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We return to the attack with our EMPI!

In previous articles we have seen how to configure and customize our EMPI, we have seen how we can include new patients in our system through HL7 messaging, but of course, not everything is HL7 v.2 in this life! How could we configure our EMPI instance to work with FHIR messaging?

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Hi community members!

I'm trying to deploy a container based on IRIS Community for Health ML image available from this url but when I start the container the memory consumption skyrockets to 99% making impossible to work with the instance (it never goes below the 95% of the memory). When I do the same with the IRIS Community for Health image it never goes over 80% of memory.

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Article
· Jun 16, 2023 10m read
Creating a REST service in IRIS

One of the most common needs of our clients is the creation of REST services that allow access to the information present in IRIS / HealthConnect. The advantage of these REST services is that it allows the development of custom user interfaces with the most current technologies taking advantage of the reliability and performance of IRIS in the back-end.

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As we said yesterday... our EMPI can receive data from multiple sources, REST, HL7 messaging, etc. But it is possible that the standard fields are not enough and we want to expand the patient information to help discriminate and uniquely identify them. How could we customize patient data? Modifying the standard classes to our liking? NOOOOO!!!! Well, a little yes, but not like crazy, because if we modify standard classes carelessly we may find that in a future update we lose all these modifications.

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As a former JAVA developer it has always been a challenge to decide which database was the most suitable for the project we were going to develop, one of the main criteria I used was their performance, as well as their HA configuration capabilities ( high availability). Well, now is the time to put IRIS to the test with respect to some of the most commonly used databases, so I've decided to create a small Java project based on SpringBoot that connects via JDBC with a MySQL database, another of PostgreSQL and finally with IRIS.

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You may have already heard that, starting with IRIS and HealthShare HealthConnect 2023.2 versions, the internal Apache Server will be removed from the default installation, so it will be necessary to have an external application server such as Apache Server or NGINX.


In this article I am going to proceed to install a HealthShare HealthConnect 2023.1 so that it works with a pre-installed Apache Server. For this I will use a virtual machine on which I have installed an Ubuntu 22.04.

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Article
· May 22, 2023 6m read
Recovering a Mirror after crash

Here we are again with an article related to the Mirror!

In the previous article we saw how we could configure a Mirror between two IRIS instances, one acting as an active node and the other as a passive one. This mirroring system works on the transfer of a journal file that keeps the instance that works as a passive node continuously updated, but what happens if due to some communication failure or permissions of the journal file it is not transferred correctly?

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Welcome, dear members of the community!

In this article we are going to demonstrate the great potential that IRIS/HealthConnect makes available to all its users with the use of Embedded Python and we are going to do it by developing a small production that will allow us to recognize and identify the faces present in a JPG file from some images that we will use as a reference.

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Article
· Apr 25, 2023 12m read
Configuring Mirror in Docker

A common need for our customers is to configure both HealthShare HealthConnect and IRIS in high availability mode.

It's common for other integration engines on the market to be advertised as having "high availability" configurations, but that's not really true. In general, these solutions work with external databases and therefore, if these are not configured in high availability, when a database crash occurs or the connection to it is lost, the entire integration tool it becomes unusable.

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We start this new article refreshing what we did in the previous EMPI configuration articles:

  • Installation in Standalone mode the Patient Index on a HealthShare instance.
  • Configuration of basic parameters to start working with the EMPI.
  • Definition of indexes and weights for NICE process.

Very well, we are practically ready to start rolling our EMPI. We only have one detail left, to start the production created by the installation to be able to start working.

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Welcome community members to a new article! this time we are going to test the interoperability capabilities of IRIS for Health to work with DICOM files.

Let's go to configure a short workshop using Docker. You'll find at the end of the article the URL to access to GitHub if you want to make it run in your own computer.

Previously to any configuration we are going to explain what is DICOM:

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In the previous article we have reviewed how to install our EMPI in standalone, so we are ready to start the basic configuration of our EMPI.

First of all we have to do an initial basic configuration, we can access to the configuration from the Configuration menu of our Registry.

Selecting that option will allow to us to edit the basic configuration table of the Registry:

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Hi community! I would like to show you how to install and configure one of the HealthShare products, the Enterprise Master Patient Index or EMPI.

The EMPI provides to any organization a master patient index to identify each patient of the organization univocally. You can find more information about the EMPI in the following URL: https://www.intersystems.com/interoperability-platform/patient-index/

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I've been working for some days in the connectivity between NodeJS client applications and IRIS as server using web sockets.

You can get all the information in relation to the web socket connections using IRIS as a client or as a server from this URL: https://docs.intersystems.com/irislatest/csp/docbook/DocBook.UI.Page.cls...

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Dear community members!

A very common problem of our users is to use an external database as data source in an IRIS production. As many of you already know, we have two ways to connect directly to an external database, the first one is using an ODBC connection, the second is using JDBC.

In our example we are going to create a connection using JDBC, and we are going to build a simple Docker's project, in this way you will be able to modify the example as you wish.

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