Xu W, Guan Z, Sun J, Wang Z, Geng Y
Wei Xu, Department of Medical Informatics, Second Military Medical University 800, Xiangyin Road, Yangpu District, Shanghai, E-mail:
Methods Inf Med. 2014;53(1):39-46. doi: 10.3414/ME13-01-0008. Epub 2013 Dec 9.
In China, deployment of electronic data capture (EDC) and clinical data management system (CDMS) for clinical research (CR) is in its very early stage, and about 90% of clinical studies collected and submitted clinical data manually. This work aims to build an open metadata schema for Prospective Clinical Research (openPCR) in China based on openEHR archetypes, in order to help Chinese researchers easily create specific data entry templates for registration, study design and clinical data collection.
Singapore Framework for Dublin Core Application Profiles (DCAP) is used to develop openPCR and four steps such as defining the core functional requirements and deducing the core metadata items, developing archetype models, defining metadata terms and creating archetype records, and finally developing implementation syntax are followed.
The core functional requirements are divided into three categories: requirements for research registration, requirements for trial design, and requirements for case report form (CRF). 74 metadata items are identified and their Chinese authority names are created. The minimum metadata set of openPCR includes 3 documents, 6 sections, 26 top level data groups, 32 lower data groups and 74 data elements. The top level container in openPCR is composed of public document, internal document and clinical document archetypes. A hierarchical structure of openPCR is established according to Data Structure of Electronic Health Record Architecture and Data Standard of China (Chinese EHR Standard). Metadata attributes are grouped into six parts: identification, definition, representation, relation, usage guides, and administration.
OpenPCR is an open metadata schema based on research registration standards, standards of the Clinical Data Interchange Standards Consortium (CDISC) and Chinese healthcare related standards, and is to be publicly available throughout China. It considers future integration of EHR and CR by adopting data structure and data terms in Chinese EHR Standard. Archetypes in openPCR are modularity models and can be separated, recombined, and reused. The authors recommend that the method to develop openPCR can be referenced by other countries when designing metadata schema of clinical research. In the next steps, openPCR should be used in a number of CR projects to test its applicability and to continuously improve its coverage. Besides, metadata schema for research protocol can be developed to structurize and standardize protocol, and syntactical interoperability of openPCR with other related standards can be considered.
在中国，用于临床研究（CR）的电子数据采集（EDC）和临床数据管理系统（CDMS）的部署尚处于非常早期的阶段，约90%的临床研究通过手动方式收集和提交临床数据。本研究旨在基于openEHR原型构建中国前瞻性临床研究的开放元数据架构（openPCR），以帮助中国研究人员轻松创建用于注册、研究设计和临床数据收集的特定数据录入模板。
采用新加坡都柏林核心应用简档（DCAP）框架来开发openPCR，并遵循定义核心功能需求和推导核心元数据项、开发原型模型、定义元数据术语和创建原型记录以及最终开发实现语法等四个步骤。
核心功能需求分为三类：研究注册需求、试验设计需求和病例报告表（CRF）需求。识别出74个元数据项并创建了它们的中文权威名称。openPCR的最小元数据集包括3个文档、6个章节、26个顶级数据组、32个下级数据组和74个数据元素。openPCR中的顶级容器由公共文档、内部文档和临床文档原型组成。根据电子健康记录架构数据结构和中国数据标准（中国电子健康记录标准）建立了openPCR的层次结构。元数据属性分为六个部分：标识、定义、表示、关系、使用指南和管理。
OpenPCR是一个基于研究注册标准、临床数据交换标准协会（CDISC）标准和中国医疗相关标准的开放元数据架构，将在中国范围内公开可用。它通过采用中国电子健康记录标准中的数据结构和数据术语来考虑未来电子健康记录和临床研究的整合。openPCR中的原型是模块化模型，可以分离、重组和重用。作者建议，其他国家在设计临床研究元数据架构时可参考开发openPCR的方法。在接下来的步骤中，openPCR应在多个临床研究项目中使用，以测试其适用性并不断扩大其覆盖范围。此外，可开发研究方案的元数据架构以结构化和标准化方案，并考虑openPCR与其他相关标准的句法互操作性。
