DQ-SR: Towards the Standardization of Data Quality Reports

Area of Science:

• Health Informatics
• Data Standards
• Information Systems

Background:

• Existing data quality frameworks distinguish between internal verification and external validation.
• Multi-site networks (e.g., German MII, European EHDS) require robust solutions for external data validation.
• There is a growing demand for standardized data quality reporting in complex health networks.

Purpose of the Study:

• To investigate the feasibility of specifying standardized data quality reports as HL7 FHIR resources.
• To address the need for external data validation solutions in multi-site networks.
• To define constraints for data quality summary reports (DQ-SRs) used in validation contexts.

Main Methods:

• Defined constraints for data quality summary reports (DQ-SRs) suitable for external validation.
• Developed a prototypical implementation of DQ-SRs using FHIR R4 MeasureReports.
• Utilized German census data for age and gender distributions as an example use case.

Main Results:

• Demonstrated that data quality reports can be specified as HL7 FHIR resources.
• Provided a concrete example of DQ-SR implementation using FHIR R4 MeasureReports.
• Established a comprehensive specification for DQ-SRs, serving as an Implementation Guide.

Conclusions:

• Standardized data quality reports can be effectively implemented using HL7 FHIR resources.
• The proposed DQ-SR specification and implementation can support external data validation needs.
• This work aims to inspire further standardization of data quality reports in healthcare and research.