Why conduct clinical data management at all? 3 reasons and 1 goal!

Why do we conduct clinical data management the way we do it for our clinical studies?  Why do we plan, conduct and document clinical data management? Why do we have to review each clinical data management step? Why do we implement numerous edit checks and do we query inconsistencies?

 

3 reasons and 1 goal!
1. Data management takes care that collected individual subject stories are transformed into a structure and format with which analysis can be done. Individual subject data doesn’t give insight in population patterns, and doesn’t allow for creating graphs, frequency tables and other study results. Therefore the first reason that CDM exists is that they translate these individual subject stories as collected in (e)CRFs to datasets with which the study analysis is done.

2. Data Management checks if data is logical, plausible and complete. If data represents what truly happened with the subjects undergoing the intervention. In the words of the Institute of Medicine; data management verifies data so that conclusions and interpretations can be drawn equivalent to error-free data.

3. The data management work should be reproducible, in other words; GCP compliant. Meaning that if the work is repeated, the same results are produced. For this part the data management process and the clinical data delivered are subject to inspection by regulatory authorities.

 

What should happen if you didn't perform clinical data management? You didn’t do any data verification and didn’t document what you planned and finally carried out. The study results, the conclusion and interpretations could be equivalent to those derived from error-free data. But you could not guarantee such a thing! And here we have our clinical data management GOAL; guaranteed data quality for each clinical study.

 

© 2009 ProCDM, Maritza Witteveen

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