WS/T 672-2020 in English
VALIDNational conceptual data model for health and population information
- Issued on:2020-05-22
- Implemented on:2020-12-01
- File Format:PDF
- Delivery:Via email within 5 business days
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本标准描述卫生与人口领域信息的特征,规定了对象类及其属性和相互关系。
本标准适用于卫生与人口相关领域信息标准的制定和信息系统的研发与管理。
Introduction
Standard Background and Significance
As a basic specification for health informationization, this standard establishes for the first time a conceptual data model framework covering the entire life cycle of universal health. Based on the HL7 V3 RIM core architecture and integrating the characteristics of China's medical and health system, it provides a unified data modeling benchmark for electronic medical records, public health monitoring and other systems.
Core model architecture
| Core class | Number of subclasses | Key attributes | HL7 RIM correspondence |
|---|---|---|---|
| Entity | 4 | Class code, identifier, existence time | Entity |
| Role | 1 | Class code, validity time, certificate | Role |
| Activity | 8 | Class code, status, validity time | Act |
Key innovations
Localization Adaptation
Added Chinese-specific attributes such as Household Registration Type and Ethnicity Code, and expanded public health monitoring-specific fields such as occupational protection and risk factor exposure in the practitioner class.
Model Extension Mechanism
The dual expression of instances and categories is achieved through the Entity.Qualifier attribute, supporting the unified modeling of epidemiological group research and individual diagnosis and treatment data.
Implementation suggestions
- System development should give priority to the value range standards specified in the WS/T 671 data dictionary
- Clinical observation classes need to simultaneously record the two time dimensions of activity time and effective time
- Medication management needs to ensure the logical consistency of the pathway code, method code, and target site
Technology evolution analysis
This standard uses public health cases as an independent activity class for the first time, supporting the correlation analysis between the infectious disease direct reporting system and clinical diagnosis and treatment data. Subsequent versions recommend the addition of data model extensions for emerging scenarios such as Internet medical care and AI-assisted diagnosis.

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