区域居民健康数据集
收藏资源简介:
基于临床数据中心(CDR)架构,构建门诊就诊等临床数据模型矩阵搭建全域数据底座,抽取、转换、加载多源异构医疗数据。通过协议解析、归一化将非结构化、半结构化和结构化数据统一为标准格式,并通过重复数据检测、异常值检测算法,进行多级数据清洗。最终借助构建患者主索引,实现跨系统患者实体精准聚合,经业务逻辑建模,按时间轴和诊疗场景维度建模,通过规则引擎等数据质量校验方式,形成以患者主索引为核心的星型数据模型,为患者 360 视图提供数据支撑。
Based on the Clinical Data Repository (CDR) architecture, this study constructs a clinical data model matrix covering scenarios including outpatient visits to establish a unified global data foundation. It leverages the Extract, Transform, Load (ETL) workflow to process multi-source heterogeneous medical data. Unstructured, semi-structured and structured data are standardized into a uniform format through protocol parsing and normalization, followed by multi-stage data cleaning with duplicate data detection and outlier detection algorithms. Ultimately, by building the Patient Master Index (PMI), accurate aggregation of patient entities across disparate systems is achieved. Following business logic modeling across dimensions of timeline and clinical diagnosis and treatment scenarios, and employing data quality validation approaches such as rule engines, a star-shaped data model with the Patient Master Index as the core is finally developed, which provides data support for the patient 360-degree view.




