Objective To construct a data-driven dynamic resource allocation model for the outpatient blood collection center, to explore the effectiveness of data-resource-quality linkage management, and to optimize service efficiency and patient experience. Methods A total of 390,700 patient visits to the outpatient blood collection center from January to December 2023 were treated as the control group, receiving conventional management.For the 433,300 patient visits from January to December 2024 were served as the observation group, receiving alternative management: a multi-source hospital data system was integrated to construct a data-resource-quality linkage optimization model, and a five-dimensional strategy for nursing quality improvement was implemented.Blood collection waiting time, blood collection efficiency, rate of unqualified specimens, and patient satisfaction rate were compared between the two groups. Results The observation group showed significantly shorter blood collection waiting time and procedure duration, lower rate of unqualified blood specimens, and higher patient satisfaction rate compared to the control group (all P＜0.05). Conclusion Data-driven dynamic resource allocation can effectively enhance blood collection efficiency and nursing quality, providing a reference for optimizing smart outpatient service systems.