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

Objectives: The main goal is to develop an automated process for connecting Research Electronic Data Capture (REDCap) instances in a clinical trial network to allow for deidentified transfer of research surveys to cloud computing data commons for discovery. Materials and Methods: To automate the process of consolidating data from remote clinical trial sites into 1 dataset at the coordinating/storage site, we developed a Hypertext Preprocessor script that operates in tandem with a server-side scheduling system (eg, Cron) to set up practical data extraction schedules for each remote site. Results: The REDCap Application Programming Interface (API) Connection provides a novel implementation for automated synchronization between multiple REDCap instances across a distributed clinical trial network, enabling secure and efficient data transfer between study sites and coordination centers. Additionally, the protocol checker allows for automated reporting on conforming to planned data library protocols. Discussion: Working from a shared and accepted core library of REDCap surveys was critical to the success of this implementation. This model also facilitates Institutional Review Board (IRB) approvals because the coordinating center can designate which surveys and data elements to be transferred. Hence, protected health information can be transformed or withheld depending on the permission given by the IRB at the coordinating center level. For the NIH HEAL clinical trial networks, this unified data collection works toward the goal of creating a deidentified dataset for transfer to a Gen3 data commons. Conclusion: We established several simple and research-relevant tools, REDCAP API Connection and REDCAP Protocol Check, to support the emerging needs of clinical trial networks with increased data harmonization complexity.