Fast Healthcare Interoperability Resources (FHIR) is a next-generation interoperability standard created by HL7 that defines a set of modular, web-based Resources representing granular clinical and administrative concepts like Patient, Observation, or MedicationRequest. By combining the best features of previous standards with modern web technologies, FHIR leverages a RESTful API architecture using standard HTTP protocols, JSON, and XML formats to enable stateless, real-time data exchange between disparate healthcare systems.
Glossary
Fast Healthcare Interoperability Resources (FHIR)

What is Fast Healthcare Interoperability Resources (FHIR)?
A modern, RESTful API standard developed by HL7 that structures healthcare data into discrete, web-friendly resources to enable seamless, developer-friendly interoperability across electronic health records.
The standard is built around the concept of discrete, addressable resources that can be combined to solve complex clinical problems. FHIR supports multiple interoperability paradigms, including a RESTful API for direct access, a messaging paradigm for event-driven workflows, and a document paradigm for persistence. Its design prioritizes rapid implementation, with the SMART on FHIR framework adding an OAuth 2.0-based security layer to enable substitutable, third-party applications to run seamlessly within any compliant electronic health record system.
Key Features of FHIR
Fast Healthcare Interoperability Resources (FHIR) revolutionizes healthcare data exchange by combining the best features of previous standards with modern web technologies. Its component-based architecture enables granular data access and seamless integration.
Frequently Asked Questions
Clear, technical answers to the most common questions about the Fast Healthcare Interoperability Resources standard, its mechanisms, and its role in modern health IT ecosystems.
Fast Healthcare Interoperability Resources (FHIR) is a modern, RESTful API standard developed by HL7 that structures healthcare data into discrete, web-friendly "resources" to enable seamless, developer-friendly interoperability across electronic health records. FHIR works by defining a set of modular, granular data components—such as Patient, Observation, MedicationRequest, and Condition—that represent common clinical and administrative entities. Each resource is uniquely addressable via a URL and can be manipulated using standard HTTP verbs (GET, POST, PUT, DELETE). Data is serialized in either JSON, XML, or RDF, with JSON being the most common for web and mobile application development. This architectural approach allows developers to build applications that can query a patient's problem list or submit a lab result without needing to understand the monolithic, legacy HL7 v2 or CDA document paradigms. The standard is organized around a maturity model (FMM) and normative content, ensuring that production-grade stability exists for core resources while allowing innovation in emerging areas.
FHIR vs. HL7 v2 vs. CDA
A technical comparison of the three primary HL7 healthcare data exchange standards across architectural style, data format, and implementation complexity.
| Feature | FHIR | HL7 v2 | CDA |
|---|---|---|---|
Architectural Style | RESTful API | Event-driven messaging | Document exchange |
Data Format | JSON, XML, RDF | Pipe-and-hat delimited | XML |
Transport Protocol | HTTP/HTTPS | MLLP over TCP/IP | HTTP, SMTP, file transfer |
Granularity | Discrete resources | Segments and fields | Whole clinical documents |
Modern Web Support | |||
Human Readable | |||
State Management | Stateless | Stateful (acknowledgments) | Stateless |
Implementation Complexity | Moderate | High | High |
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Related Terms
Mastering FHIR requires understanding its supporting standards, architectural patterns, and complementary technologies that enable plug-and-play healthcare interoperability.
FHIR Resources
The fundamental building blocks of the FHIR standard, each representing a discrete, addressable clinical or administrative concept with a known identity and defined structure.
- Patient: Demographics and administrative information
- Observation: Vital signs, lab results, and assessments
- MedicationRequest: An order for a specific medication
- Condition: A clinical problem, diagnosis, or concern
- All resources share a common base set of metadata and are accessed via RESTful URLs
FHIR RESTful API
FHIR defines a simple, stateless RESTful architecture using standard HTTP verbs to perform CRUD operations on resources, making it instantly familiar to any web developer.
- GET
/Patient/123retrieves a specific patient - POST
/Observationcreates a new lab result - PUT
/MedicationRequest/456updates an existing order - DELETE removes a resource (when permitted)
- Supports search via query parameters like
?name=Smith
FHIR Extensions
A built-in customization mechanism that allows implementers to add data elements not covered by the core FHIR specification without breaking base interoperability.
- Every element can be extended with a unique canonical URL
- Extensions are always optional and must be safely ignorable by receivers
- Used to model local requirements like race, ethnicity, or proprietary risk scores
- Prevents the standard from becoming bloated while allowing for real-world variability
FHIR Profiles
A formal declaration of how FHIR resources are constrained, extended, and used for a specific context or jurisdiction, enabling semantic interoperability at scale.
- US Core: Mandates which resources and elements must be supported in the United States
- Profiles define cardinality constraints (e.g., making an optional field required)
- Bind terminology value sets to specific coded elements
- Published on a FHIR Implementation Guide for conformance testing
FHIR Bundles
A container resource that groups multiple FHIR resources together into a single transaction or document, enabling atomic operations and stateful exchanges.
- Search Bundle: Returns paginated results from a query
- Transaction Bundle: Executes multiple create/update/delete operations as a single atomic unit
- Document Bundle: Packages a clinical document like a discharge summary with all its referenced resources
- Critical for maintaining referential integrity across complex clinical workflows

About the author
Prasad Kumkar
CEO & MD, Inference Systems
Prasad Kumkar is the CEO & MD of Inference Systems and writes about AI systems architecture, LLM infrastructure, model serving, evaluation, and production deployment. Over 5+ years, he has worked across computer vision models, L5 autonomous vehicle systems, and LLM research, with a focus on taking complex AI ideas into real-world engineering systems.
His work and writing cover AI systems, large language models, AI agents, multimodal systems, autonomous systems, inference optimization, RAG, evaluation, and production AI engineering.
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