#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.

The real problem

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.

Overview

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:

• ED Doctor
• Care Manager
• Patient
• Family Caregiver

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.