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Automated multi-instance REDCap data synchronization for NIH clinical trial networks.

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Summary
This summary is machine-generated.

We developed automated tools to connect Research Electronic Data Capture (REDCap) instances for deidentified data transfer to cloud commons. This improves clinical trial data harmonization and discovery.

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Area of Science:

  • Clinical Informatics
  • Data Science
  • Biomedical Research

Background:

  • Clinical trial networks generate complex, distributed data.
  • Consolidating data from multiple sites is challenging.
  • Standardized data transfer is crucial for research discovery.

Purpose of the Study:

  • To develop an automated process for connecting Research Electronic Data Capture (REDCap) instances within a clinical trial network.
  • To enable deidentified transfer of research surveys to cloud computing data commons for enhanced data discovery.

Main Methods:

  • Developed a Hypertext Preprocessor (PHP) script for automated data extraction scheduling.
  • Utilized the REDCap Application Programming Interface (API) for synchronization between multiple REDCap instances.
  • Implemented a protocol checker for automated reporting on data library protocol adherence.

Main Results:

  • The REDCap API Connection facilitates automated synchronization across distributed clinical trial networks.
  • Secure and efficient data transfer between study sites and coordination centers is enabled.
  • Automated reporting on protocol adherence streamlines data quality management.

Conclusions:

  • Established REDCap API Connection and REDCap Protocol Check tools address clinical trial network data harmonization needs.
  • This automated approach supports deidentified data transfer to data commons for research.
  • Facilitates Institutional Review Board (IRB) approvals by enabling controlled data sharing.