Abstract
Clinical data is the staple of modern learning health systems. It promises to accelerate biomedical discovery and improves the efficiency of clinical and translational research but is also fraught with significant data quality issues. This paper aims to provide a life cycle perspective of clinical data quality issues along with recommendations for establishing appropriate expectations for research based on real-world clinical data and best practices for reusing clinical data as a secondary data source.
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