Validation Overview

Validation is necessary to ensure that data in Relevant is accurate. Data must be accurate in order to inform decision making and build trust amongst users. Also, Relevant’s default logic is aligned with UDS requirements; so, validating your data in Relevant’s data model works toward validating your UDS submission.

In addition to initial validation during implementation, it is a best practice to periodically repeat validation efforts as the way data is collected can change over time (for example, a new lab or medication requires updates to data mapping).

Relevant provides tools to validate the following concepts using random samples. Please click the links below for more details:

• Patients
• Visits
• Care Gaps
• Quality Measures

Relevant recommends validating Patients and Visits before moving on to Care Gaps and Quality Measures, because the latter rely on the former.