Which of the following statements would be BEST included in a data management plan describing the process for making self-evident corrections in a…

A Data Management Plan (DMP) must prospectively define all data handling procedures to ensure consistency and quality. The best practice for managing self-evident corrections involves two key principles outlined in Good Clinical Data Management Practices (GCDMP). First, the specific types of changes that are permissible must be pre-defined in a set of conventions within the DMP. This prevents subjective or arbitrary changes. Second, because the Principal Investigator is ultimately responsible for all site data, any changes made centrally—even obvious ones—must be documented and communicated to the investigative site. This ensures transparency and maintains the investigator's oversight.

A. Making changes "without further documentation" violates core principles of traceability, transparency, and investigator oversight required by GCDMP.

B. Internal review is a good quality control step, but this statement omits the essential requirements of pre-defined conventions and communication to the site.

C. This negates the efficiency and purpose of a self-evident correction process, which is designed to handle obvious errors without unnecessarily burdening the site.

1. Society for Clinical Data Management. (2023). Good Clinical Data Management Practices (GCDMP v2).

Section 4.6.10, Data Review and Cleaning Procedures: This section specifies that the DMP must describe the procedures for data review, query generation, and management, including "any pre-approved data corrections that may be applied by the data manager." This supports the need for "listed conventions."

Section 5.4.4, Discrepancy Management: This section emphasizes that "Any changes made to the clinical data by the CDM team should be documented and communicated to the investigator," which supports the requirement to document changes to the investigative site.

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/Data cleaning": The article states, "The data management plan or a separate data validation plan should describe the data validation activities in a clinical trial... Any discrepancies generated are resolved with the investigator." This highlights the principle of resolving data issues, including corrections, in communication with the investigator. https://doi.org/10.4103/0253-7613.93842

3. Tudur Smith, C., et al. (2012). The data management plan: a practical guide to documenting the management of data in a clinical study. Trials, 13(1), 1-7.

Section "Data checking, validation and error handling": The paper notes the importance of documenting procedures for handling data errors, stating, "The DMP should describe the procedures for checking and validating data... and the process for resolving any inconsistencies." This reinforces the need for a pre-specified process as described in option D. https://doi.org/10.1186/1745-6215-13-78