Python is an interpreted high-level programming language for general-purpose programming. Created by Guido van Rossum and first released in 1991, Python has a design philosophy that emphasizes code readability, notably using significant whitespace
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.
In my first article, I described the baseline version of the FHIR Patient Snapshot Agent: a Streamlit and Python application that retrieves FHIR resources from InterSystems IRIS for Health and uses an LLM to generate a concise patient summary.
This follow-up article explains how I extended the project with two additional InterSystems-focused features:
The goal was to make the project more useful as a clinical summarisation prototype while keeping the design small enough to understand and reproduce.
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.
At 4:57 PM on a Friday, a routine laboratory order failed.
The patient's sample was already in transit. The external reference laboratory rejected the request — it could not uniquely identify the patient. The insurance operator rejected authorization for a different reason. Neither system spoke the same language, neither exposed compatible error messages, and the only integration layer in the middle simply forwarded requests.
A laboratory technician spent the next 25 minutes navigating portals, copying identifiers, and manually reconciling data between systems.
Smart Patient Summary Generator is an AI-powered FHIR demo application built for InterSystems IRIS for Health. It reads FHIR R4 patient data, extracts key clinical information, and generates concise summaries for four different roles:
By consolidating fragmented FHIR records into role-specific summaries, the application helps clinicians quickly understand a patient’s current condition, recent changes, and follow-up risks. For patients and family caregivers, it presents the same clinical context in a more accessible format.
Hi!
I'm trying to compiling a class with an Embedded Python and got this error:
Compilation started on 06/12/2026 11:44:17 with qualifiers 'cuk'
Compiling class User.VectorSearch
ERROR #7802: Worker job/s '749:33' unexpectedly shut down in group '#Default:(446070926892):0'.
ERROR #7812: Work queue unexpectedly removed, shutting down.
ERROR #5002: ObjectScript error: <THROW>WaitForComplete+215^%SYS.WorkQueueMgr *%Exception.StatusException ERROR #7802: Worker job/s '749:33' unexpectedly shut down in group '#Default:(446070926892):0'.
ERROR #7812: Work queue unexpectedly removed, shutting down.
Detected 3 errors during compilation in 1.020s.
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.
Hi everyone,
I created a short demo and reference repository showing how to configure Auth0 as an OAuth provider for an InterSystems IRIS FHIR server, and how to call protected FHIR resources from a Python Flask application.
The links below include a video walkthrough and a github repo with the sample application used in the video
Links
Video walkthrough:
GitHub repository: https://github.com/MarshyKid/iris-fhir-oauth-demo