目的：探索新形势下建立医院多院区一体化运维管理系统。方法：运用 SWOT 分析法全面分析医院信息、后勤和设备三大部门运维管理状况，进而对运维一体化模式进行全面剖析。结果：医院多院区一体化运维发展战略在信息运维一体化系统建设工作实践中取得显著成效，提升了工作效率和医院核心竞争力。结论：SWOT 分析法对医院多院区一体化发展战略研究提供了理论基础，为医院多院区一体化管理提供了扎实有效的理论参考。

Objective: To establish the new eye hospital operational integration management mode. Methods: Using SWOT to analysis of hospital information management operations, logistics and equipment department, comprehensive analysis of operational integration mode. Results: We proposed hospital campus more operational integration development strategy, and in the practice of the information integration of operational work achieved remarkable achievement, which improved the working efficiency and the hospital core competitiveness. Conclusion: The SWOT analysis method for hospital operational integration development strategy research, provides a theoretical basis for hospital campus more leapfrog development provides a solid and effective theoretical reference.

随着亚太眼科学会(Asia-Pacific Academy of Ophthalmology，APAO)永久会址和秘书处落户在中山大学中山眼科中心珠江新城院区眼科学国家重点实验室大楼(中国广州)，在大数据时代背景下，建设先进的亚太级眼科学科学数据中心已成为亚太眼科创新战略发展的需要。通过建设科学数据中心，一方面缓解眼科学国家重点实验室项目科研数据增长压力，一方面为眼科大数据与人工智能等新兴科研项目开展提供保障平台，为亚太眼科学科建设打下坚实的数据基础。科学数据中心设计建设遵照国家《科学数据管理办法》实施，以加强和规范科学数据管理，保障科学数据安全，提高开放共享水平，更好支撑国家科技创新、经济社会发展和符合国家信息安全建设方针。

As the Asia-Pacific Academy of Ophthalmology (APAO) secretariat permanently located in the building of State Key Laboratory of Ophthalmology (Guangzhou, China). In big data time, it’s a problem for the development of the Asia-pacific ophthalmology innovation strategy to construct the Asia-pacific science data center of ophthalmology. Through the construction of science data center, alleviate the pressure of the state key laboratory of ophthalmology data growth, for big data and new research fields such as artificial intelligence to provide guarantee, provided a basis for the Asia-pacific eye subject construction. Science data center construction in accordance with national “scientific data management method”, to strengthen and standardize the scientific data management, to ensure the safety of scientific data, improve the level of open sharing, better support scientific and technological innovation, economic and social development and national security as a policy.