Abstract
Tertiary public hospitals are the backbone of China's healthcare system, yet their medical quality varies across regions. Since 2019, the national performance appraisal for tertiary public hospitals (NPA-TPH) has emphasized medical quality as the core evaluation dimension. However, comprehensive, objective, and dynamic assessment models remain limited, particularly in western regions such as Guangxi. This study evaluated medical quality in 23 tertiary general public hospitals in Guangxi from 2018 to 2021 using a hybrid model integrating entropy weight method (EWM), grey relational analysis (GRA), and technique for order preference by similarity to ideal solution (TOPSIS). Indicator weights were determined via EWM, performance association was assessed through GRA, and composite rankings were generated using TOPSIS. Kernel density estimation (KDE) was applied to visualize temporal changes in quality distribution. Overall medical quality showed an upward trend during the study period. Top-ranking hospitals consistently demonstrated strong performance, while others exhibited slow improvement or decline, indicating widening inter-hospital disparities. KDE results revealed a shift in score distribution from unimodal to multimodal patterns, suggesting structural differentiation and increasing polarization, characterized by "the strong getting stronger." The EWM-GRA-TOPSIS model effectively provides an objective and comprehensive framework for medical quality evaluation. Findings indicate that while NPA-TPH policy has promoted quality improvement, disparities among tertiary public hospitals in Guangxi have intensified. Targeted, differentiated strategies are needed to enhance weaker hospitals and promote balanced regional healthcare development.