Hey Community!

We're happy to share the first video in the "InterSystems Instruqt Walkthroughs" series on our InterSystems Developers YouTube:

⏯ Data Models of InterSystems IRIS - InterSystems Instruqt Walkthrough

Using the SOAP wizard many moons ago, I had setup a process to get Patient Demographics, and the current Visit Location from Epic for processing HL7 DFT Charge Messages.

Within the past week we have had two cases where the Outbound SOAP Adapter has been throwing Errors (Exceptions) where in this case 

NO-PATIENT-FOUND details: No patient found with the provided ID and ID type.

The error is not being sent back in the Response to the Business Process that sent the call. The Response comes back blank.

A vector-search knowledge base of past clinical assessments, running on InterSystems IRIS, gives the LLM a deterministic calibration signal — making its triage reasoning faster, more structured, and clinically defensible.

The Problem with Probabilistic Medicine

The LLM answered correctly. But would it answer the same way for the next patient with the same profile? Same conditions, same medications, same symptoms — would the risk score drift? Would the priority shift from "emergency" to "urgent"? Would the follow-up tasks be different?

Hi all,

I'm looking for some advice on a DTL issue.

I'm working on an HL7 DTL where I need to populate MSH-6 / Receiving Facility using a combination of literal text and values from the PD1 Patient Primary Care Provider field.

The required MSH-6 value needs to be something like:

MCNIMCNumber.PracticeID

Where:

• MCN is a literal string
• IMCNumber comes from PD1
• PracticeID comes from PD1

For the IMC number, the direct source path that works is:

source.{PIDgrpgrp().PIDgrp.PD1(3).assigningauthority.namespaceID}

If I assign this direct path straight into MSH-6, the value populates.

When installing InterSystems IRIS on Windows, you may see the following option in the installer wizard if IIS has already been installed and enabled (Enable IIS).

Note: Depending on your installation type, you may not see this exact installer screen. In that case, proceed with installation as normal, and then configure the IIS settings on the server where the Web Gateway is installed.

If you choose to configure the local IIS web server for the instance, the installer wires IIS and the InterSystems Web Gateway together for you.

Amazon SQS (Simple Queue Service) is a managed message queue service that provides a simple, durable, and scalable mechanism for exchanging messages between applications. It is particularly well suited for event-driven integration patterns and loosely coupled architectures.

Bear in mind that the AWS SQS adapter is based on InterSystems PEX Network and requires the Java External Server to be enabled.

When using Amazon SQS you can either take the role of a Consumer or a Publisher.

We are happy to present the bonuses page for the applications submitted to the InterSystems Programming Contest: AI Agents for FHIR

See the results below.

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.

Hi Community,

It's voting time! Cast your votes for the best applications in our InterSystems Programming Contest: AI Agents for FHIR:

🔥 VOTE FOR THE BEST APPS 🔥

Voting period: June 8 to June 14, 2026

How to vote? Details below.

 Hi everyone,

I've been exploring the growing use of AI agents and LLM-powered workflows with InterSystems IRIS and InterSystems IRIS for Health.

I'm curious to learn how others in the community are approaching this.

• Are you currently using AI agents in production or testing environments?
• What use cases have delivered the most value so far?
• Have you integrated IRIS with models such as GPT, Claude, or other LLMs?
• What challenges did you encounter during implementation?

I'm especially interested in hearing about healthcare, automation, data integration, and decision-support scenarios.

InterSystems Programming Contest: AI Agents for FHIR at https://openexchange.intersystems.com/contest/46 . 

Code: https://github.com/eungi-hong/central-park

Demo: https://triagepark.78-47-167-98.sslip.io/ 

The first ten minutes of a visit are always the same: take the history, pull the record, cross-check the medications, decide how urgent it is. Triage Park does that first pass as a team of AI agents running entirely inside InterSystems IRIS for Health, and hands the clinician a cited, explainable handoff. The part most "AI triage" demos skip is the part we cared about most: safety

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.

I'm pleased to share that FHIR Agent Studio is now running as a live, hosted demo on the InterSystems Developer Cloud — no install, no setup, just open it in a browser.

FHIR Agent Studio is a developer portal for building, running, and inspecting AI agents for FHIR workflows on a single InterSystems IRIS for Health backend.

Hi Community,

In this article, I will introduce my application iris-fhir-agents A multi-agent clinical AI platform powered by InterSystems IRIS for Health. Features agents for triage, specialist consultation, pharmacy safety, and FHIR server exploration — all grounded by IRIS Vector Search RAG. Includes a no-code Agent Builder that lets you design and deploy custom clinical agents without writing a single line of code.

Hi Community,

We're super excited to share with you the recording of the Developer Community session from the recent READY 2026. Join us as we explore how the Developer Ecosystem resources foster practical learning and real-world solution building on InterSystems IRIS.

🤩 Streamlining Development Workflow with InterSystems Developer Community and Ecosystem

AI is going to change healthcare, but only if clinicians can trust it and developers can build it without reinventing the plumbing every time. FHIR Agent Studio is my attempt at both: a place to build AI agents for FHIR workflows from reusable building blocks, run them on a real InterSystems IRIS for Health backend, and inspect exactly what each one did at every step.

It is my entry in the InterSystems AI Agents for FHIR contest, and it ships with twelve working agents over a synthetic FHIR repository of around 1,000 patients and 20,000 resources.

1. The End of "Pay-and-Chase": A New Era of Payment Integrity

For decades, healthcare payers have been trapped in a reactive cycle known as "pay-and-chase." Traditional payment integrity relies on retrospective audits—reviewing claims months after disbursement to claw back overpayments. This inefficiency costs the industry billions in unrecovered fraud, waste, and abuse.

ClaimAuditAI introduces a fundamental paradigm shift by moving the audit to the point of submission.

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.

Hi folks!

Suppose a new version of your amazing software solution built on IRIS needs some persistence change: some data needs to be converted, some classes get new properties or even renamed, and some data should be prepopulated for newly introduced persistent classes to keep the whole application data consistent.

What are your approaches? 

SQL-based scripts? ObjectScript, or Python? for both directions of migration, up and down? 

Do you autogenerate it with Claude/Codex? What about data-consistency tests?

COuld you please share your thoughts? or libraries?

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.

 Hello Community,

I am learning more about InterSystems IRIS administration and would like to understand the recommended approach for monitoring performance in a production environment.

What tools, metrics, or dashboards do you typically use to monitor system health, database activity, and application performance?

I am particularly interested in learning which indicators are most useful for identifying potential bottlenecks before they affect users.

Thank you for sharing your experience and recommendations.

The CCR EHR Application Specialist Exam is now available on the InterSystems exam store! 

This exam certifies that developers are able to use Tier 2 CCRs to document and progress change workflows.

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 All,

There is a steady increase in the amount of metadata that I need to build in the message flow (across BPs & DTLs) and I am interested on a good pattern to follow that allows for a mix of metadata types (e.g. json, xml list, etc) and is accessible quickly either within DTLs or BP.

One example for this would be adding various localised codesets to metadata during DTLs which would later be used to submit a FHIR translate request to a terminology server. Providing visibility in the DTL to which codesets are to be translated while batching up the translate request for performance.

Hi Developers,

We are happy to announce the new InterSystems online programming contest:

🏆 InterSystems Programming Contest: AI Agents for FHIR🏆

Duration: May 25 - June 14, 2026

Prize pool: $12,000

Virginia's got BIGDATA in IRIS and Iowa wants it

This distraction, "Meshing IrisClusters" with Cilium ClusterMesh, provides database access using the Enterprise Cache Protocol (ECP) from the Eastern Seaboard of the United States to the MidWest on Google Cloud Platform.  Ridiculously powerful setup for national/multi-national setups and though the use cases are a plenty, this particular one is a simple example on how to send ETL/ELT the unemployment office.

The rise of distributed systems and cloud-native architectures within large institutions has redefined hosting for InterSystems IRIS interoperability applications (productions). In modern environments, the standard layout involves at least two production instances operating on distinct nodes under a load-balancing configuration to handle requests.

The benefits are clear: you can now scale dynamically based on request volume, increasing the number of active productions during peak demand and going down when traffic subsides.