The European Medicines Agency (EMA) and the European Medicines Regulatory Network established a coordination centre to provide timely and reliable evidence on the use, safety and effectiveness of medicines for human use, including vaccines, from real world healthcare databases across the European Union (EU).

This capability is called the Data Analysis and Real World Interrogation Network (DARWIN EU®).

How does DARWIN EU make health data count?
Cover of the fourth annual report on regulatory-led studies using RWD
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Fourth annual report on regulatory-led studies using RWD published

EMA has published the fourth annual report on regulatory-led studies using RWD. This report outlines the progress in integrating real-world evidence (RWE) into regulatory decision-making, aligned with the European Medicines Regulatory Network (EMRN) strategy to 2028 and in anticipation of the provisions from the new pharmaceutical legislation. It comprises two RWE generation pathways coordinated by the European Medicines Agency (EMA): DARWIN EU®, and studies commissioned via framework contracts.

Highlighted Studies

Visual abstracts for ten key DARWIN EU® studies

Data Quality Dashboard

The DataQualityDashboard (DQD) is an R package maintained by the OHDSI community. It performs a set of over 3000 standardised checks on a populated OMOP CDM instance. The goal is to evaluate observational data quality in a systematic and transparent way.

The quality checks are organized according to the Kahn Framework which uses a system of categories and contexts that represent strategies for assessing data quality. DQD contains 24 checks defined within this framework that can be systematically executed against all relevant tables and fields in the OMOP CDM.

Examples of checks executed by DQD are:

  • does the table/field exist, is populated and does it have the right data type (cdmField, cdmDataType, isRequired)
  • does the field follow the standard semantic interoperability (isStandardValidConcept)
  • gender-specific diagnosis/procedure associated with correct person gender (gender)
  • measurement value within extreme ranges (valueLow, valueHigh)

Clair Blacketer, Frank J Defalco, Patrick B Ryan, Peter R Rijnbeek, Increasing trust in real-world evidence through evaluation of observational data quality, Journal of the American Medical Informatics Association, Volume 28, Issue 10, October 2021, Pages 2251–2257, https://doi.org/10.1093/jamia/ocab132

 

 

 

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