HL7 FHIR (Fast Healthcare Interoperability Resources) [Neurosurgery Wiki]

This page is read only. You can view the source, but not change it. Ask your administrator if you think this is wrong.
====== HL7 FHIR (Fast Healthcare Interoperability Resources) ======

**Definition:**  
HL7 FHIR is a healthcare data exchange standard developed by HL7. It uses modern web technologies such as RESTful APIs, JSON, and XML to enable secure and efficient communication between electronic health systems.

**Core Concepts:**  
  * **Resources**: modular components like `Patient`, `Observation`, `Medication`, `Encounter`  
  * **Interoperability**: facilitates data sharing across systems and organizations  
  * **Extensibility**: allows customization while maintaining standards compliance  
  * **Web Technologies**: supports HTTP(S), OAuth2, and formats like JSON/XML

**Advantages:**  
  - Simple to implement and integrate  
  - Supports real-time data exchange  
  - Enables mobile and cloud-based healthcare applications  
  - Ideal for integrating EHR systems, research platforms, and patient apps

**Example Resource:**  
```json
{
  "resourceType": "Patient",
  "id": "example",
  "name": [{ "family": "Doe", "given": ["John"] }],
  "gender": "male",
  "birthDate": "1990-01-01"
}
----

----
====== 🧠 How to Become an HL7 FHIR Expert for Neurosurgery ======

Step 1: Master the Fundamentals of HL7 FHIR (Week 1–2)
Goals:

Understand the FHIR architecture

Learn about core Resources like Patient, Observation, Procedure, ImagingStudy

Grasp RESTful API basics and data formats (JSON, XML)

Resources:

FHIR Overview for Clinicians

FHIR Specification Home

FHIR DevDays videos

Step 2: Hands-on Practice with FHIR Servers (Week 3–4)
Tools:

Use Postman to test RESTful queries

Practice with public FHIR servers:

HAPI FHIR R4 server

SMART Health IT Sandbox

Examples for Neurosurgery:

Create a Patient with clinical notes and imaging references

Record a Procedure like aneurysm clipping

Link an ImagingStudy (e.g., pre/post-op MRI) to a DiagnosticReport

Step 3: Clinical Modelling for Neurosurgery (Month 2)
Goals:

Learn how to create custom FHIR Profiles for neurosurgical use cases

Use SNOMED CT for procedures/diagnoses and LOINC for observations

Model clinical events like:

GCS scoring

mRS (modified Rankin Scale)

Post-op status

Example JSON:

json
Copiar
Editar
{
  "resourceType": "Observation",
  "code": {
    "coding": [{
      "system": "http://loinc.org",
      "code": "9269-2",
      "display": "Glasgow coma score"
    }]
  },
  "valueQuantity": {
    "value": 7
  },
  "subject": {
    "reference": "Patient/123"
  }
}
Step 4: Real Use Cases in Your Hospital (Month 3+)
Project Idea: Build a small neurosurgical clinical dashboard with:

Patient list

GCS scores

Surgery dates

Links to DICOM imaging

Post-op functional status

Tech stack suggestions:

Use React or Medblocks UI (FHIR-friendly components)

Connect to PACS via DICOM to FHIR bridge

Step 5: Advanced FHIR Concepts (Month 4 and beyond)
Learn FHIRPath for querying FHIR resources

Explore CQL (Clinical Quality Language) for clinical logic

Understand FHIR Subscriptions for real-time alerts

Contribute to Implementation Guides (IGs) for neurosurgical workflows