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10 Important Metrics in Clinical Data Management
Clinical data management involves numerous metrics that must be tracked to ensure the quality and integrity of the data collected. Data quality, data entry timeliness, query resolution time, data monitoring, adverse event reporting, patient recruitment and retention, data accuracy, protocol deviations, database lock time, and data archiving are some of the most important metrics in clinical data management. Tracking these metrics can help ensure that the study is conducted as per the study protocol, and the data collected is accurate and reliable.
