I'm always on the lookout for tools that make the development and testing of my interfaces more efficient. A couple of years ago I came across HL7 Spy, from Inner Harbour Software. It quickly became my go-to tool for running message comparison reports for interface engine migrations, message statistics gathering, and troubleshooting message receipt and delivery. It also offered enhanced functionality for things like fetching messages via sftp that other tools don't provide.

I've recently been working with HL7 Spy's author, Jon Reis, to enable support for fetching messages directly from the Ensemble message store. Its SQL Loader feature now has native Caché/IRIS support, and I've contributed a small server-side class to support the extraction of messages using it.

InterSystems FAQ rubric

In this article, we will introduce how to deal with the situation: "I accidentally deleted a global!"

InterSystems FAQ rubric

The ID of the last updated record can be obtained using the SQL function LAST_IDENTITY().
* This function can be used with embedded SQL or ODBC but not with Dynamic SQL, SQL Shell, or the Management Portal's SQL interface.

Here's an example of usage with simple Embedded SQL:

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...

​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.

Introduction

Say you have a receiving system that accepts HL7 and provides error messages in field ERR:3.9 in the ACK it returns. You require a different reply code action depending on the error message, however the Reply Code Actions settings for the operation do not provide this level of granularity. One option could be to create a process that takes the ACK and then completes the action you were expecting, however things can get a bit messy if the action is to retry the message, especially when trying to view a message trace.

SSH framework is a relatively representative framework of Java, which was popular many years ago. There are Struts+Spring+hibernate and Spring MVC+Spring+hibernate. Of course, I used the second one in college. If I can connect IRIS to Hibernate as a library, does it also mean that IRIS can be developed using SSH framework in theory?

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.

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.

Overview

With the gradual improvement of hospital information construction, there are more and more business interfaces in hospitals. Due to the influence of various factors (network, consumer system, etc.), the data processing of business interface may cause excessive message accumulation and even the situation of interface card congestion, which affects the normal business development in the hospital. Therefore, the monitoring of the queue of business interface components becomes more and more important.

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.

If you want to know more about a new project or generate a new way to see your project, the better way is using mindmaps or markdown documentation. The IRIS Connections allows to you generate the mindmap for your classes and get your classes documentation in a markdown file.

Python has become the most used programming language in the world (source: https://www.tiobe.com/tiobe-index/) and SQL continues to lead the way as a database language. Wouldn't it be great for Python and SQL to work together to deliver new functionality that SQL alone cannot? After all, Python has more than 380,000 published libraries (source: https://pypi.org/) with very interesting capabilities to extend your SQL queries within Python.

In the previous article, we've discussed the origin of the standard HL7v2, the structure and the types of messages. Let's now look at one of the most used types of messages and an example of its structure. I'm talking about ADT.

HL7 ADT messages (Admit, Discharge, Transfer) are used to communicate basic patient information, visit information and patient state at a healthcare facility. ADT messages are one of the most widely-used and high volume HL7 message types, as it provides information for many trigger events including patient admissions, registrations, cancellations, updates, discharges, patient data merges, etc.