Abstract：Objective To analyze the practical effect of the diagnosisrelated groups (DRGs) of myelodysplastic syndromes (MDS) on hospitalization costs under the ECHAID decision model.Methods Data of patients with myelodysplastic syndrome as the first discharge diagnosis were retrospectively collected in the first page of medical records in the Hospital Information System (HIS) records from a tertiary hospital in Zhejiang Province from February 2021 to February 2023. All indicators of the medical record home page were tested via multiple linear regression tests between groups, Mann-Whitney-U- tests, and KruskalWallis H-tests. With indicators of variance inflation factor (VIF)<10 and P<0.05 in the univariate screen as the independent variable, and hospitalization costs as the dependent variable, the DRGs grouping decision tree model was established by using the E-CHAID exhaustive algorithm. The maximum cost was determined as the "median hospitalization cost+1.5 times the standard deviation" for each DRGs case combination, and the ratio of maximum cost for each DRGs grouping to the maximum cost for all cases was calculated to analyze the distribution characteristics of hospitalization costs.Results A total of 2 223 MDS patients were included. The three variables of whether monoclonal antibodies were used, whether the patients were admitted to the ICU, and the number of transfusions were the hierarchical classification variable nodes of the E-CHAID decision tree model. Twelve nodes were established, generating 7 terminal nodes. Variance coefficient -CV-s were 0.40, 0.15, 0.23, 0.21, 0.25, 0.51, and 0.46 respectively, and the Kruskal-Wallis -H- test between the DRGs groupings held statistical significance (H=2816.568, P<0.001). Among the 2 223 patients, 76 (3.42%) exceeded the maximum cost. The total hospitalization cost of patients exceeding the cost ceiling was 662 241.71yuan, accounting for 1.40% of the total DRGs hospitalization cost. The relative weights of DRGs groups 1 to 7 were 1.49, 2.42, 2.14, 1.33, 1.10, 0.47 and 0.24.Conclusion DRGs grouping of myelodysplastic syndromes under the E-CHAID decision model is more heterogeneous and the distribution among groups is reasonable, which can be used for the future development of DRGs in Zhejiang Province. It can provide some basis for the subsequent development of local DRGs medical payment reform for malignant hematological diseases such as myelodysplastic syndromes.
［15］LUO A J, CHANG W F, XIN Z R, et al. Diagnosis related group grouping study of senile cataract patients based on E-CHAID algorithm［J］. Int J Ophthalmol, 2018,11(2):308-313. DOI: 10.18240/ijo.2018.02.21.
