#FHIR

Hi Community!

We’re excited to announce the launch of a new, hands-on training program:

 🧑‍💻 Developing FHIR Applications Using Python 🧑‍💻

This cohort-based course takes developers from FHIR fundamentals to advanced, real-world healthcare interoperability solutions, with deeper, more practical coverage than typical industry offerings and a strong focus on production-ready skills using InterSystems technology.

You’ve seen how tools like Lovable are shaking up web development. People are spinning up entire apps just by talking to an AI, almost like pair‑programming on steroids.

Now imagine bringing that same “vibe coding” experience into healthcare. know, it sounds crazy. Healthcare is complex, full of regulations, and usually gives us a headache just thinking about the interoperability rules.

That’s exactly the space where withLove lives: an AI‑Native, Low‑Code platform built entirely on InterSystems IRIS for Health.

Hi, Community!

👩‍⚕️If you need to access clinical data at scale, the InterSystems Bulk FHIR Coordinator can help!

Using the InterSystems Bulk FHIR Coordinator to Extract Clinical Data

Hey Developers,

Watch this video to learn about automating the provisioning and management of FHIR services:

     ⏯ Automating Provisioning and Management of FHIR Services @ Ready 2025

Hi,
I need to create a bundle of synthetic data in order to populate FHIR servers (not mine).

Can I use a predefined ids, or is it possible the one of the servers will not allow using my IDs and replace them with it's automatic numbering?

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:

✅ 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.