Streamlining Clinical Data Management: Eliminating Redundancy To Increase Efficiency

By Ashlee Curtis, inSeption Group

Improving clinical data management requires an understanding of the root issues — identifying which data points are essential, how those data points are used and coded for interpretation after they are entered by the site, and then determining which data-centric tasks can be completed by data management personnel, statisticians, and clinical scientists.

In addition to scrubbing unnecessary data points from a study protocol and EDC system before the trial starts, data collection and management can be streamlined by addressing issues throughout the study. Under most studies, the data team asks the site for interpretation, or the sponsor asks the CRA for feedback on the build, and that collective feedback contributes to modifying the study build. Such collaboration helps to eliminate the cycle of data hoarding and can spare sites significant work.

Improving the timing of some tasks, assigning them to different parties, and fostering team communication promotes better operating conditions for the entire study team. The way the teams are built and how they work together is the linchpin of study progress.