biostudies-literatureUnknown8(5)Schauer JM<h4>Objective</h4>Covariate-adaptive randomization algorithms (CARAs) can reduce covariate imbalance in randomized controlled trials (RCTs), but a lack of integration into Research Electronic Data Capture (REDCap) has limited their use. We developed a software pipeline to seamlessly integrate CARAs into REDCap as part of the all2GETHER study, a 2-armed RCT concerning HIV prevention.<h4>Materials and methods</h4>Leveraging REDCap's Data Entry Trigger and a separate server, we implemented software in PHP and R to automate randomizations for all2GETHER. Randomizations were triggered by saving a specific REDCap form and were automatically communicated to unblinded study personnel.<h4>Results</h4>Study arms were highly comparable, with differences across covariates characterized by Cohen's <i>d</i> = 0.003 for continuous variables and risk differences <2.4% for categorical/binary variables.<h4>Conclusions</h4>Our pipeline proved effective at reducing covariate imbalance with minimal additional effort for study personnel.<h4>Discussion</h4>This pipeline is reproducible and could be used by other RCTs that collect data via REDCap.JAMIA openooaf110https://www.ebi.ac.uk/biostudies/studies/S-EPMC12486239biostudies-literatureWorkflows to automate covariate-adaptive randomization in REDCap via data entry triggers.PMC12486239Rasmussen LVSwann GCiolino JDNewcomb MESchauer JMBroxton MOfalseWorkflows to automate covariate-adaptive randomization in REDCap via data entry triggers.<h4>Objective</h4>Covariate-adaptive randomization algorithms (CARAs) can reduce covariate imbalance in randomized controlled trials (RCTs), but a lack of integration into Research Electronic Data Capture (REDCap) has limited their use. We developed a software pipeline to seamlessly integrate CARAs into REDCap as part of the all2GETHER study, a 2-armed RCT concerning HIV prevention.<h4>Materials and methods</h4>Leveraging REDCap's Data Entry Trigger and a separate server, we implemented software in PHP and R to automate randomizations for all2GETHER. Randomizations were triggered by saving a specific REDCap form and were automatically communicated to unblinded study personnel.<h4>Results</h4>Study arms were highly comparable, with differences across covariates characterized by Cohen's <i>d</i> = 0.003 for continuous variables and risk differences <2.4% for categorical/binary variables.<h4>Conclusions</h4>Our pipeline proved effective at reducing covariate imbalance with minimal additional effort for study personnel.<h4>Discussion</h4>This pipeline is reproducible and could be used by other RCTs that collect data via REDCap.2025-01-01T00:00:00Z2025 Oct2026-06-04T02:23:20.303Z2026-05-04T03:13:08.747ZS-EPMC124862394104162410.1093/jamiaopen/ooaf110