## 7 Conclusions  
This study utilized online platforms to gather fundamental hospital information and transportation data. Based on the integration and analysis of these datasets, a structural equation model (SEM) was developed to investigate the theoretical pathways influencing hospital traffic attraction, with hospital size, medical level, and traffic accessibility as latent variables. Validation analyses were conducted using case studies from general hospitals and specialized hospitals. The main conclusions are as follows:  
1. Among the influencing factors, medical level, traffic accessibility, and hospital size emerge as key determinants. Ranked by importance, the impact of medical level has surpassed that of traditional hospital size metrics, which explains why well-known hospitals in China consistently maintain high patient volumes. Traditional size indicators, such as construction area and number of beds, have shown declining predictive accuracy, particularly in the context of increasingly complex healthcare environments and the evolving, diverse needs of patients. In contrast, the number of medical departments, as a critical indicator of service diversity, exerts a more significant influence, highlighting the limitations of relying solely on traditional parameters to accurately predict patient demand.
2. Significant differences exist in the influencing factors between general hospitals and specialized hospitals. For general hospitals, hospital size is the second most influential factor in traffic attraction, as their broad service coverage and resource availability play a critical role in patient choice. In contrast, specialized hospitals are more dependent on traffic accessibility. Given their focus on specific medical needs, patients require greater geographic convenience to access specialized care. Therefore, measures such as optimizing public transit connections and planning adequate parking facilities are particularly crucial for enhancing the attractiveness of specialized hospitals.
3. The analysis using the structural equation model further reveals a significant positive correlation between hospital size and medical level. Specifically, the expansion of hospital size (e.g., increasing the number of medical departments or optimizing spatial utilization) can directly enhance patient volume and indirectly influence patient volume by improving medical levels, such as strengthening the capacity for key specialty development.  
Conceptualization, B.H.; Methodology, N.T. and S.Z.; Software, Z.Z., Y.J. and N.Q.; Validation, N.T. and S.Z.; Writing--original draft, B.H.; Writing--review and editing, N.Q.; Supervision, Z.Z. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The raw data supporting the conclusions of this paper will be provided by the authors upon reasonable request.  
Authors [PERSON] and [PERSON] were employed by the company Shandong Architectural Design and Research Institute Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.