Standardized Data Models for Clinical Research: Challenges and Opportunities in China
Authors: Y. Zhang, L. Wang, H. Li, J. Chen
Standardized data models are essential for enabling interoperability and secondary use of clinical data in research. This paper reviews the current landscape of data models for clinical research, focusing on the challenges and opportunities in China. We analyze the adoption of common data models such as OMOP CDM and PCORnet, and discuss the barriers to implementation, including data heterogeneity, privacy concerns, and lack of standardized vocabularies. We also highlight the potential of emerging technologies like FHIR and AI to facilitate data standardization. Our findings suggest that a collaborative approach involving stakeholders, investment in infrastructure, and policy support are critical for advancing data-driven clinical research in China.
