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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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FDA: US Food and Drug Administration; FHIR: Fast Healthcare Interoperability Resources.
The methods section is crucial for ensuring the accuracy and reliability of research findings. This study’s methodology encompasses the following aspects: computable phenotype development, phenotype distributed deployment, study period, data, and the process of reviewing medical records.
J Med Internet Res 2024;26:e54597
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While FHIR holds the potential to standardize data, various challenges persist. Most frequently named is the implementation of FHIR as an application, the complexity of the FHIR standard (including its nested structure), and the representational state transfer (RESTful) approach [14]. In particular, the complexity of the data structure makes it not readily available for processing and easy access to the end user.
J Med Internet Res 2024;26:e55148
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HL7 FHIR is the emerging standard for health care–specific data exchange and has been broadly adapted worldwide [8]. FHIR provides state-of-the-art technologies to modernize the current health care landscape using extensible resources as harmonized and semantically annotatable information units [9]. However, FHIR also provides mechanisms to natively define transformations on its structures.
JMIR Med Inform 2024;12:e57569
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FHIR Search and the FHIR standard did not provide the ability to express a feasibility query in the required scope [25] at the time of our research. Other query languages that could have been candidates, like CQL or SQL, are complex or data model specific, making the translation between different data models and their representation, as well as the generation of the syntax by a user interface, challenging.
JMIR Med Inform 2024;12:e58541
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HL7 API (HAPI) FHIR is a comprehensive implementation of FHIR in the Java language [56]. The API is available for both FHIR clients and servers [57]. Several studies used HAPI FHIR in the data model implementation process. Bennett et al [26] used the HAPI FHIR server in the process of validation, bulk export, and writing data to NDJSON files. Hong et al [29] used the API to put ovarian cancer data into FHIR resources. They also used the client API to upload structured FHIR data elements to the FHIR server.
JMIR Med Inform 2024;12:e58445
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