Clinical Data Validation

While more clinical trials are outsourced to CROs/EDC vendors, the needs for ensuring clinical data quality become increasingly important. Sponsor companies with very limited data management resources need an easy-to-use tool to allow clinical data managers to validate existing clinical data, and catch the data issues in the early stage.

The process of clinical data validation is to apply a set of validation rules to datasets. A validation rule is like an edit check in EDC world, however it can be defined and applied dynamically at any time.

The validation engine is vendor neutral and works with both CDISC and non-CDISC data. No EDC system, SQL, or SAS knowledge is required. The same validation tool can be applied to any clinical studies from any CRO vendors regardless of data capture systems they use.

Key Function Overview

Data Validation Screenshot

Define your edit-checks anytime (see above) and click to get report. The unique "catch-on-the-spot" validation report, not only captures "dirty" data, also highlights the reasons.

Supported Validation and Edit-checks

Supported Validation Types  Examples
Ensure required field and field completeness  
Data format compliance Date of birth, lab data with correct unit
Values within designed ranges Gender (M/F), vital sign valid ranges, etc.
In-form cross-field check AE end date must be later than its start date
Cross-form field check AE start date must be later than the screen date
Logic-support cross-field check If other choice is checked, the "other" value must be set
Advanced programmed edit-check/validation Subjects of protocol deviations/violations based on designated criteria