Visual Data Analytics in Clinical Data Management
01 Feb 2019
Clinical Data Management is the back bone of every successful clinical trial, conducted at single or multiple sites. Considering the complexity of operational aspects of the trials, it is essential to check the data quality and trend analysis of data across the site(s). Visual data analytics is a helpful approach to identify and trigger the various risks’ alerts associated with Quality and Timelines at an earlier stage of the study/trial.
The term, Visual Data Analytics, means the presentation of the numerical data in a graphical manner, which can be derived from the CDMS application. More precisely, visual data analytics is an interactive process of data processing and presenting. Interpretation from such tools would help in the decision making process. It can allow the stakeholders to see the status of data more clearly, act smarter and react more quickly.
Various aspects where Visual Data Analytics can be applied
Concepts of Visual Data Analytics applicable for graphical representation of Clinical Trial data are:
- Pending Data Entry Status – Helps team to know the status of anticipated data entry
- Recruitment ratio – Controls skewed recruitment in the trail
- Query Matrices (like DCF by site and by subject) – Provides discrepancy status
- Query Ageing and Query trending – Focus on pending DCF resolution & Type of queries
- Repetitive queries on critical variables – Helps to identify site training requirements
- Data review matrices – Updates on the Monitoring & DM review process
Visual Data Analytics are applicable throughout the lifecycle of the trial. It provides ongoing data trending and comparatives across and within the trial sites. It significantly helps the project management team to take rapid and confident decisions to safeguard the quality and timelines of the project.