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Adapting the Medical Core Data Set Framework for Nursing: A Conceptual Review of the German Medical Informatics
Julia Röglin1, Doreen Werner2, Lisa Dobbert2
1Data Integration Center Department, Medical University Lausitz - Carl Thiem, Cottbus, Germany.
Studies in Health Technology and Informatics
|May 23, 2026
Summary
The Medical Informatics Initiative (MII) Core Dataset is adaptable for nursing data, requiring extensions for specific areas. This integration aims to improve digital health records and interoperability in nursing.
Area of Science:
- Medical Informatics
- Nursing Informatics
- Health Data Standards
Background:
- The Medical Informatics Initiative (MII) has established an interoperable research data infrastructure using HL7 FHIR and standards like SNOMED CT and LOINC since 2016.
- Integrating heterogeneous nursing routine data is crucial for sustainable healthcare digitalization but faces challenges due to fragmented documentation.
- Existing medical data models need evaluation for their applicability to nursing data.
Purpose of the Study:
- To assess the transferability of existing Medical Informatics Initiative (MII) Core Dataset (MII-KDS) modules to nursing.
- To identify necessary adaptations and new modules for incorporating nursing data into the MII-KDS.
- To propose a framework for a comprehensive nursing core dataset aligned with medical informatics standards.
Main Methods:
- A conceptual review based on a selective literature search (2015-2025).
- Interdisciplinary expert assessment involving nursing science, health science, and medical informatics professionals.
- Analysis of module transferability, required adaptations, and the specification of new modules for nursing data.
Main Results:
- Modules such as Person, Demographics, and Medication are directly transferable from the MII-KDS to nursing.
- Encounter, Diagnosis, and Procedures modules require nursing-specific extensions for accurate representation.
- Three new modules are proposed: Nursing Aids, Outcomes, and Care Planning/Care Process.
Conclusions:
- The MII-KDS provides a compatible foundation for a nursing core dataset, demonstrating structural alignment with medical standards.
- Challenges include semantic heterogeneity, lack of standardized nursing classifications, and governance issues.
- Further efforts are needed for semantic harmonization and integration into existing healthcare infrastructures to realize full potential.
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