基于多模态医养大数据深度聚合的动态主动服务模式研究

我国经济社会发展的需求正从“人口红利”开始向“健康红利”转变，大数据、人工智能 、云计算等新一代信息技术广泛渗透医疗健康与养老服务领域，正在引发深刻管理变革。目前，我国仍然存在医疗健康资源分布不均、服务滞后等问题，加快医养大数据跨界聚合与服务管理的基础理论研究，对实现“健康中国2030”目标和应对人口老龄化问题具有重大的战略意义。本课题以“医养数据跨界聚合—知识协同发现—动态主动服务”为研究主线，以5P医学模式为指导，研究跨时空多模态医养大数据跨界共享与安全管理机制、深度聚合方法与全周期动态主动服务模式，通过医养大数据智能服务实现人、设备、床位、检验等各种资源的有效整合和个性化主动健康服务。本课题是连接医疗健康大数据管理与医养资源要素整合服务的桥梁，有助于丰富智慧医疗健康管理的信息处理方法体系和知识服务理论体系。

The needs of China's economic and social development are shifting from a "demographic bonus" to a "health bonus". The new generation of information technologies, such as big data, artificial intelligence and cloud computing are widely penetrating medical health and old-age care, and leading to profound management changes. At present, China still has problems such as uneven distribution of resources and lagging services in medical and health fields. Accelerating the research on the basic theories of medical and healthcare big data cross-border integration and service management is of great strategic significance for achieving the goal of "Health China 2030" and effectively responding to the population aging issue. Taking " medical and healthcare data cross-border integration-knowledge collaborative discovery-dynamic active service" as the main line and 5P medical model as a guide, this proposal investigates the cross-space multi-modal medical and healthcare data big data cross-border sharing and security management mechanisms, deep aggregation methods, as well as full cycle dynamic service mode. The effective integration of people, equipment, beds, inspections and related resources and personalized active health services will be achieved by medical and healthcare big data intelligent services. This proposal is a bridge connecting medical health big data management and medical resource integration services, and it is helpful to enrich the information processing methodology system and knowledge service theory system of smart medical and health management.