Henrique Dias · Aug 22, 2020 2m read
An overview of iris-fhir-portal

I created the iris-fhir-portal as part of the current contest InterSystems IRIS for Health FHIR, and I'm writing this quick overview to introduce the features that my application offers.

The goal of iris-fhir-portal is to show how easy we can create a Patient Chart using FHIR capabilities in IRIS for Health and empower the user with their own data.

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Myself and the other Technology Architects often have to explain to customers and vendors Caché IO requirements and the way that Caché applications will use storage systems. The following tables are useful when explaining typical Caché IO profile and requirements for a transactional database application with customers and vendors. The original tables were created by Mark Bolinsky.

In future posts I will be discussing more about storage IO so am also posting these tables now as a reference for those articles.

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Henrique Dias · Jan 13, 2022 4m read
How to find the dataset you need?

Hey community! How are you doing?

I hope to find everyone well, and a happy 2022 to all of you!

Over the years, I've been working on a lot of different projects, and I've been able to find a lot of interesting data.

But, most of the time, the dataset that I used to work with was the customer data. When I started to join the contest in the past couple of years, I began to look for specific web datasets.

I've curated a few data by myself, but I was thinking, "This dataset is enough to help others?"

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Hi Community,

This post is a introduction of my openexchange iris-python-apps application. Build by using Embedded Python and Python Flask Web Framework.
Application also demonstrates some of the Python functionalities like Data Science, Data Plotting, Data Visualization and QR Code generation.



  • Responsive bootstrap IRIS Dashboard

  • View dashboard details along with interoperability events log and messages.

  • Use of Python plotting from IRIS

  • Use of Jupyter Notebook

  • Introduction to Data Science, Data Plotting and Data Visualization.

  • QR Code generator from python.

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Hello, developers!

In this series, I will not show you how to use IRIS for Health, but rather how to use SUSHI, a tool for creating FHIR profiles, as an associated technology.

With the right tools, the profile information (specifications, limitations, extensions, etc.) of a FHIR project can be well organized and published.

Before we begin, what is SUSHI? I will briefly explain it.

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Hi everyone,

I want to talk about our project and use the dataset theme for this contest.

Our intention never was to be a data curator, especially because sometimes my precious data means a lot for me, but not for the rest of the world.

My Precious

We want to go a step further and empower the user to find the perfect dataset for their needs.

Our project is a bridge between the data science community and the developer's community using InterSystems IRIS to achieve this mission.

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Robert Cemper · Feb 8, 2021 3m read
WebSocket Client with embedded Python

This is a demo to make use of a simple WebSocket Client with Embedded Python in IRIS.

To continue my series of WebSocket Client I have added an example written in Python.
The most impressive experience was how easy the writing and testing of the client was
which happened total offline from IRIS.
Embedding, running and feeding the client with data from IRIS was also incredibly simple.

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We often run into connectivity problems with HealthShare (HS) deployments in Microsoft Azure that have multiple HealthShare components (instances or namespaces) installed on the same VM, especially when needing to communicate to other HS components while using the Azure Load Balancer (ILB) to provide mirror VIP functionality. Details on how and why a load balancer is used with database mirroring can be found this community article.

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For those that, at some point, need to test what means that of ECP for horizontal escalability (computing power and/or users and processes concurrency), but they're lazy o have no much time to build the environment, configure the server nodes, etc..., I've just published in Open Exchange the app/sample OPNEx-ECP Deployment .

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Released with no formal announcement in IRIS preview release 2019.4 is the /api/monitor service exposing IRIS metrics in Prometheus format. Big news for anyone wanting to use IRIS metrics as part of their monitoring and alerting solution. The API is a component of the new IRIS System Alerting and Monitoring (SAM) solution that will be released in an upcoming version of IRIS.

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I recently published the "appmsw-docbook" module for deploying the solution not by individual programs, but by the entire database. This solution allows you to deploy a project without source codes.

Having received feedback, I decided to improve it significantly. Replaced zip archive with tgz, which will allow not using external system-dependent archivers.

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FHIR Terminology Service specification describes a set of operations on CodeSystem, ValueSet and ConceptMap resources. Among those operations, the following four operations appear to be the most widely adopted ones:

CodeSystem ValueSet

Developing a partial implementation of the specification has been an effective way to explore the new FHIR framework introduced in IRIS for Health 2020.1. The implementation includes four operations listed above, and supports read and search interactions for CodeSystem and ValueSet resources.

It's important to note that the implementation uses plain ObjectScript persistent classes as source terminology tables.

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Guillaume Rongier · Apr 9, 2019 3m read
IRIS/Ensemble as an ETL

IRIS and Ensemble are designed to act as an ESB/EAI. This mean they are build to process lots of small messages.

But some times, in real life we have to use them as ETL. The down side is not that they can't do so, but it can take a long time to process millions of row at once.

To improve performance, I have created a new SQLOutboundAdaptor who only works with JDBC.


Extend EnsLib.SQL.OutboundAdapter to add batch batch and fetch support on JDBC connection.

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I have just created a new Global Master Topic, "IRIS Cheatsheets". IRIS has introduced a lot of new functionality, especially in scripting languages, FHIR R4 support, enhanced Interoperability Tools, and IRIS Analytics. Having spent 35 years working on Windows-based PC's and Laptops, I have surprisingly little knowledge of Linux, Docker and Git. Furthermore, I have written almost every application and Interface in ObjectScript with splatterings of SQL, .Net, and Java Gateways and the most basic knowledge of WinSCP, Putty, SSH. All that changed when I received my first Raspberry Pi.

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In this article I will demonstrate the following :

  • Update ReferencesRange(OBX:7) against ObservationIdentifier(OBX:3.1)[TestCode] from database by using custom utility function
  • Update Abnormal Flag(OBX:8) against ObservationIdentifier(OBX:3.1)[TestCode] and ObservationValue(OBX:5)[Result] from database utility function
  • Route Message based on Abnormal Flag(OBX:8)

Below is the primary and transformed HL7 2.5 ORU_R01 message:

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