Adapting the Medical Core Data Set Framework for Nursing: A Conceptual Review of the German Medical Informatics Initiative

Since 2016, the Medical Informatics Initiative (MII) has been developing an interoperable research data infrastructure based on HL7 FHIR and international terminologies such as SNOMED CT and LOINC. To achieve sustainable digitalization, nursing routine data must also be integrated, though they are currently documented in a heterogeneous and fragmented manner. This conceptual review examined which modules of the MII Core Dataset (MII-KDS) are transferable to the field of nursing, which require adaptation, and which new modules should be specified. The review was based on a selective literature search (2015-2025) and an interdisciplinary expert assessment involving nursing science, health science, and medical informatics. Results indicate that Person, Demographics, and Medication modules are directly transferable, while Encounter, Diagnosis, and Procedures require nursing-specific extensions. Three additional modules are proposed: Nursing Aids, Outcomes, and Care Planning / Care Process. The findings confirm the structural compatibility of nursing data models with medical standards while emphasizing challenges such as semantic heterogeneity, missing classifications, and governance issues. The MII-KDS thus offers a robust foundation for developing a nursing core dataset. Further work should focus on semantic harmonization and integration into existing infrastructures.