Why R Matters for Clinical Data Management

Clinical data management is increasingly dependent on the ability to move between data collection systems, statistical software, reporting tools, and documentation workflows. In many studies, the primary database may be implemented in REDCap, OpenClinica, Medidata Rave, Castor, or another electronic data capture system. However, data managers often need to perform tasks that go beyond the point-and-click interface of the database. They may need to compare exports, check data consistency across instruments, generate query lists, reconcile laboratory files, prepare monitoring reports, summarize missingness, inspect patterns across sites, or document a cleaning decision in a way that can be repeated later. R is valuable because it allows these tasks to be written as reusable scripts rather than performed manually each time [@rcore2024r; @wickham2023r4ds].