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DermaDashboard: Bridging the Gap Between FHIR Standards and Clinical Usability
As health care institutions increasingly adopt FHIR to standardize data, there is a growing need for tools that enable accessible, exploratory analysis of FHIR-based datasets without requiring deep technical knowledge. In particular, there is an unmet need for lightweight, modular tools that can bridge the gap between the complex FHIR data standard and intuitive clinical interfaces used by health care professionals.
JMIR Cancer 2025;11:e73691
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develop the necessary attributes required to meet the objectives described earlier and (2) develop and test FHIR resource options to accurately describe and exchange these requirements.
JMIR Med Inform 2025;13:e71430
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Based on this semantic annotation, FHIR instances are created as digital representations of the QIs and then validated (Section 2.4). To ensure that the FHIR-encoded structured representations accurately reflect the intent of the original narrative QIs, the FHIR-encoded representations are back-translated into a format that can be understood and reviewed by clinicians (Section 2.5).
J Med Internet Res 2025;27:e77077
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Consumer Data is Key to Artificial Intelligence Value: Welcome to the Health Care Future
A crucial component of contemporary health data policy is the adoption of Fast Healthcare Interoperability Resource (FHIR), one of the most significant advancements in EMR data exchange [24]. Developed and maintained by Health Level 7 International (HL7), FHIR is an open, license-free standard that is publicly available and designed to promote seamless interoperability.
J Particip Med 2025;17:e68261
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Therefore, understanding how standards such as fast healthcare interoperability resources (FHIR), digital health technologies such as electronic health records (EHRs) systems, and emerging artificial intelligence (AI) applications such as explainable artificial intelligence (XAI) integrate with CDSS is essential for effective implementation.
This review seeks to expand on existing literature by examining CDSS design through the unique lens of a UCD perspective.
J Med Internet Res 2025;27:e63733
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In 2011, due to the rapidly growing amount of health data, HL7 started developing the Fast Interoperability Resources (FHIR), a standard that addresses the need for faster and better methods for interoperable data exchange.
FHIR was designed to be flexible and adaptable, making this standard easy to implement and suitable for a wide range of clinical processes. It uses a modern web-based application programming interface (API) [17].
JMIR Med Inform 2025;13:e64099
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Reflecting on this condition in the context of open health data ecosystems, we observe a salient difference between FHIR versus open EHR and OMOP, namely that the former is the only one that has been mandated—or at least strongly recommended—in some jurisdictions. Survey results on the state of FHIR show that the FHIR standard has been mandated or advised in 20 countries [9].
J Med Internet Res 2025;27:e66616
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A Validation Tool (VaPCE) for Postcoordinated SNOMED CT Expressions: Development and Usability Study
Ontoserver is currently the only Fast Healthcare Interoperability Resource (FHIR) terminology server that supports postcoordination at all. Ontoserver is used to validate the PCEs in combination with the FHIR service $validate-code [11]. This checks a PCE against specific coding systems, such as SNOMED CT. This method provides a validation result through a Representational State Transfer (REST) request that returns a JSON object [11].
JMIR Med Inform 2025;13:e67984
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Reference 33: FHIR-Spezifikation(https://mio.kbv.de/pages/viewpage.action?pageId=273318266)fhir
JMIR Nursing 2025;8:e60810
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