Data Quality Management and Query Resolution: Orientation
Learning Objectives
Learning Objectives
Learning Objectives
Explain the meaning of data quality in clinical research and why it must be managed continuously.
Describe major dimensions of data quality, including accuracy, completeness, consistency, validity, timeliness, uniqueness, and integrity.
Identify common sources of data quality problems across the clinical research lifecycle.
Develop a data quality plan that defines checks, responsibilities, timelines, and escalation procedures.
Use REDCap Data Quality tools and reports to detect missing, invalid, inconsistent, and duplicate data.
Explain the query management workflow from discrepancy identification to query closure.
Write clear, neutral, non-leading data queries.
Interpret query metrics and use them to improve study operations.
Explain central monitoring and risk-based monitoring approaches.
Describe database freeze and database lock and the data management work required before each milestone.