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#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.

InterSystems Official
· Mar 27, 2025 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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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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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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Interoperability on Python (IoP) is a proof-of-concept project designed to showcase the power of the InterSystems IRIS Interoperability Framework when combined with a Python-first approach.IoP leverages Embedded Python (a feature of InterSystems IRIS) to enable developers to write interoperability components in Python, which can seamlessly integrate with the robust IRIS platform. This guide has been crafted for beginners and provides a comprehensive introduction to IoP, its setup, and practical steps to create your first interoperability component. By the end of this article, you will get a clear understanding of how to use IoP to build scalable, Python-based interoperability solutions.

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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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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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Article
· Feb 13, 2025 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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FHIR Server

A FHIR Server is a software application that implements the FHIR (Fast Healthcare Interoperability Resources) standard, enabling healthcare systems to store, access, exchange, and manage healthcare data in a standardized manner.

Intersystems IRIS can store and retrieve the following FHIR resources:

  • Resource Repository – IRIS Native FHIR server can effortlessly store the FHIR bundles/resources directly in the FHIR repository.
  • FHIR Facade - the FHIR facade layer is a software architecture pattern used to expose a FHIR-compliant API on top of an existing one (often non-FHIR). It also streamlines the healthcare data system, including an electronic health record (EHR), legacy database, or HL7 v2 message store, without requiring the migration of all data into a FHIR-native system.

What is FHIR?

Fast Healthcare Interoperability Resources (FHIR) is a standardized framework created 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 various healthcare systems.

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One of the challenges of creating a DICOM message is how to implement putting data in the correct place. Part of it is by inserting the data in the specific DICOM tags, while the other is to insert binary data such as a picture - In this article I will explain both.

To create a DICOM message, you can either use the EnsLib.DICOM.File class (to create a DICOM file) or the EnsLib.DICOM.Document class (to create a message that can be sent to PACS directly). In either case, the SetValueAt method will allow you to add your data to the DICOM tags.

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RabbitMQ is a message broker that allows producers (those who send a data message) and consumers (those who receive a data message) to establish asynchronous, real-time, and high-performance massive data flows. RabbitMQ supports AMQP (Advanced Message Queuing Protocol), an open standard application layer protocol.
The main reasons to employ RabbitMQ include the following:

  • You can improve the performance of the applications using an asynchronous approach.
  • It lets you decouple and reduce dependencies between services, microservices, and applications with the help of a data message mediator, meaning that there is no need for producers and consumers of exchanged data to know each other.
  • It allows the long-running processing of sent data (with the results) to be delivered after utilizing a response queue.
  • It helps you migrate from monolithic to microservices, where microservices exchange data via Rabbit in a decoupled and asynchronous way.
  • It offers reliability and resilience by making it possible for messages to be stored and forwarded. A message can be delivered multiple times until it is processed.
  • Message queueing is the key to scaling your application. As the workload increases, you will only have to add more workers to handle the queues faster.
  • It works well with data streaming applications.
  • It is beneficial for IoT applications.
  • It is a must for Bots’ communication.

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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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Article
· Sep 29, 2025 13m read
InterSystems for Dummies – Record Map

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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In 2023, according to IDC, Salesforce's market share in CRM reached 21.7%. This company owns a substantial amount of critical corporate business processes and data, so the InterSystems IRIS must have an interoperability connector to fetch data from the Salesforce data catalog. This article will show you how to get any data hosted by Salesforce and create an interoperation production to get data and send it to such targets as files and relational databases.

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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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In this section, we will explore how to use Python as the primary language in IRIS, allowing you to write your application logic in Python while still leveraging the power of IRIS.

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I am receiving the garbled text due to incorrect encoding or decoding. I tried to use the $zconvert function to convert it into the normal text but failed to do that. Can anybody suggest what I have to use to convert that into normal text?

Example: Garbled text that I am getting is "canââ¬â¢t , theyââ¬â¢re".

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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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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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We are receiving the report in text format and it has special characters like ', - like that in the text. Source system is using the UTF8 encoding format hence the text is showing as ' � ' . Is there a way to convert the utf8 to actual character in the DTL.

Thank you,

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I would like to know which are the best practices of using Streams in Interoperability messages.

I have always use %Stream.GlobalCharacter properties to hold a JSON, or a base64 document, when creating messages. This is fine and I can see the content in Visual Trace without doing anything, so I can check what is happening and resolve issues if I have, or reprocess messages if something went wrong, because I have the content.

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