This certification is intended for InterSystems EHR application specialists who use Tier 2 CCRs to manage and deploy configuration changes across environments. The content covers CCR fundamentals through Tier 2–specific topics.
Headache-free stored objects: a simple example of working with InterSystems Caché objects in ObjectScript and Python
Neuschwanstein Castle
Tabular data storages based on what is formally known as the relational data model will be celebrating their 50th anniversary in June 2020. Here is an official document – that very famous article. Many thanks for it to Doctor Edgar Frank Codd. By the way, the relational data model is on the list of the most important global innovations of the past 100 years published by Forbes.
On the other hand, oddly enough, Codd viewed relational databases and SQL as a distorted implementation of his theory. For general guidance, he created 12 rules that any relational database management system must comply with (there are actually 13 rules). Honestly speaking, there is zero DBMS's on the market that observes at least Rule 0. Therefore, no one can call their DBMS 100% relational :) If you know any exceptions, please let me know.
UPDATE: since version 0.0.4 of the extension was published on 2025-11-23 it is now possible to use gj :: configExplorer directly in VS Code on Windows.
In my previous article introducing gj :: configExplorer I flagged up how an apparent bug in the Windows elements of the Native API for Node.js means it's not currently available to run in VS Code on a Windows desktop. In a comment on that article I offered a workaround, but this requires a Docker-equipped Linux host you can SSH to.
If you don't have a suitable target it's now possible to leverage your local Windows Docker Desktop.
While working with external languages for IRIS (such as Python and Node.js), one of the first things you must accomplish is making a connection to an IRIS instance.
import iris
# Open a connection to the server
args = {
'hostname':'127.0.0.1',
'port': 1972,
'namespace':'USER',
'username':'username',
'password':'password'
}
conn = iris.connect(**args)
# Create an iris object
irispy = iris.createIRIS(conn)
# Create a global array in the USER namespace on the server
irispy.set("myGlobal", "hello world!")
In a previous article, I presented the IRIStool module, which seamlessly integrates the pandas Python library with the IRIS database. Now, I'm explaining how we can use IRIStool to leverage InterSystems IRIS as a foundation for intelligent, semantic search over healthcare data in FHIR format.
This article covers what I did to create the database for another of my projects, the FHIR Data Explorer. Both projects are candidates in the current InterSystems contest, so please vote for them if you find them useful.
Currently, my Caché code triggers an email using Basic Authentication. Now Microsoft is going to stop Basic SMTP Authentication. In this case, what is the best approach to trigger an email alert from the database? It seems OAuth 2.0 is the best approach. Do anybody have any sample using Azure Entra ID?
This program turns ideas from the Ideas Portal into real applications published on Open Exchange while rewarding developers with points, badges, visibility, and recognition across the ecosystem 🚀
We have another great initiative for you to sink your teeth into! Following last year's resounding success, we're hosting a new edition of the Demo Games. But with a twist: our North American Sales Engineers have submitted their best demo videos, but this time, you're the ones to take part and win a prize.
Please welcome the North American Demo Showcase! 🎉
I’m exploring deployment options for InterSystems IRIS in cloud environments such as AWS or Azure.
What deployment architectures, scaling strategies, or infrastructure best practices are commonly recommended by the community? I’d also appreciate guidance regarding high availability, backups, and monitoring in cloud-based deployments.
What logging and auditing strategies are commonly recommended for InterSystems IRIS environments?
I’m interested in learning about best practices for tracking user activity, troubleshooting issues, monitoring integrations, and maintaining compliance in enterprise or healthcare systems.
Are there built-in tools or external integrations that work especially well for this purpose?
The competition brought together outstanding publications, each showcasing expertise and innovation. With so many high-quality submissions, selecting the best was a true challenge for the judges.
Let's meet the winners and look at their articles:
I’m looking for recommendations to improve interoperability performance in InterSystems IRIS, especially when handling large volumes of HL7 or healthcare-related messages.
What are the best practices for optimizing productions, business services, operations, and message processing performance? I’d also like to know if there are recommended monitoring tools or settings commonly used in production environments.
I’m currently working with REST APIs in InterSystems IRIS and would like to better understand the recommended security practices for production environments.
I’m especially interested in:
Authentication and authorization methods
Token management strategies
Role-based access control
API gateway recommendations
Encryption and secure communication practices
Monitoring and logging for API activity
I would also appreciate learning about common mistakes to avoid when deploying APIs publicly or integrating with external systems.
What approaches or tools have worked best in your environments?
I'm running a shell script and the q isn't exiting the screen. this is RHEL 7.9 I used to issue in VMS just fine but we have found that Linux scripts behave different. after these run I search the file for the status and depending on what it comes back with it will send an email.
I’m looking for practical recommendations to monitor InterSystems IRIS performance in a production environment. What are the most useful built-in tools, metrics, or best practices to track system health, database performance, and possible bottlenecks?
I would also like to know if there are recommended dashboards, logs, or monitoring integrations commonly used by the community.
What's the most straight-forward way to install this on an offline server? I'm trying to set this up on an Azure DevOps server to support our CI/CD pipelines. I've tried using zpm installing the tgz from the local filesystem. I note zpm seems to need a repo configured to install but I can't work out how to setup a bare-bones Filesystem repo (please point me to some documentation on this). I have no idea what I'm doing...
Common Table Expressions (CTEs) provide a structured framework for defining reusable intermediate result sets within SQL statements. InterSystems IRIS implements CTEs via the WITH clause, enabling clearer query composition and modular analytical processing while remaining fully integrated with the IRIS cost-based optimizer.
This article explores the semantics of CTEs in InterSystems IRIS, explains their interaction with query optimization, discusses appropriate deployment scenarios, and presents executable examples illustrating practical patterns for production environments.
ExplantIQ is an intelligent data application that tackles one of healthcare's most overlooked financial and regulatory risks: the management of explanted medical device warranty credits. When an implanted device is removed from a patient (due to failure or recall) hospitals are legally required to pursue manufacturer credits, refund payers if the credit exceeds 50% of the device's cost, and report to CMS. Miss that obligation and you're facing a reverse False Claims Act violation. Industry data shows hospitals miss 81% of eligible credits.
ExplantIQ, built entirely on InterSystems IRIS for Health and DeepSee, solves this by unifying clinical, supply chain, billing, and FDA recall data into a single real-time compliance dashboard, complete with KPI scorecards, trend analytics, and a Text-to-SQL AI Assistant that lets compliance officers query live operational data in plain English. No separate BI tool. No additional architecture. All questions can be answered without leaving your browser tab.
Health Galaxy creates an AI access point on top of any FHIR server, bringing healthcare into the AI future that has become a reality for many other industries.
AI access: Health Galaxy gives AI agents a single gateway into any healthcare system, so they can pull patient data, schedule appointments, and check insurance automatically instead of a human doing it manually.
Ease of use: You point it at an existing FHIR endpoint, click a button, and it generates an MCP endpoint automatically from the capability statement.
FHIR: Since we are using FHIR, we can leverage both the storage and exchange capabilities of InterSystems IRIS.
🗣 Presenter: @Zelong Wang, Sales Engineer at InterSystems
This demo highlights how HL7 validation logs can be transformed into scalable, actionable data quality insights using a lightweight application built on top of Health Connect.
Batch ingestion and parsing of HL7 validation error logs into structured data
Aggregation of errors by segment, field, and type to reveal systemic issues
Interactive dashboard (Streamlit) for filtering, exploration, and root cause analysis
Rapid identification of top error patterns across entire data feeds
Natural language chatbot for intent-driven data investigation and querying
PDF report generation for sharing clear, evidence-based feedback during data source onboarding
Special thanks to @Henry Wojnicki for his contributions to designing and refining the application workflow.
🗣 Presenter: @Lynn Wu, Sales Engineer at InterSystems
We are using IRIS for Health to develop an agentic AI chatbot workflow that can interact with a patient using voice commands, reach out to an EHR or other system for context, and provide recommendations back.
Presenters: 🗣 @Vic Sun, Sales Engineer at InterSystems 🗣 @Brad Nissenbaum, Sales Engineer at InterSystems 🗣 Danielle Micciantuono, Clinical Solutions Specialist at InterSystems
In this demo, you will see how Gemini works directly with FHIR data, and how it leverages the harmonized dataset provided by InterSystems Unified Care Record. It also showcases multiple AI assistants helping multiple groups of users, e.g. clinicians, patients.
🗣 Presenter: @Simon Sha, Sales Architect at InterSystems
