As said in the previous article about the iris-fhir-generative-ai experiment, the project logs all events for analysis. Here we are going to discuss two types of analysis covered by analytics embedded in the project:

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I know that people who are completely new to VS Code, Git, Docker, FHIR, and other tools can sometimes struggle with setting up the environment. So I decided to write an article that walks through the entire setup process step by step to make it easier to get started.

I’d really appreciate it if you could leave a comment at the end - let me know if the instructions were clear, if anything was missing, or if there’s anything else you'd find helpful.

The setup includes:

✅ VS Code – Code editor
✅ Git – Version control system
✅ Docker – Runs an instance of IRIS for Health Community
✅ VS Code REST Client Extension – For running FHIR API queries
✅ Python – For writing FHIR-based scripts
✅ Jupyter Notebooks – For AI and FHIR assignments

Before you begin: Ensure you have administrator privileges on your system.

In addition to reading the guide, you can also follow the steps in the videos:

For Windows

https://www.youtube.com/embed/IyvuHbxCwCY
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Article
· Jan 29, 2024 2m read
Get familiar with FHIR

🔥 Curious about the FHIR standard that everyone's talking about?

📚 Read on for a brief introduction, then try a brand-new learning path to get more in-depth knowledge!

The HL7® FHIR® standard has revolutionized the way healthcare developers take on the challenges of data interoperability. FHIR allows healthcare systems to exchange information seamlessly, and patient data can be consolidated in real time, regardless of where it's stored.

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Article
· Nov 15, 2024 2m read
HL7 -> SDA -> FHIR -> Personal Growth

I have a large tree outside my window. Here in Phoenix, Arizona, USA it's still warm and sunny so our plants are still covered in lush foliage despite so many other places in the full throws of Autumn. My desk is oriented such that I can look out at the tree throughout the day.

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Article
· Mar 10 5m read
FHIR SQL Builder: step by step

The FHIR standard establishes a powerful but flexible data model that can smoothly adapt to the complexities of operational healthcare data management. This flexibility comes at the cost of a data model with many tables and relationships, even for simple data such as the patient's record of telephone numbers, addresses, and emails. It would easily require querying 4 different tables. However, FHIR SQL Builder eliminates this problem, allowing you to create visual projections (mappings) in web wizards.

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Article
· Feb 13 4m read
Bulk FHIR Step by Step

FHIR repositories, applications and servers typically serve clinical data in small quantities, whether to return data about a patient, their medications, vaccines, allergies, among other information. However, it is common for a large amount of data in FHIR/JSON format to be requested to be used to load into Data Lakes, identifying study cohorts, population health, or transferring data from one EHR to another. To meet these business scenarios that require large extractions and loads of data, it is recommended to use the FHIR Bulk Data Access feature provided by HL7 institution.

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An extension “extends” or enhances a FHIR resource or a data element in a custom way. The extension can be added to the root of a resource, such as “Patient.ethnicity” in US Core profile, and they can be added to individual elements such as HumanName, Address or Identifier.

Did you know that you can also add an extension to a primitive data type?

Primitives usually store a single item and are the most basic element in FHIR. For example: "Keren", false, 1234, 12/08/2024 etc.

For example, the patient resources might look like this:

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Over the past couple of months, I have been working on the SMART on FHIR EHR Launch to test the capabilities of IRIS for Health using two open-source apps from CSIRO: SMART-EHR-Launcher and SMART Forms App. This journey has been incredibly interesting, and I’m truly grateful for the opportunity to work on this task and explore more of IRIS for Health’s potential.

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Hi colleagues!

Often, while developing a frontend app or any other communication vs REST API, it is worth having a Swagger UI - a test UI for the REST API that follows Open API 2.0 spec. Usually, it is quite a handful as it lets have quick manual tests vs REST API and its responses and the data inside.

Recently I've introduced the Swagger support to the InterSystems IRIS FHIR template for FHIR R4 API:

How to get it working.

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Article
· Jan 28, 2024 3m read
Fhir-HepatitisC-Predict

Processing FHIR resources with FHIR SQL BUILDER to predict the probability of developing hepatitis C disease

With the development of technology, the medical industry is also constantly advancing, and humans often pay more attention to their own health,
By learning and processing datasets through computers, diseases can be predicted.

Pre condition: Ability to use FHIR and ML
Firstly, our dataset is obtained from kaggle and transformed into FHIR resources based on patient gender, age, ALP or ALT, and imported into the FHIR resource repository

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Article
· Feb 2, 2024 2m read
Fhir-HepatitisC-Predict application

Hi Community

This document mainly enriches the content of the previous article and introduces the use of the application.

Perhaps you have already read the previous article, but I still want to say,
After completing the initialization operation (including model creation and training), the Fhir HepatitisC Predict application then predicts HepatitisC

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Hi developers!

This will be a very short article as in April 2025 with Lovable and other Prompt-to-UI tools it becomes possible to build the frontend with prompting. Even to the folks like me who is not familiar with modern UI techics at all.

Well, I know at least the words javascript, typescript and ReactJS, so in this very short article we will be building the ReactJS UI to InterSystems FHIR server with Lovable.ai.

Let's go!

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Introduction

To achieve optimized AI performance, robust explainability, adaptability, and efficiency in healthcare solutions, InterSystems IRIS serves as the core foundation for a project within the x-rAI multi-agentic framework. This article provides an in-depth look at how InterSystems IRIS empowers the development of a real-time health data analytics platform, enabling advanced analytics and actionable insights. The solution leverages the strengths of InterSystems IRIS, including dynamic SQL, native vector search capabilities, distributed caching (ECP), and FHIR interoperability. This innovative approach directly aligns with the contest themes of "Using Dynamic SQL & Embedded SQL," "GenAI, Vector Search," and "FHIR, EHR," showcasing a practical application of InterSystems IRIS in a critical healthcare context.

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Hi Community,

In this article, I will introduce my application iris-fhir-bridge

IRIS-FHIR-Bridge is a robust interoperability engine built on InterSystems IRIS for Health, designed to transform healthcare data across multiple formats into FHIR and vice versa. It leverages the InterSystems FHIR Object Model (HS.FHIRModel.R4.*) to enable smooth data standardization and exchange across modern and legacy healthcare systems.

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1Background

When I first encountered FHIR, I encountered a problem with its message format. It was difficult for me to determine whether the message I created met the format, and it was also difficult to easily create an FHIR message from scratch.

So, through fhir server of IntereSystemsfhirserver API, I created this application for quickly generating/validating FHIR messages.

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Introducing Smart Clinical Sidechick — the intelligent, no-drama partner your EHR wishes it could be. She reads FHIR data in real time, interprets lab results without ghosting, and explains clinical alerts like she actually cares. Built with GPT-4 brains and YAML sass, she’s not here to replace your main EHR—just to make it look bad. Tired of irrelevant alerts and cryptic warnings? Sidechick serves up real, explainable insights, not vague “elevated risk” vibes. And when your backend crashes, she doesn’t panic—she self-heals.

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IRIS supports CCDA and FHIR transformations out-of-the-box, yet the ability to access and view those features requires considerable setup time and product knowledge. The IRIS Interop DevTools application was designed to bridge that gap, allowing implementers to immediately jump in and view the built-in transformation capabilities of the product.

In addition to the IRIS XML, XPath, and CCDA Transformation environment, the Interop DevTools package now provides:

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Digital health solution providers face increasing pressure to integrate complex health data systems while ensuring scalability, security, and compliance with standards like HL7 FHIR. Fast Healthcare Interoperability Resources (FHIR) has revolutionized health data exchange by offering a standardized framework that allows diverse health IT systems to communicate effortlessly. But simply adhering to FHIR standards isn’t enough to overcome the intricacies of health data integration. Solution partners must leverage advanced architectural components like FHIR brokers, façades, and repositories to build scalable and efficient solutions. InterSystems offers all the essential features you need to implement FHIR for your health data, whether on-premises, in a public cloud, or as a cloud-based service managed by InterSystems.

Medical Science Hospital Lab Meeting healthcare

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After we rolled out a new cointainer based on containers.intersystems.com/intersystems/irishealth:2023.1 this week, we suddenly noticed that our FHIR Repository started responding with an Error 500. This turns out to be caused by PROTECT violations on the new HSSYSLOCALTEMP namespace and database used by this version of the IRIS for Health FHIR components.

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