#Interoperability

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In healthcare, interoperability is the ability of different information technology systems and software applications to communicate, exchange data, and use the information that has been exchanged.

The Interoperability user interface project has continued from 2025.1 and has incorporated many of the items that you – our customers and partners – have suggested and observed. We are continuing to invest in feedback and updating this important user experience. In the latest relea

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Hello Community,

Great news for developers who have just started working with InterSystems IRIS! We have hands‑on interactive tutorials available via the Instruqt platform! These are perfect for getting up to speed quickly, playing in real environments, and building confidence with IRIS‑based development.

Here is the list of available tutorials:

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The 2025.3 release of InterSystems IRIS® data platform, InterSystems IRIS® for Health, and HealthShare® Health Connect is now Generally Available (GA). This is a Continuous Delivery (CD) release.

Release Highlights:

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Overview

Fast Healthcare Interoperability Resources (FHIR) is a standardized framework developed by HL7 International to facilitate the exchange of healthcare data in a flexible, developer-friendly, and modern way. It leverages contemporary web technologies to ensure seamless integration and communication across healthcare systems.

Key FHIR Technologies

  • RESTful APIs for resource interaction
  • JSON and XML for data representation
  • OAuth2 for secure authorization and authentication

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Hi Community,

In the first part of this series, we examined the fundamentals of Interoperability on Python (IoP), specifically how it enables us to construct such interoperability elements as business services, processes, and operations using pure Python.

Now, we are ready to take things a step further. Real-world integration scenarios extend beyond simple message handoffs.They involve scheduled polling, custom message structures, decision logic, filtering, and configuration handling.In this article, we will delve into these more advanced IoP capabilities and demonstrate how to create and run a more complex interoperability flow using only Python.

To make it practical, we will build a comprehensive example: The Reddit Post Analyzer Production. The concept is straightforward: continuously retrieving the latest submissions from a chosen subreddit, filtering them based on popularity, adding extra tags to them, and sending them off for storage or further analysis.

The ultimate goal here is a reliable, self-running data ingestion pipeline. All major parts (the Business Service, Business Process, and Business Operation) are implemented in Python, showcasing how to use IoP as a Python-first integration methodology.

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Modern data architectures utilize real-time data capture, transformation, movement, and loading solutions to build data lakes, analytical warehouses, and big data repositories. It enables the analysis of data from various sources without impacting the operations that use them. To achieve this, establishing a continuous, scalable, elastic, and robust data flow is essential. The most prevalent method for that is through the CDC (Change Data Capture) technique. CDC monitors for small data set production, automatically captures this data, and delivers it to one or more recipients, including analytical data repositories. The major benefit is the elimination of the D+1 delay in analysis, as data is detected at the source as soon as it is produced, and later is replicated to the destination.

This article will demonstrate the two most common data sources for CDC scenarios, both as a source and a destination. For the data source (origin), we will explore the CDC in SQL databases and CSV files. For the data destination, we will use a columnar database (a typical high-performance analytical database scenario) and a Kafka topic (a standard approach for streaming data to the cloud and/or to multiple real-time data consumers).

Overview

This article will provide a sample for the following interoperability scenario:

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Using embedded Python while building your InterSystems-based solution can add very powerful and deep capabilities to your toolbox.

I'd like to share one sample use-case I encountered - enabling a CDC (Change Data Capture) for a mongoDB Collection - capturing those changes, digesting them through an Interoperability flow, and eventually updating an EMR via a REST API.

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Hey Community,

Enjoy the new video on InterSystems Developers YouTube:

⏯ Using SerenityGPT to Build Out an Application GenAI Middleware at InterSystems @ Ready 2025

https://www.youtube.com/embed/ZXULSWMmOD0
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When I started my journey with InterSystems IRIS, especially in Interoperability, one of the initial and common questions I had was: how can I run something on an interval or schedule? In this topic, I want to share two simple classes that address this issue. I'm surprised that some similar classes are not located somewhere in EnsLib. Or maybe I didn't search well? Anyway, this topic is not meant to be complex work, just a couple of snippets for beginners.

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InterSystems Official
· Mar 27 4m read
2025.1 Modernizing Interoperability User Experience

The Interoperability user interface now includes modernized user experiences for the DTL Editor and Production Configuration applications that are available for opt-in in all interoperability products. You can switch between the modernized and standard views. All other Interoperability screens remain in the Standard user interface. Please note that changes are limited to these two applications and we identify below the functionality that is currently available.

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When we create a FHIR repository in IRIS, we have an endpoint to access information, create new resources, etc. But there are some resources in FHIR that probably we wont have in our repository, for example, Binary resource (this resource returns a document, like PDF for example).

I have created an example that when a Binary resource is requested, FHIR endpoint returns a response, like it exists in the repository.

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High-Performance Message Searching in Health Connect

The Problem

Have you ever tried to do a search in Message Viewer on a busy interface and had the query time out? This can become quite a problem as the amount of data increases. For context, the instance of Health Connect I am working with does roughly 155 million Message Headers per day with 21 day message retention. To try and help with search performance, we extended the built-in SearchTable with commonly used fields in hopes that indexing these fields would result in faster query times. Despite this, we still couldn't get some of these queries to finish at all.

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Over time, while I was working with Interoperability on the IRIS Data Platform, I developed rules for organizing a project code into packages and classes. That is what is called a Naming Convention, usually. In this topic, I want to organize and share these rules. I hope it can be helpful for somebody.

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Hey Community!

We're happy to share a new video from our InterSystems Developers YouTube:

⏯ Source Control Interoperability Productions in a Decomposed Format @ Ready 2025

https://www.youtube.com/embed/7SF9kntjQmM
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What is TLS?

TLS, the successor to SSL, stands for Transport Layer Security and provides security (i.e. encryption and authentication) over a TCP/IP connection. If you have ever noticed the "s" on "https" URLs, you have recognized an HTTP connection "secured" by SSL/TLS. In the past, only login/authorization pages on the web would use TLS, but in today's hostile internet environment, best practice indicates that we should secure all connections with TLS.

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Hi all,

Let's do some more work about the testing data generation and export the result by REST API.😁

Here, I would like to reuse the datagen.restservice class which built in the pervious article Writing a REST api service for exporting the generated patient data in .csv

This time, we are planning to generate a FHIR bundle include multiple resources for testing the FHIR repository.

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Introduction

As AI-driven automation becomes an essential part of modern information systems, integrating AI capabilities into existing platforms should be seamless and efficient. The IRIS Agent project showcases how generative AI can work effortlessly with InterSystems IRIS, leveraging its powerful interoperability framework—without the need to learn Python or build separate AI workflows from scratch.

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I am looking for a way to capture Data Quality issues with the Source data that is populating HealthShare Provider Directory. 1 way is to use Managed Alerts, but since it could be multiple Providers and different messages it seems silly to alert on every message that has the error. Instead, I was thinking of using the Workflow Engine so it could populate a Worklist for someone to review and work.

Looking over the Demo.Workflow Engine example, I am not comprehending on how to send a task to the Workflow manager to populate the worklist from a DTL.

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Hi community,

I have a service that uses EnsLib.RecordMap.Service.FTPService to capture files in an FTP directory.

Instead of uploading them all at once, I would need to do so one at a time.

I have a class that extends this class because it preprocesses, saves everything in the RecordMap class, and then processes all the records at once.

When I invoke the BP, it does so through the method set tStatus = ..SendRequest(message, 1).

I've set the SynchronousSend flag to 1, but it continues processing all the files at once.

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To manage the accumulation of production data, InterSystems IRIS enables users to manage the database size by periodically purging the data. This purge can apply to messages, logs, business processes, and managed alerts.

Please check the documentation for more details on the settings of the purge task:
https://docs.intersystems.com/irislatest/csp/docbook/DocBook.UI.Page.cls?KEY=EGMG_purge#EGMG_purge_settings

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Hi,

It's me again😁, recently I am working on generating some fake patient data for testing purpose with the help of Chat-GPT by using Python. And, at the same time I would like to share my learning curve.😑

1st of all for building a custom REST api service is easy by extending the %CSP.REST

Creating a REST Service Manually

Let's Start !😂

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I know the next ones:

1. Place all different settings in environment variables. You have a different .env file for each environment, and you must add some code to Production for reading and setting these values. It's good for deploying into containers, but challenging for management when we have a large production. I mean, we have many settings that can vary depending on the environment: active flag, pool size, timeouts, and so on. Not only endpoints.

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Hey Community,

The InterSystems team put on our monthly Developer Meetup with a triumphant return to CIC's Venture Café, the crowd including both new and familiar faces. Despite the shakeup in both location and topic, we had a full house of folks ready to listen, learn, and have discussions about health tech innovation!

https://www.youtube.com/embed/-ER8dW6ZtQw
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For historic reasons we've got a mix of ADT feeds coming out of our PAS (TrakCare) to a wide range of downstream systems. In particular, there are some that are direct from TrakCare to the downstream systems, and many more that pass through Ensemble as our integration engine.

This is complicating management of the integrations, and so we'd like everything to go through the integration engine. In other words move from the flow in the top of the diagram to the flow in the bottom of the diagram:

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Hey Community!

We're happy to share a new video from our InterSystems Developers YouTube:

⏯ Python Interoperability Productions @ Ready 2025

https://www.youtube.com/embed/TJ5zf3FsqjA
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I am truly excited to continue my "InterSystems for Dummies" series of articles, and today, we want to tell you everything about one of the most powerful features we have for interoperability.

Hey, even if you have already had a go, we plan to take a really close look at how to get the most out of them and make our production even better.

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