#Open Exchange

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Hi folks!
Our community is growing rapidly, and the knowledge base is incredibly vast. Whether you're a newbie, confused, and unsure where to start, or a seasoned IRIS veteran who occasionally forgets a few basic rules (it's normal and happens to everyone!), you'll find this brief overview of IRIS basics and all its wonders useful.
Here I'd like to begin a series of articles dedicated to this topic.
There will be eight main topics in total:

1. InterSystems ObjectScript
2. Build with REST APIs
3. Managing Data Models
4. Explore Integrated ML
5. Interoperability & Integrations
6. Introduction to IRIS HealthShare products
7. Analytics & Business Intelligence
8. Deployment & DevOps

Each of them will consist of four parts: Courses, Community articles, Documentation, Applications

This particular part will cover InterSystems ObjectScript. For your convenience, all categories will be hidden under a spoiler.
 

Every clinic visit starts the same way: a patient sits in a waiting room holding a clipboard, answering the same questions they'll be asked again ten minutes later — while the clinician walks in cold, with no idea whether the next case is a sore throat or a heart attack in progress.

That gap: between what the patient knows and what the clinician sees — is what Triage Park closes. It's our entry for the InterSystems Programming Contest: AI Agents for FHIR.

Project Links

• GitHub: https://github.com/vinogrannia/fhir-patient-snapshot-agent
• Online demo: https://fhir-patient-snapshot-agent.onrender.com/
• YouTube demo: https://youtu.be/Hsu10Nnujng

Overview

FHIR Patient Snapshot Agent is a small open-source application built for the InterSystems AI Agents and FHIR Programming Contest.

The project implements the suggested Smart Patient Summary Generator idea: it retrieves structured FHIR resources for a selected patient and generates a concise, role-specific patient summary.

The goal is not to diagnose or recommend treatment.

The successful construction and implementation of AI agents to address diverse use cases in the healthcare sector depend on high-quality data and APIs, effective governance, and management. The InterSystems IRIS FHIR server delivers all of this and is also fluent in Python, Vectors, and Interoperability. Combined with a strong LLM, patients, physicians, caregivers, and managers gain access to state-of-the-art technology for personal and public health.

Most "AI agent + FHIR" projects end up with the same shape: a FHIR server over here, a vector database over there, and a Python service in the middle whose job is to call an embedding API, marshal float arrays back and forth, and keep two datastores in sync. Three moving parts, two network hops, and an embedding client you now own forever.

Triage Park: our entry for the InterSystems Programming Contest: AI Agents for FHIR, doesn't have any of that. The agent never computes an embedding. It never imports an OpenAI embeddings client. There is no vector database.

1. Introduction

Epidemiological surveillance is one of the foundational pillars of public health. Régis Júnior et al. (2026) define it as a continuous system of data collection, analysis, interpretation and dissemination of health events — a function whose effectiveness depends critically on the quality of information systems, data analysis capacity, and coordination between different levels of care.

Hospital readmissions cost the US healthcare system $17 billion annually. A significant portion of those readmissions are preventable — but only if the right information reaches the right clinician at the right moment: at discharge.

That's the problem I set out to solve with Smart Discharge Navigator, my entry for the InterSystems Programming Contest: AI Agents for FHIR 2026.

When I started building Smart Discharge Navigator, I faced a common challenge: FHIR data is stored as JSON bundles, but the analysis I needed required joining multiple resources together, the kind of thing SQL was built for.

InterSystems FHIR SQL Builder solved this completely. Instead of parsing JSON bundles in application code, I was able to write plain SQL directly against FHIR resource projections inside IRIS for Health. This article shows exactly how I used it to build the population-level readmission risk scoring engine at the heart of the application.

An AI agent reads the FHIR patient record before the consultation, asks the right questions based on what it already knows, detects critical red flags, and writes its findings back — so the physician arrives prepared.

This project was inspired in the suggested task #10 (Conversational FHIR Triage Assistant) for the InterSystems Programming Contest: AI Agents for FHIR

Healthcare Pain Points Addressed

Before a patient walks into a consultation room, a critical failure has already occurred: nobody read their medical history. The physician has 15 minutes.

If one of your packages on OEX receives a review, you get notified by OEX only of YOUR own package.   
The rating reflects the experience of the reviewer with the status found at the time of review.   
It is kind of a snapshot and might have changed meanwhile.   
Reviews by other members of the community are marked by * in the last column.

Sorry for the weird question, but mumps skills are very rusty.

Am trying to create globals dynamically, but with using names from an array. For example: 

S Names="A,B,Y,Z"
S A=$L(Names,"$")
F I=1:1:A D
//Create globals based on names from database
//^A,  ^B,  ^Y, ^Z etc..  

If one of your packages on OEX receives a review, you get notified by OEX only of YOUR own package.   
The rating reflects the experience of the reviewer with the status found at the time of review.   
It is kind of a snapshot and might have changed meanwhile.   
Reviews by other members of the community are marked by * in the last column.
 

Hey Community,

We’re launching a new initiative in which ideas from the Ideas Portal become real applications on Open Exchange, and their authors are rewarded through Global Masters:

💡 Community Bounty Program “Idea to Application” ⚙️

Hi, every one. Again, it's me!!😀😀

Recently I was trying to organize some learning materials for InterSystems IRIS😆, and realized that the resources are actually quite scattered.🤐

So I put together a list here—grouped by categories—for anyone who:

• is new to InterSystems
• or wants to go deeper into specific areas

Also adding some of my own experience on what worked (and what didn’t, may be only not work for me🤫🤐).

1. For starters

If you don’t know where to begin, start here:

• https://developer.intersystems.com/
• https://developer.intersystems.com/resources/
• https://developer.intersystems.com/intersystems-iris-getting-started/

Motivation

Why do we need this?

1. Lack of Compiled Context: AI tools only see source code; they don't know what the final compiled routine looks like.

2. Macro Hallucination: Because AI doesn't see our #include files or system macros, it often makes them up, wasting time during debugging.

3. The Documentation Gap: Deep logic optimization often requires understanding internal macros that aren't fully covered in public documentation.

4. Manual Overhead: Currently, the only way to fix this is to manually use the IRIS VS Code extension to find the "truth" in the routine.

Is your source control treating your InterSystems IRIS environment like a simple collection of files? Most source control tools lack the native intelligence to handle InterSystems IRIS, which is why your code is treated as such. 

Deltanji is different. It understands how code and other artifacts are stored within IRIS and can manage them directly. This eliminates the friction that other tools introduce to the process. 

Join us for an InterSystems-hosted webinar to see how Deltanji provides an enterprise-grade source control solution that is tightly integrated with your IRIS environment.

Welcome to the monthly recap of updates and releases to VS Code and InterSystems-related extensions relevant to IRIS developers. 

If you're migrating from InterSystems Studio to VS Code, or want to deepen your knowledge check out the VS Code training courses from George James Software: georgejames.com/vscode-training.

VS Code version 1.110
Kitty graphics protocol in the Terminal - The integrated terminal now supports the Kitty graphics protocol, allowing for high-fidelity image rendering directly in the terminal pane.

If one of your packages on OEX receives a review, you get notified by OEX only of YOUR own package.   
The rating reflects the experience of the reviewer with the status found at the time of review.   
It is kind of a snapshot and might have changed meanwhile.   
Reviews by other members of the community are marked by * in the last column.
 

iris-budget

I created iris-budget app for the InterSystems Full Stack Contest in 2026. By full stack, we mean a frontend web or mobile application that inserts, updates, or deletes data in InterSystems IRIS via REST API, Native API, ODBC/JDBC, or Embedded Python.

My app uses multiple REST APIs to add a new category or retrieve a list of categories of expenses and income.

First web application /csp/coffee

I inherited /csp/coffee from module.xml in iris-fullstack-template.

Second web application /csp/budget

For this project, I created a swagger file called "budget.json.