Data Quality Tip # 1: Understand the purpose and objectives of the study.
The study protocol serves as a road map for understanding the context of the data being collected. A good understanding of the why’s and when’s of the data being collected is an important aspect pertaining to quality data.
Data Quality Tip # 2: Usage of appropriate reporting tools.
Creating reports for key data items like adverse events, screening and enrollment, Query status and aging, site performance, and their analysis will help address inconsistency/errors with data items that cannot be otherwise picked up using programmed edit checks.
Data Quality Tip # 3: Stay on top of missing data.
Define a completion timeline for missing data and follow up with the sites or CRA to get the missing data. This would avoid any undue pressure at a database lock.
Here are some thoughts on how the 5-S Process of Total Quality Management (TQM) could be implemented for data cleaning:
Remember – Garbage in is Garbage out! A clean data input paves the way for a clean data output, which subsequently helps to transform the ‘data’ into useful ‘information’, ultimately leading the business to making well informed decisions.