Migrating a Well-Established Longitudinal Cohort Database From Oracle SQL to Research Electronic Data Entry (REDCap):...

Area of Science:

• Medical Informatics
• Epidemiology
• HIV Research

Background:

• Large multicenter studies require user-friendly electronic data collection tools for high-quality research data.
• The Swiss Mother and Child HIV Cohort Study (MoCHiV), a longitudinal study since the 1980s, historically used paper-based data collection.
• Research Electronic Data Capture (REDCap) is a software solution for creating research databases with integrated electronic data entry interfaces.

Purpose of the Study:

• To develop a user-friendly graphical interface for electronic data entry for physicians and study nurses in the MoCHiV study.
• To migrate existing MoCHiV data from an Oracle SQL database to the REDCap platform.

Main Methods:

• The MoCHiV study collects data on obstetric events for women with HIV and children born to mothers with HIV.
• Data stored in Oracle SQL were cleaned, formatted, and migrated to REDCap using R for data processing and structure definition.
• REDCap database structure was defined, including branching logic, and data underwent systematic checks for compliance before and after import.

Main Results:

• A systematic pipeline was established for data cleaning, formatting, and comparison, involving database design in REDCap, data preparation, and migration.
• R was utilized to generate REDCap-specific variables and numbering for repeated events, enabling a relational data structure.
• Add-on features like data access groups, redirections, and summary reports were integrated to enhance usability in the multicenter MoCHiV study.

Conclusions:

• The migration from Oracle SQL to REDCap was successfully achieved by integrating Oracle SQL, R, and REDCap with a systematic data management pipeline.
• REDCap provides a flexible platform for customized study designs, including longitudinal studies with diverse data arms.
• Preprocessing large datasets for REDCap requires additional software, such as R, for effective data formatting and cleaning to meet structural requirements.