HL7 FHIR Integration for Clinical AI: A Practitioner's Guide Using Mirth Connect and Epic
A complete practitioner curriculum covering HL7 v2 feeds, FHIR R4 APIs, Mirth Connect channel engineering, Epic SMART on FHIR, and production clinical AI inference — from raw healthcare data to deployed systems.
Course Overview
From raw HL7 v2 feeds to FHIR R4 APIs, Mirth Connect channel engineering, Epic SMART on FHIR, and production clinical AI inference — a complete practitioner curriculum for healthcare data integration.
What You’ll Learn
Track A — Healthcare Data Fundamentals (Modules 1–3)
| Module | Title | Focus |
|---|---|---|
| M1 | HL7 v2 Essentials | Message structure, segments, encoding rules, real hospital data |
| M2 | FHIR R4 Fundamentals | Resources, RESTful APIs, JSON/XML, clinical data models |
| M3 | Mirth Connect Basics | Channel creation, message flow, transformation scripts |
Track B — Production Integration (Modules 4–6)
| Module | Title | Focus |
|---|---|---|
| M4 | Epic EHR & SMART on FHIR | Epic API authentication, SMART launch, production security |
| M5 | Clinical Data Validation | Data quality checks, compliance (HIPAA), error handling |
| M6 | Building Real-World Pipelines | Mirth routing, error recovery, monitoring |
Track C — AI Integration & Deployment (Modules 7–8)
| Module | Title | Focus |
|---|---|---|
| M7 | Clinical AI Model Inference | Real-time prediction, latency optimization, safety checks |
| M8 | Production Monitoring & MLOps | Alert systems, drift detection, audit logging |
Tech Stack
HL7 v2 · FHIR R4 · Mirth Connect · Epic EHR · SMART on FHIR · Python · Docker · Kubernetes · MLflow
Target Audience
Healthcare software engineers, clinical informaticists, and ML engineers integrating AI into EHR systems.
Status: In development — launching May 2026