基于多源大数据融合分析的院外心脏骤停急救快速反应体系优化策略研究

院外心脏骤停救治生存链跨“民众-急救-医院”三大主体，并受动态环境、政策和经济等因素影响。构建适应国情的心脏急救快速反应体系需全面把握救治系统割裂数据间的潜在关联，精准突破关键问题。本项目将从管理科学、预防医学、信息技术和软件工程的学科交叉领域入手，探索以患者为中心，无缝对接的动态心脏急救“社区-院前-院内”优化策略。1）结合定量和定性研究，构建心脏急救快速反应体系影响因素框架；2）通过实证分析，运用跨领域数据融合与分析技术，找出关键环节问题；3）创建内容标准化、存储数字化、互联网信息多元化的xAPI心脏急救模式，规范调度指导和医疗团队急救流程，提高系统管理的质控能力，补齐框架已知短板环节；4）通过政策情景模拟和深度强化学习方法，实现心脏急救快速反应体系运行机制关键环节最优设计。从而，在政府财政能力和卫生资源水平的约束条件下，探索心脏急救优化策略，为提升急症救治能力提供决策依据。

The chain of survival for out-of-hospital cardiac arrest (OHCA) is comprised of the ‘community, emergency medical system, and hospital’ linkages which is influencing by dynamic environment, policy, and economic factors. Successful resuscitation depends on the optimization of a rapid response system (RRS) with fully understanding of potential correlations between fragmented data in the system and of precisely breaking through the key barriers. This study will utilize interdisciplinary principles of preventive medicine, management science, information technology，and software engineering, aiming to explore a patient-centered, standardized dynamic process of the OHCA ‘community - pre-hospital - in-hospital’ chain. Specific methods include: 1) Mixed methods of quantitative and qualitative studies to develop a conceptual framework of influencing factors of RRS; 2) Using cross-domain data fusion and analysis technology to empirically evaluate the impact of the key elements of RRS; 3) to create the xAPI resuscitation training platform with standardized contents, digital storage and integrations of internet information and multiple tools for quality assessment; 4) Using policy scenario simulation and deep reinforcement learning method to figure out the optimal design of key issues leading to the RRS. Finally, to propose optimized strategies for operational mechanisms at the implementation level considering organizational objectives and socioeconomic development.