​Keywords: ChatGPT, COS, Lookup Table, IRIS, AI

Purpose

Here is another quick note before we move on to GPT-4 assisted automation journey. Below are some "little" helps ChatGPT had already been offering, here and there, during daily works.

And what could be the perceived gaps, risks and traps to LLMs assisted automation, if you happen to explore this path too. I'd also love to hear anyone's use cases and experiences on this front too.

InterSystems IRIS for Health ENSDEMO

Yet another basic setup of ENSDEMO content into InterSystems IRIS for Health.

Make sure you have Docker up and running before starting.

Setup

Clone the repository to your desired directory

git clone https://github.com/OneLastTry/irishealth-ensdemo.git

Once the repository is cloned, execute:

Always make sure you are inside the main directory to execute docker-compose commands.

Hi Community,

This post is a introduction of my open exchange iris-fhir-client application.

iris-fhir-client can connect to any open FHIR Server by using embedded python with the help of fhirpy Library.
Get Resource information by terminal and by using CSP web application.

Loading your IRIS Data to your Google Cloud Big Query Data Warehouse and keeping it current can be a hassle with bulky Commercial Third Party Off The Shelf ETL platforms, but made dead simple using the iris2bq utility.

Let's say IRIS is contributing to workload for a Hospital system, routing DICOM images, ingesting HL7 messages, posting FHIR resources, or pushing CCDA's to next provider in a transition of care. Natively, IRIS persists these objects in various stages of the pipeline via the nature of the business processes and anything you included along the way. Lets send that up to Google Big Query to augment and compliment the rest of our Data Warehouse data and ETL (Extract Transform Load) or ELT (Extract Load Transform) to our hearts desire.

A reference architecture diagram may be worth a thousand words, but 3 bullet points may work out a little bit better:

• It exports the data from IRIS into DataFrames
• It saves them into GCS as .avro to keep the schema along the data: this will avoid to specify/create the BigQuery table schema beforehands.
• It starts BigQuery jobs to import those .avro into the respective BigQuery tables you specify.

Overview

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.

Hi all!

I'm sharing a tool for data ingestion that we have used in some projects.

DataPipe is an interoperability framework for data ingestion in InterSystems IRIS in a flexible way. It allows you to receive data from external sources, normalize and validate the information and finally perform whatever operation you need with your data.

Like hardware hosts, virtual hosts in public and private clouds can develop resource bottlenecks as workloads increase. If you are using and managing InterSystems IRIS instances deployed in public or private clouds, you may have encountered a situation in which addressing performance or other issues requires increasing the capacity of an instance's host (that is, vertically scaling).

When you first start working with InterSystems IRIS, it’s a common practice to install a system with only a minimum level of security. You have to enter passwords fewer times and this makes it easier to work with development services and web applications when you're first getting acquainted. And, sometimes, minimal security is more convenient for deploying a developed project or solution.
And yet there comes a moment when you need to move your project out of development, into an Internet environment that’s very likely hostile, and it needs to be tested with the maximum security settings (that is, completely locked down) before being deployed to production. And that’s what we’ll discuss in this article.
For more complete coverage of DBMS security issues in InterSystems Caché, Ensemble, and IRIS, you may want to read my other article, Recommendations on installing the InterSystems Caché DBMS for a production environment.
The security system in InterSystems IRIS is based on the concept of applying different security settings for different categories: users, roles, services, resources, privileges, and applications.

Users can be assigned roles. Users and roles can have privileges on resources — databases, services, and applications — with varying read, write, and use rights. Users and roles can also have SQL privileges on the SQL tables located in databases.

Hello everyone, this is with great pleasure that I announce the V2 of my application 'Contest-FHIR'.

In this new version, I used new tools and techniques I discovered at the EUROPEAN HEALTHCARE HACKATHON in which I was invited by InterSystems as a guest and as a mentor to display the multiple projects I did in my intership back in April 2022.

Today I present to you the V2 of my application, it can now transform CSV to FHIR to SQL to JUPYTER notebook.

About regulations

Personal data privacy regulations have become an indispensable requirement for projects dealing with personal data. The compliance with these laws is based on 4 principles:

Intro

If you ever wondered how to debug some requests that are being made to or from IRIS, well here is a little tutorial on how to do that.

During a complex project, usually you get the specifications and implement the communication between IRIS and other things based on that. But from the paper to the real world there's usually a huge gap and you need to know why you are receiving an error on a parameter, on a header, you are not receiving the data and so on.

Hi Developers!

Another way to start using InterSystems ObjectScript Package Manager is to use prebuilt container images of InterSystems IRIS Community Edition and InterSystems IRIS for Health Community Edition.

We deploy this IRIS images on DockerHub and you can run it with the following command:

docker run --rm -p 52773:52773 --init --name my-iris -d intersystemsdc/iris-community:2019.4.0.383.0-zpm

Launch a terminal with:

docker exec -it my-iris iris session IRIS

And install zpm-module as:

USER>zpm 

zpm: USER>install objectscript-math

[objectscript-math] Reload START

[objectscript-math] Reload SUCCESS

[objectscript-math] Module object refreshed.

[objectscript-math] Validate START

[objectscript-math] Validate SUCCESS

[objectscript-math] Compile START

[objectscript-math] Compile SUCCESS

[objectscript-math] Activate START

[objectscript-math] Configure START

[objectscript-math] Configure SUCCESS

[objectscript-math] Activate SUCCESS

zpm: USER>

And use same commands for InterSystems IRIS for Health using the tag: intersystemsdc/irishealth-community:2019.4.0.383.0-zpm

The images are being published on IRIS Community Edition and IRIS Community Edition for Health repositories of Docker Hub.

We will update tags with every new release of IRIS and ZPM.

Happy coding!

1. Overview

With more and more hospital applications built, business interface data processing may be affected by a variety of factors (network, consumer systems, etc.), there is an excessive accumulation of messages or even cause interface lag, affecting the routine performance of hospital IT systems , so the monitoring of the business interface components queue is increasingly important.

While current Intersystems IRIS platform's built-in queue monitoring only displays real-time queue information for interface components, which is limited in providing the queue data information needed by hospitals. The queue monitoring component program is based on the Intersystems IRIS platform and can monitor all interface components and display component queue information within 24h of the component, as well as query component historical queue data by setting a time period to better meet the needs of current in-hospital applications.

For a long time, we have been using a utility in production to export the result of a query to an Excel spreadsheet. Moreover, we have applied a modification of it, in which the explicit setting of column formats is a priority.