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Introducing a FHIR-Based Toolset for Analyzing Nursing-Related Data.

Steffen Netzband¹, Johann Frei¹, Florian Weber¹

¹IT-Infrastructure for Translational Medical Research, University of Augsburg, Germany.

Studies in Health Technology and Informatics

|July 1, 2025

Summary

This summary is machine-generated.

This study introduces an open-design framework using HL7 FHIR for nursing data analytics, addressing limited software solutions. It enables secure data exchange and visualization to improve nursing research and practice.

Keywords:

Data Analytics FHIR Nursing Informatics

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Area of Science:

Healthcare Informatics
Nursing Informatics
Health Data Standards

Background:

Data analytics can enhance nursing management and research but is limited by non-standardized data.
The HL7 Fast Healthcare Interoperability Resources (FHIR) standard provides structure, but nursing-specific FHIR analysis tools are scarce.
Developments in Germany's healthcare sector, including nursing FHIR specifications and secure data exchange infrastructure, provide a foundation for innovation.

Purpose of the Study:

To introduce an open-design framework for data-driven nursing research and practice.
To present software solutions for secure data exchange and the analysis/visualization of nursing-related FHIR resources.
To demonstrate the feasibility and potential of the framework in real-world nursing settings.

Main Methods:

Development of an open-design framework integrating German healthcare sector advancements.
Implementation of secure data exchange software (Kommunikation im Medizinwesen Care).
Creation of tools for evaluating and visualizing nursing FHIR resources (FHIR QR Vis, FHIR Nursing Dashboard).
Validation through case studies in a German nursing home and university hospital.

Main Results:

Successful implementation of a framework facilitating nursing data analytics.
Demonstrated feasibility of secure data exchange and visualization of nursing FHIR data.
Positive validation in case studies, showing potential for enhanced decision-making and workflow optimization.

Conclusions:

The developed framework and software solutions effectively support data-driven innovation in nursing.
The approach enhances secure data exchange and the utilization of nursing-related FHIR resources.
This work provides a foundation for improving nursing management, research, and practice through accessible data analytics.