Currently submitted to: JMIR Medical Informatics
Date Submitted: Jul 12, 2026
Open Peer Review Period: Jul 16, 2026 - Sep 10, 2026
(currently open for review)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Configuring REDCap to Support Complex Systematic Review Workflows: A User-Centered Design and Implementation Case Study.
ABSTRACT
Background:
Background:
Systematic literature reviews require transparent and reproducible workflows for screening, data abstraction, critical appraisal, discrepancy resolution, and auditability. While most low-cost, institutionally accessible systematic review platforms can streamline citation screening and review management, systematic reviews with complex structures/themes may require more flexible data structures, conditional workflows, and customized abstraction tools.
Objective:
Objective:
This paper describes the user-centered design, implementation, and field testing of a comprehensive REDCap-based system configured to support data abstraction, critical appraisal, reviewer assignment, discrepancy management, and workflow tracking in a complex systematic literature review.
Methods:
Methods:
Development followed an iterative user-centered design process that included requirements elicitation, prototype construction, reviewer testing, feedback-driven refinement, and production deployment. REDCap instruments, branching logic, Data Access Groups, data quality rules, reports, and external modules were configured to support a two-reviewer workflow across article classification, abstraction, and critical appraisal.
Results:
Results:
The resulting REDCap project contained 37 data collection instruments (forms), 891 data fields, and four logic branches that controlled form display. Forms contained an average of 17 conditional branches (range: 1–31), reflecting the complexity of the review workflow. The system also incorporated eight external module integrations to extend REDCap functionality. Article screening and data abstraction were performed by 22 reviewers paired into 11 REDCap Data Access Groups (DAGs). At the time of reporting, the REDCap system had been operational for more than 8 months and supported the complete abstraction of 190 heterogeneous articles by the review team.
Conclusions:
Conclusions:
REDCap should not be viewed as a complete replacement for dedicated systematic review platforms, particularly for citation import, de-duplication, and title/abstract screening. However, it may provide a flexible, scalable, and cost-effective solution for complex post-screening systematic literature review workflows that require customized data abstraction, conditional critical appraisal, audit trails, reviewer coordination, and iterative refinement. We transformed REDCap from a participant-level data capture platform into an article-level post-screening data abstraction and review management system.
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Copyright
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