In general terms, quality is defined as an attribute of a product or service that defines the degree to which it meets customer and other stakeholder needs within statutory and regulatory requirements or its fitness for intended use.
The same principle applies to data and for the purpose of this document, EMA adopts the following definition:
Data quality is defined as fitness for purpose for users’ needs in relation to health research, policy making, and regulation and that the data reflect the reality, which they aim to represent.
Therefore, this DQF restricts its scope to aspects of DQ that are relevant for regulatory decision making.
This document is the first release of the EU data quality framework for medicines regulation and addresses high level principles and procedures that apply across the European Medicines Regulatory Network (EMRN)’s regulatory activities.
This framework provides general considerations on data quality that are relevant for regulatory decision making, definitions for data dimensions and sub-dimensions, as well as their characterization and related metrics.
It provides an analysis of what data quality actions and metrics can be put in place in different scenarios and introduces a maturity model to drive the evolution of automation to support data-driven regulatory decision making.
This document is intended to be an overall umbrella from which more focused recommendations can be derived for specific regulatory domains with specified metrics and checks.