摘要真实世界数据（RWD）治理是高质量真实世界证据生成的重要基础。然而，不同来源数据在结构、术语和质量控制方面的不一致，制约了跨机构数据整合与使用。T/CAS 1170—2025《医疗领域真实世界数据治理 通用数据模型构建》团体标准在此背景下制定，旨在为医疗领域RWD的通用数据模型（CDM）构建提供技术规范。本文对该标准的起草背景、主要内容及应用意义进行解读。该标准介绍了CDM建设过程中需求分析与数据源定义、数据模型设计、术语标准化与映射、数据集成与整合、模型验证与质量评估、模型维护与演进等关键环节，并进一步对数据安全与合规、数据透明性、偏倚控制及分析结果可重复性提出要求。结合国内外实践，CDM已逐步成为支撑RWD标准化治理、协同分析和证据生成的重要技术基础。我国虽已在医院、专科及区域健康信息平台层面开展探索，但总体较为分散。该标准的发布为我国医疗领域RWD治理提供了统一框架，有助于提升数据标准化水平、促进多中心协作与数据共享，并为药品上市后评价及监管科学发展提供基础支持。

abstractsReal-world data (RWD) governance is a critical foundation for generating high-quality real-world evidence. However, inconsistencies in data structure, terminology, and quality control across different data sources hinder cross-institutional data integration and use. Against this background, the group standard T/CAS 1170-2025, Medical real-world data governance-Construction of common data model, was developed to provide technical specifications for common data model (CDM) construction for medical RWD. This article interprets the drafting background, main contents, and practical significance of the standard. The standard describes key stages in CDM development, including requirement analysis and data source definition, data model design, terminology standardization and mapping, data integration, model validation and quality assessment, as well as model maintenance and evolution. It also puts forward requirements for data security and compliance, data transparency, bias control, and reproducibility of analytical results. In light of domestic and international practice, CDM has gradually become an important technical foundation for standardized RWD governance, collaborative analysis, and evidence generation. Although China has initiated relevant explorations at the levels of hospitals, specialty platforms, and regional health information systems, these efforts remain relatively fragmented overall. The release of this standard provides a unified framework for medical RWD governance in China, and is expected to improve data standardization, promote multicenter collaboration and data sharing, and support post-marketing evaluation of drugs and the development of regulatory science.