Clinical data management (CDM) is the process of collecting, cleaning, and securing the data a clinical trial produces so it is accurate, complete, and ready for statistical analysis. Every efficacy result and safety signal in a regulatory submission depends on it.<\/p>\n\n\n\n
Trials now generate far more data than they did a decade ago. Total data points in phase 3 trials grew from about 929,000 in 2012 to about 3.56 million in 2020<\/a>.<\/p>\n\n\n\n In this guide, we break down what CDM covers and the stages of the process. We also cover the systems teams use, the rules that govern them, and how to judge data quality.<\/p>\n\n\n\n\n\n Clinical data management is the discipline that turns raw trial observations into a reliable, analysis-ready database. It covers planning what to collect, capturing it, cleaning it, coding it, and locking it for analysis.<\/p>\n\n\n\n A clinical data manager usually owns this work. Their goal is simple: the final database must match what happened to participants, and every change must be traceable.<\/p>\n\n\n\n CDM covers five core activities:<\/p>\n\n\n\n CDM sits between the clinic and the biostatistician. Sites record what they observe. Data managers make sure those records are complete, consistent, and defensible before anyone runs a single analysis.<\/p>\n\n\n\n CDM is the work. EDC, CDMS, and CTMS are software that supports parts of it. People often use the terms interchangeably, which causes confusion when teams evaluate vendors.<\/p>\n\n\n\nWhat is clinical data management?<\/strong><\/h2>\n\n\n\n
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How is clinical data management different from EDC, CDMS, and CTMS?<\/strong><\/h2>\n\n\n\n