Abstract: Objective To analyze the structure and behavioral patterns of outpatient populations, construct a long-term and dynamic panoramic patient profile, and explore the correlation between departmental supply-demand tension and academic reputation, thereby providing evidence for optimizing hospital resource al-location and services. Methods Based on complete outpatient data from Peking Union Medical College Hospi-tal from 2015 to 2025, we performed descriptive analysis of patient characteristics. Spearman correlation analysis was used to assess the relationship between departmental waitlist success rates and the Fudan Hospital Ranking as well as the Chinese Hospital Science and Technology Evaluation Metrics. Prediction models were in-tegrated to forecast future outpatient trends. Results The male-to-female ratio among outpatients was approxi-mately 1:2, with the majority aged 30-60 years. The proportion of non-locally insured patients increased an-nually, reaching 31. 68% in 2025, while the share of specialized disease clinics rose to 21. 64%. The overall average waitlist success rate was 17. 05%, which showed significant positive correlations with the Fudan North China Regional Ranking (r=0. 540, P=0. 002), the overall Fudan Ranking (r=0. 621, P<0. 001), the Sci-ence and Technology Evaluation Ranking (r=0. 487, P=0. 003), and the 5-year Comprehensive Science and Technology Evaluation Ranking (r=0. 545, P=0. 001). The proportion of revisit visits exhibited a declining trend, falling to 68. 49% in 2025. Predictions indicated an average annual growth rate of approximately 4. 90% in outpatient visits over the next five years, driven mainly by middle-aged, elderly, and female patients. Conclusions Peking Union Medical College Hospital has continuously expanded its service coverage while deepening specialization and precision in service delivery. High-reputation departments face more pronounced supply-demand contradictions, offering a new perspective for objectively assessing the dynamic relationship be-tween service pressure and brand influence. We recommend that the hospital adopt data-driven management strategies to establish dynamic resource allocation and service optimization mechanisms, thereby promoting high-quality institutional development.