ArticleBMJ open2022
Existing barriers and recommendations of real-world data standardisation for clinical research in China: a qualitative study.
Article in BMJ open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Integrated Implementation Strategies to Promote the Use of AI-Assisted Diagnostic Software for Lung Nodule Screening in China: Process Evaluation Based on the RE-AIM Framework.JMIR formative research · 2026Article
- Navigating barriers to real-world evidence utilization for drug regulatory affairs and market access in Saudi Arabia.Frontiers in pharmacology · 2025Article
- Use of Real-World Evidence in Regulatory Decisions for Traditional Chinese Medicine: Current Status and Future Directions.Therapeutic innovation & regulatory science · 2024Review
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo investigate the existing barriers and recommendations of real-world data (RWD) standardisation for clinical research through a qualitative study on different stakeholders.
designThis qualitative study involved five types of stakeholders based on five interview outlines. The data analysis was performed using the constructivist grounded theory analysis process.
settingEight hospitals, four hospital system vendors, three big data companies, six medical products companies and four regulatory institutions were included.
participantsIn total, 62 participants from 25 institutions were interviewed through purposive sampling.
resultsThe findings showed that the lack of clinical applicability in existing terminology standards, lack of generalisability in existing research databases, and lack of transparency in existing data standardisation process were the barriers of data standardisation of RWD for clinical research. Enhancing terminology standards by incorporating locally used clinical terminology, reducing burden in the usage of terminology standards, improving generalisability of RWD for research by using clinical data models, and improving traceability to source data for transparency might be feasible suggestions for solving the current problems.
conclusionsEfficient and reliable data standardisation of RWD for clinical research can help generate better evidence used to support regulatory evaluation of medical products. This research suggested enhancing terminology standards by incorporating locally used clinical terminology, reducing burden in the usage of terminology standards, improving generalisability of RWD for research by using clinical data models, and improving traceability to source data for transparency to guide efforts in data standardisation in the future.
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