数据驱动的慢性病精准管理模式探究

Research on data-driven precision management mode for chronic diseases

慢性病已成为影响社会发展的重大公共卫生问题。传统的慢性病管理模式多"重治疗、轻预防"。本研究将信息管理学科中的大数据应用、知识管理、知识服务等方法与慢性病管理相结合,通过构建包括多源异构的慢性病数据资源库、慢性病健康知识分析平台以及慢性病服务应用平台,实现慢性病数据管理中自我检测数据与医疗机构等来源数据的互联互通,慢性病健康知识的融合与精准推送,以及围绕慢性病预防、诊断、治疗与康复全过程提供的个性化精准服务。2019年8月起采用该管理模式搭建糖尿病大数据平台,至2022年1月,收集来自216万名居民的诊疗及管理数据3.8亿条,数据采集的准确率达97.46%,完整率达96.07%;构建相应知识库和服务平台,实现对糖尿病患者的个性化服务,提高了患者和社区居民的糖尿病知晓率、治疗率、治疗控制率、科普与传播率。

Chronic diseases have grown into a major public health threat affecting social development.The traditional management of chronic diseases tends to characterize"prioritizing treatment and neglecting prevention".In this study,big data application,knowledge management,knowledge service and other theories and methods in the information management discipline were put in practice of chronic disease management.Thanks to the construction of a multi-source and heterogeneous chronic disease database,a chronic disease health knowledge analysis platform and a chronic disease service application platform,the following objectives were achieved.These included the data interconnections between patients′self-testing data and medical institutions′data in chronic disease data management,the integration and accurate delivery of chronic disease health knowledge,and personalized and accurate services covering the whole process of chronic disease management,namely prevention,diagnosis,treatment and rehabilitation.Since August 2019,this management mode has been used to build a diabetes big data platform.By January 2022,380 million pieces of diagnosis,treatment and management data were collected from about 2.16 million residents,with the accuracy rate of 97.46%and the integrity rate of 96.07%.Corresponding knowledge base and service platform were built,and personalized service was provided to diabetes patients.These measures improvd the awareness rate,treatment rate,treatment control rate,science popularization and communication rate covering both diabetes patients and community residents.