Data Reconciliation and Validation Flashcards

What is the primary purpose of data reconciliation in clinical data management?

Answer: To ensure consistency and completeness of data across multiple sources

Data reconciliation ensures that data from different sources (e.g., EDC, lab systems, IRT) are consistent, complete, and in agreement before database lock.

During external data reconciliation, a discrepancy is found between the EDC system and the central lab data. What is the appropriate first step?

Answer: Investigate the source of the discrepancy using original source documents

Investigating the discrepancy against source documents is the correct first step to determine which record is accurate before making any changes.

Which type of validation check verifies that a date entered in a CRF falls within the acceptable range of the study period?

Answer: Range check

Range checks verify that a data value falls within predefined acceptable minimum and maximum boundaries, such as valid dates within a study timeline.

What does a 'discrepancy management' process in clinical data management primarily involve?

Answer: Identifying, documenting, resolving, and closing data queries

Discrepancy management is the systematic process of identifying data issues via queries, tracking them, obtaining site responses, and closing them once resolved.

In clinical data management, a 'hard edit' (or hard stop) in an EDC system means:

Answer: The system prevents data entry from being saved until the error is corrected

Hard edits prevent the user from saving or progressing past a data entry point until the entered value meets the validation criteria.

Lab data reconciliation typically requires comparing EDC-entered lab values against which reference?

Answer: Listings or data transfers from the central or local laboratory

Lab data reconciliation compares the lab values recorded in the EDC against the data provided by the central or local laboratory in data transfer files or listings.

Which metric is commonly used to measure the quality of data during validation activities?

Answer: Error rate (number of errors per 100 fields entered)

Error rate, typically expressed as errors per 100 or 1,000 fields, is a standard metric for assessing data quality and entry accuracy.