Development of an Open Metadata Schema for Prospective Clinical Research (openPCR) in China
Autor: | Z. Wang, Z. Guan, J. Sun, Weigang Xu, Yibing Geng |
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Rok vydání: | 2014 |
Předmět: |
China
Biomedical Research Computer science Datasets as Topic Information Storage and Retrieval Data element definition Health Informatics 030226 pharmacology & pharmacy World Wide Web 03 medical and health sciences 0302 clinical medicine Health Information Management Electronic Health Records Humans Prospective Studies 030212 general & internal medicine Database catalog Advanced and Specialized Nursing Data element Data Collection Meta Data Services openEHR Metadata repository Data mapping Metadata Database Management Systems |
Zdroj: | Methods of Information in Medicine. 53:39-46 |
ISSN: | 2511-705X 0026-1270 |
DOI: | 10.3414/me13-01-0008 |
Popis: | SummaryObjectives: 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.Methods: 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.Results: 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 Stand -ard of China (Chinese EHR Standard). Meta-data attributes are grouped into six parts: identification, definition, representation, relation, usage guides, and administration.Discussions and Conclusion: OpenPCR is an open metadata schema based on research registration standards, standards of the Clinical Data Interchange Standards Consortium (CDISC) and Chinese healthcare related stand -ards, 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. |
Databáze: | OpenAIRE |
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