FHIR – Overdue Standard for Radiology Data Warehouses

Abstract

Background

In radiology, technological progress has led to an enormous increase in data volumes. To effectively use these data during diagnostics or subsequent clinical evaluations, they have to be aggregated at a central location and be meaningfully retrievable in context. Radiology data warehouses undertake this task: they integrate diverse data sources, enable patient-specific and examination-specific evaluations, and thus offer numerous benefits in patient care, education, and clinical research.

Method

The international standard Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) is particularly suitable for the implementation of such a data warehouse. FHIR allows for easy and fast data access, supports modern web-based frontends, and offers high interoperability due to the integration of medical ontologies such as SNOMED-CT or RadLex. Furthermore, FHIR has a robust data security concept. Because of these properties, FHIR has been selected by the Medical Informatics Initiative (MII) as the data standard for the core data set and is intended to be promoted as an international standard in the European Health Data Space (EHDS).

Conclusion

Implementing the FHIR standard in radiology data warehouses is therefore a logical and sensible step towards data-driven medicine.

Key Points

• A data warehouse is essential for data-driven medicine, clinical care, and research purposes.

• Data warehouses enable efficient integration of AI results and structured report templates.

• Fast Healthcare Interoperability Resources (FHIR) is a suitable standard for a data warehouse.

• FHIR provides an interoperable data standard, supported by proven web technologies.

• FHIR improves semantic consistency and facilitates secure data exchange.

Citation Format

• Arnold P, Pinto dos Santos D, Bamberg F et al. FHIR – Overdue Standard for Radiology Data Warehouses. Fortschr Röntgenstr 2024; DOI 10.1055/a-2462-2351

Keywords

PACS - Data Warehouse - diagnostic radiology - Artificial Intelligence - Fast Healthcare Interoperability Resources (FHIR)

Publication History

Received: 08 May 2024

Accepted after revision: 27 October 2024

Article published online:
06 December 2024

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