In my study investigating participation and experience within the primary healthcare system, utilizing case record forms (CRFs), I implemented several data management processes within REDCap to ensure data quality and integrity:
Audit Trail/Time Stamp: REDCap automatically tracked user actions and data modifications, including timestamps, providing a comprehensive audit trail for identifying changes and their originators. This was particularly crucial as health village volunteers were responsible for CRF data collection. To ensure data completeness and trace potential issues, a participant coding system was implemented alongside a data collector coding system. This allowed us to identify missing codes and trace them back to the responsible data collector.
User Authentication and Access Control Level: Access to the data was restricted based on user roles and permissions within REDCap. This ensured that only authorized individuals could access and modify sensitive information. REDCap’s user management features allowed for granular control over edit and view permissions for the CRFs.
Edit Check and Logical Check: REDCap’s built-in data validation features helped prevent errors during data entry, such as enforcing numerical range limitations. Additionally, custom logic checks were implemented within the platform to identify inconsistencies and potential outliers, such as automatically skipping to the next question based on specific answer choices.
Data Backup and Recovery Plan: Data backups were conducted regularly on a secure PCM database. While the specific backup procedures within PCM might require further verification, data was also downloaded locally to our computers, ensuring comprehensive information protection.
Furthermore, the study employed a cross-sectional design, with data collection occurring in April and July.