Researchers Develop Nursing Fall-Prevention Minimum Dataset
In 2026, researchers from Hochschule Bochum and Fraunhofer institutes developed a FHIR-based nursing minimum dataset focused on fall prevention in long-term care. They used literature reviews, co-design workshops with 12 experts, and a quantitative survey of 158 practitioners to define 8 basic and 11 extension modules, then translated items into a FHIR implementation guide. The dataset aims to standardize nursing data to enable AI-based analysis and interoperable cross-sector research.
Key Points
- 1Defines FHIR-based nursing minimum dataset for fall prevention comprising 8 basic and 11 extension modules.
- 2Addresses fragmented documentation by standardizing terms through literature, workshops, and a survey of 158 practitioners.
- 3Enables interoperable, AI-ready nursing data and supports research, analytics, and cross-sector long-term care solutions.
Scoring Rationale
Strong methodological development and FHIR-backed implementation increase usability, but scope primarily targets German long-term care settings.
Sources
Public references used for this report.
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