Google Forms is the most popular solution on the market for collecting data, answering questionnaires and quizzes. So, it is the ideal solution for collecting patient data and responses in a practical way, without the need to expand or develop systems. In this article, I will detail how to create an account on Google Cloud, register the application that will consume the Google Forms API, generate the service user necessary to consume the API and finally perform actions to create new forms and collect data filled in them in an automated way in embedded Python and IRIS.

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.

InterSystems FAQ rubric

Use the ErrorList query of the SYS.ApplicationError class.

In our previous article we saw how to capture DICOM type files located in a folder in our server and how we could send them to a PACS software (in our case the ORTHANC open source solution) for storage and consultation. Well, in this article we are going to deal with the opposite movement.

When using InterSystems IRIS as an interoperability engine, we all know and love how easy it is to use the Message Viewer to review message traces and see exactly what's going on in your production. When a system is handling millions of messages per day, you may not know exactly where to begin your investigation though.

Over my years supporting IRIS productions, I often find myself investigating things like...

In the previous article, we saw different modules in IRIS AI Studio and how it could help explore GenAI capabilities out of IRIS DB seamlessly, even for a non-technical stakeholder. In this article, we will deep dive into "Connectors" module, the one that enables users to seamlessly load data from local or cloud sources (AWS S3, Airtable, Azure Blob) into IRIS DB as vector embeddings, by also configuring embedding settings like model and dimensions.

I know that people who are completely new to VS Code, Git, Docker, FHIR, and other tools can sometimes struggle with setting up the environment. So I decided to write an article that walks through the entire setup process step by step to make it easier to get started.

I’d really appreciate it if you could leave a comment at the end - let me know if the instructions were clear, if anything was missing, or if there’s anything else you'd find helpful.

The setup includes:

✅ VS Code – Code editor
✅ Git – Version control system
✅ Docker – Runs an instance of IRIS for Health Community
✅ VS Code REST Client Extension – For running FHIR API queries
✅ Python – For writing FHIR-based scripts
✅ Jupyter Notebooks – For AI and FHIR assignments

Before you begin: Ensure you have administrator privileges on your system.

In addition to reading the guide, you can also follow the steps in the videos:

For Windows

https://www.youtube.com/embed/IyvuHbxCwCY
[This is an embedded link, but you cannot view embedded content directly on the site because you have declined the cookies necessary to access it. To view embedded content, you would need to accept all cookies in your Cookies Settings]

Healthcare interoperability is instrumental in improving patient care, decreasing healthcare provider costs, and providing a more accurate picture to providers. However, with so many different systems, data is formatted in many different ways. There are many standards that have been created to try to solve this problem, including HL7v2, HL7v3, and CDA but each one has its drawbacks.

InterSystems FAQ rubric

The meaning of each timeout value is as follows.

1. [Server response timeout]

If IRIS/Caché processing (routine or query execution) does not finish within this set time, the browser will return an error.

For example, if this value is 60 seconds and it takes 90 seconds to execute a routine/method/query, an error will occur.

2. [Queued request timeout]

Would you like to be sure your data transforms work as expected with a single command? And what about writing unit tests for your data transforms in a quick and simple way?

When talking about interoperability, there are usually a lot of data transforms involved. Those data transforms are used to convert data between different systems or applications in your code, so they are running a very important job.

Who hasn't been developing a beautiful example using a Docker IRIS image and had the image generation process fail in the Dockerfile because the license under which the image was created doesn't contain certain privileges?

In my case, what I was deploying in Docker is a small application that uses the Vector data type. With the Community version, this isn't a problem because it already includes Vector Search and vector storage. However, when I changed the IRIS image to a conventional IRIS (the latest-cd), I found that when I built the image, including the classes it had generated, it returned this error:

InterSystems FAQ rubric

In the sample below, an image file is encoded into a Base64 string in a class property, saved, decoded again with Base64, and restored to another file.

【Usage class】

Class User.test Extends %Persistent
{
Property pics As %GlobalBinaryStream;
}

【When importing】

The ability to resend messages easily has always been a strong feature of our Interoperability capabilities.

With v2024.3 coming out soon (available already now as Developer Preview) out already we've made this even easier!