Which is the most important reason for why a data manager would review data before a monitor reviews it?

The most important reason for a data manager to review data before a monitor is to enhance the efficiency and effectiveness of the overall data cleaning and verification process. By performing a central review first, the data manager can use programmed edit checks and manual review to identify inconsistencies, outliers, and missing data across the entire study database. This allows discrepancies to be flagged (queried) in the system before the monitor conducts an on-site visit. The monitor can then focus their valuable on-site time on resolving these pre-identified issues with site staff and performing Source Data Verification (SDV), rather than discovering basic data entry errors that could have been caught centrally.

A. Data managers write the Data Management Plan that specifies the data cleaning workflow.

This is a statement of responsibility. While true, it describes what a data manager does (planning), not the strategic reason for the specific timing of the review.

C. Data managers have access to programming tools to identify discrepancies.

This describes a capability or tool used by data managers. It enables the pre-review but is not the fundamental reason why the pre-review is important for the workflow.

D. The GCDMP recommends that data managers review data prior to a monitor's review.

While this workflow aligns with the principles of Good Clinical Data Management Practices (GCDMP), the recommendation exists because of the operational benefit described in option B. Option B is the underlying reason for the best practice.

1. Society for Clinical Data Management (SCDM). (2019). Good Clinical Data Management Practices (GCDMP v2).

Section 5.5, Data Review and Query Management: This section details the ongoing process of data review performed by the data management team, which includes both automated and manual checks. It states, "Data review is an ongoing process that occurs from the first data received until database lock." This central, ongoing review logically precedes a monitor's periodic, on-site review to ensure efficiency. The central review identifies issues for the monitor to address during site visits.

2. Krishnankutty, B., Bellary, S., Kumar, N. B. R., & Moodahadu, L. S. (2012). Data management in clinical research: An overview. Indian journal of pharmacology, 44(2), 168–172.

Page 170, "Data validation" section: The article describes the process where "validation procedures... check the data for its completeness, consistency and accuracy." This is a core data management function. The text distinguishes this from the Clinical Research Associate's (monitor's) role of source data verification. A central data validation before the monitor's visit makes the monitor's subsequent verification more targeted and efficient.

DOI: https://doi.org/10.4103/0253-7613.93842

3. Gassman, J. J., et al. (2019). A guide to data management for clinical trials. In Clinical and translational science, 12(4), 326–333.

Page 329, "Data Cleaning" section: The authors describe data cleaning as an iterative process involving query generation. "Queries are typically generated by the data management/coordinating center and sent to the clinical sites for resolution." This central generation of queries by data management is the process that occurs before a monitor might visit the site to help resolve them and perform SDV.

DOI: https://doi.org/10.1111/cts.12635