Dealing with multiple data sources:
Fundamental aspects of data integration and reconciliation for high data quality
As technology’s penetration in the clinical trials space has become spectacular, the industry has also significantly increased the volume of data collected, the variability of data sources, as well as the number of vendors and systems used. This generates a rising complexity in clinical trials operational structures, potentially jeopardizing not only the user experience but also the quality and integrity of the clinical trials’ data.
In the increasingly frequent case of a clinical trial encompassing several systems such as eCRF, eConsent, IRT/IxRS, eCOA, and even potentially wearable data collection, several questions arise:
- How can we maximize data entry without compromising data quality?
- How can we reconcile data from these multiple sources without putting at risk each clinical study milestone?
- How can we anticipate and organize data management activities so that the data reconciliation process does not become an endless nightmare?
Through detailed examples, this webcast describes specific data management practices and customized approaches that can be put in place to meet the evolving needs of data integration and data reconciliation from multiple data sources. The perspective of a data management expert, Sonja Banjac, Phd, Data Manager & Analyst at Kayentis, demonstrates how strong coordination and expert data management activities will be key to support new generation clinical trials.
Watch the webcast 👇
