#Interoperability

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In healthcare, interoperability is the ability of different information technology systems and software applications to communicate, exchange data, and use the information that has been exchanged.

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Discussion André Sheydin · Feb 28

Hello everyone,

I am André from MedVertical. We are exploring InterSystems-native ways to operationalize continuous FHIR conformance: repeatable regression runs, baseline/delta comparisons, and evidence-style reporting to detect drift after releases and IG changes.

In many FHIR implementations, validation is done “point-in-time” in pre-prod, but conformance degrades in production due to IG/profile updates, terminology changes, mapping evolution, upstream releases, and configuration drift.

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Question Yone Moreno Jiménez · Feb 24

Hello, how are you?

Using Healthshare for Interoperability, we often see a wide variety of encoding issues. Some happen when transforming XML to HL7. Some happen the other ay around transforming HL7 to XML.

Is there a valid way to understand which encoding needs to be used?

I ask, because we use SOAP or REST or TCP HL7 services.

And we deliver messages with TCP HL7, SOAP, HTTP Operations.

And we often face this issue where special characters like ñ or á, are not encoded correctly.

Thanks for your replies.

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Discussion Aya Heshmat · Feb 27

Hello!

I am requesting feedback on the usage and experience of the Schema Viewer feature available in Interoperability-enabled products (IRIS, IRIS for Health, Health Connect). This feature is accessible via Interoperability > Interoperate

Some questions to jog your discussion/comments below:

  1. What's one enhancement that would drastically change your experience or enable faster schema configurations?
  2. If you are not a user of this feature (but need to create custom schemas/view your schemas), why do you not use the schema viewer?
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Discussion Jorge Jaramillo Herrera · Feb 23

Hello everyone,
I’m looking to implement Continuous Training (CT) as part of an MLOps strategy for some data science projects in IRIS. I want to automate the full cycle:

- Monitoring model performance & accuracy degradation.
- Retraining models automatically.
- Validating and updating production models.

I’ve looked into IntegratedML, but it seems more focused on the SQL interface for training (AutoML). Even with the new Custom Models (beta), which allows for more flexibility with Python, it doesn't seem to provide the "Continuous" orchestration out of the box.

I’d like to know:

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Article Sanjib Pandey · Feb 20 5m read

Project Overview:

 

The Clinical Staff Master Data Management (CSMDM) system is a full-stack healthcare integration application built on InterSystems IRIS for Health. It centralizes and standardizes clinical staff metadata into a single authoritative repository, exposed through RESTful CRUD APIs and reusable backend methods.

The platform eliminates fragmented lookup tables and hardcoded mappings that commonly cause errors in HL7 and FHIR integration workflows, ensuring data consistency and interface reliability.

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Article Geet Kalra · Feb 18 6m read

Intersystems IRIS Productions provide a powerful framework for connecting disparate systems across various protocols and message formats in a reliable, observable, and scalable manner. intersystems_pyprod, short for InterSystems Python Productions, is a Python library that enables developers to build these interoperability components entirely in Python. Designed for flexibility, it supports a hybrid approach: you can seamlessly mix new Python-based components with existing ObjectScript-based ones, leveraging your established IRIS infrastructure.

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Article Henry Pereira · Feb 16 15m read

cover

Welcome to the finale of our journey in building MAIS.

  • In Part 1, we constructed the agnostic "Brain" using LiteLLM and IRIS.
  • In Part 2, we designed the "Persona", mastering Dynamic Prompt Engineering and the ReAct theory.

Now, the stage is set. Our agents are ready, defined, and eager to work. However, they remain frozen in time. They require a mechanism to drive the conversation, execute their requested tools, and pass the baton to one another.

Today, we will assemble the Nervous System.

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Question Jordan Everett · Feb 11

Hey everyone,

I'm just seeking some guidance and confirmation on what I'm doing for my production health monitoring.

We utilize Grafana to have reporting/monitoring dashboards and I have made a REST API to query the health of our productions. I believe I have everything figured out except for one thing that I'm uncertain about and that is the Production Item Color indicators:

Is there an easy way of being able to figure out the status of an item with the legend above? Ideally, I'd like to have this data in my JSON response.

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Article Alberto Fuentes · Feb 13 10m read

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:

image

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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