Recommended data elements for health registries: a survey from a German funding initiative.

Background: The selection of data elements is a decisive task within the development of a health registry. Having the right metadata is crucial for answering the particular research questions. Furthermore, the set of data elements determines the registries' readiness of interoperability and data reusability to a major extent.

Cross-Registry Benchmarking of Data Quality: Lessons Learned.

Feedback of data quality measures to study sites is an established procedure in the management of registries. Comparisons of data quality between registries as a whole are missing. We implemented a cross-registry benchmarking of data quality within the field of health services research for six projects.

FAIR and Quality Assured Data - The Use Case of Trueness.

The FAIR Guiding Principles do not address the quality of data and metadata. Therefore, data collections could be FAIR but useless. In a funding initiative of registries for health services research, trueness of data received special attention.

[Germany-wide, Web-based ParaReg Registry for Lifelong Monitoring of People with Spinal Cord Injury: Data Model, Ethico-legal Prerequisites and Technical Implementation].

Objective: In Germany, treatment paths for patients with acute spinal cord injury (SCI) differ considerably depending on intrinsic, disease-specific and extrinsic factors. Which of these factors are associated with improved outcome with fewer subsequent complications and inpatient re-admissions is not clear. The German-wide, patient-centered, web-based ParaReg registry will be implemented to improve the long-term quality of patient care and the planning of treatment paths with increased cost-effectiveness.