TheQuery frequency counts per data element(Option D) is the best metric for identifyingdata trends and potential systemic data issuesin clinical trials.
According to theGood Clinical Data Management Practices (GCDMP, Chapter: Data Quality Assurance and Control),trend analysisinvolves identifying recurring data issues across subjects, sites, or variables to detect training gaps, protocol misinterpretation, or CRF design flaws. A high number of queries generated for specific fields (e.g., visit date, lab values, or dosing information) may indicate systemic problems such as unclear CRF instructions or site-level misunderstandings.
While metrics such aspercent of data cleaned (A)andtime to database lock (B)reflect overall progress and efficiency, they do not identifyspecific data pattern issues. Thenumber of subjects screened/enrolled (C)pertains to recruitment rather than data quality.
Therefore,query frequency per data elementprovides actionable insights for quality improvement, process refinement, and early identification of potential risks.
Reference (CCDM-Verified Sources):
SCDM Good Clinical Data Management Practices (GCDMP), Chapter: Data Quality Assurance and Control, Section 6.3 – Metrics and Trend Analysis
ICH E6 (R2) Good Clinical Practice, Section 5.18.4 – Risk-Based Quality Review and Data Trends
FDA Guidance for Industry: Oversight of Clinical Investigations – Risk-Based Monitoring, Section 6 – Data Metrics and Trend Evaluation
