Contestant

10:47 AM — Jose Garcia's creatinine test results arrive at the hospital FHIR server.
2.1 mg/dL — a 35% increase from last month.

What happens next?

  • Most systems: ❌ The result sits in a queue until a clinician reviews it manually — hours or days later.
  • This system: 👍 An AI agent evaluates the trend, consults clinical guidelines, and generates evidence-based recommendations — in seconds, automatically.

No chatbot. No manual prompts. No black-box reasoning.

This is event-driven clinical decision support with full explainability:

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Triggered automatically by FHIR events
Multi-agent reasoning (context, guidelines, recommendations)
Complete audit trail in SQL (every decision, every evidence source)
FHIR-native outputs (DiagnosticReport published to server)

Built with:
- InterSystems IRIS for Health — Orchestration, FHIR, persistence, vector search
- CrewAI — Multi-agent framework for structured reasoning

You'll learn: 🖋️ How to orchestrate agentic AI workflows within production-grade interoperability systems — and why explainability matters more than accuracy alone.

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Hey Developers,

Enjoy the new video on InterSystems Developers YouTube

HealthShare Vision & Roadmap - Fueling Faster AI Adoption Through Trusted Health Data @ READY 2025

https://www.youtube.com/embed/UdnpN7m-kRs
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Contestant

Introduction

Earlier this year, I set about creating kit to introduce young techy folk at a Health Tech hackathon to using InterSystems IRIS for health, particularly focusing on using FHIR and vector search.

I wanted to publish this to the developer community because the tutorials included in the kit make a great introduction to using FHIR and to building a basic RAG system in IRIS. Its an all inclusive set of tutorials to show in detail how to:

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