#Python

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:

• Source context vector search
• Embedded Python artifacts for IRIS-compatible review

The goal was to make the project more useful as a clinical summarisation prototype while keeping the design small enough to understand and reproduce.

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.