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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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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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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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