. Tobit model was constructed to observe the impact of HAIs on the overrun of costs. The sources of differences in the overrun costs between the two groups were explored by Oaxaca-Blinder decomposition method. RESULTS The incidence of HAIs was 9.91% in the neurosurgery department， and the patients with lower respiratory tract infections (54.27%) and the patients with organ space infections (17.52%) were dominant among the patients with HAIs. Totally 200 pairs of data were included after propensity score matching (PSM)， logistic regression analysis showed that the HAIs is a risk factor for the DRG overrun (OR=5.916，P＜0.001). Tobit model indicated that the HAIs could lead to an increase of 11 030 yuan of overrun costs on average (P=0.002)， the length of hospital stay， age， admitting diagnosis and complications could also affect the overrun costs in varying degrees (all P＜0.05). The result of Oaxaca-Blinder decomposition showed that 97.25% of the difference in the overrun cost between the infection group and the non-infection group could be interpreted by observed characteristics， and the length of hospital stay alone accounted for 95.93% of the total difference (P＜0.001). CONCLUSIONS The HAIs can remarkably lead to the increase of overrun risk and overrun costs of the neurosurgery department patients under DRG payment system， and the length of hospital stay is the core driving factor for the difference in the cost. It is necessary to actively explore the infection risk adjustment mechanisms， and establish the dynamic surveillance and alarming mechanism of infection-related length of hospital stay so as to achieve the precise control of infections.