#HealthShare

Hey everyone.

I came across some issues when setting up Freeze and Thaw batch scripts for use with VMWare in a Windows ecosystem, and I wanted to share what I found in the hopes it can help others. This was undertaken in an environment using Healthconnect 2019.1.x.

During the last weeks, I was working on various issues and problems related to SW development.
I found that quite often problem analysis was mostly chasing issues just on the surface
but not really attacking the deeper reasons of the problem and follow the consequences.
It's like the doc that stops your leg bleeding but doesn't see that it is broken.

This tutorial is a follow on to Working with %Query
It was displaying the content of the input stream chopped in fixed-size chunks.
But often those streams are structured and have well-defined separators (e.g HL7)
So as a side subject of this tutorial, this chapter shows how to break a stream into PIECES.

It is exactly the same idea as the $PIECE() function for strings with some add-ons.

Purpose

This pair of tools (RanRead and RanWrite) is used to generate random read and write events within a database (or pair of databases) to test Input/Output operations per second (IOPS). They can be used either in conjunction or separately to test IO hardware capacity, validate target IOPS, and ensure acceptable disk response times are sustained. Results gathered from the IO tests will vary from configuration to configuration based on the IO sub-system. Before running these tests ensure corresponding operating system and storage level monitoring are configured to capture IO performance metrics for later analysis. The suggested method is by running the System Performance tool that comes bundled within IRIS. Please note that this is an update to a previous release, which can be found here.

In case you've never used the "About" link at the top of Management Portal, here's a screenshot of the kind of information it shows. I've highlighted the link and some of the information I find it handy to get from here.

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.

Sometimes I observe people scrolling manually down to the bottom of the Console Log document when they want to see the most recent messages. So I want to draw attention to the handy link that does the job for you in a single click:

I only recently noticed the presence of a local database named CACHE alongside the more familiar CACHESYS, CACHELIB, CACHETEMP and CACHEAUDIT.

A bit of digging through the documentation archive led me to conclude that the CACHE database arrived in 2010.2, where the release notes say:

I was searching for the most simple way to connect from visual studio code to my local instance via terminal without having to change any window.

I know this can also be achieved via telnet but seems a bit overhead if you're in your local machine.

For me the simplest sollution is to open a terminal window in VS Code, navigate to the /bin folder of your instance installation and run .\csession.exe INSTANCENAME

For simplicity you can just include your /bin folder in your path so you don't even need to navigate there

Hello, friends who are developing IRIS. I recently participated in the InterSystems Developer Tools Contest. This time, I made a tool based on the idea described in an article I published earlier as a template for quick query of messages. Currently, you only need to establish entity classes in IRIS, Then record the message corresponding to the entity class in the specified lookup table, and all the key fields generated in the message can be inverted indexed (the concept in ElasticSearch), which is convenient for quick query. The following is the design idea of my program.

Keywords: Deep Learning, Grad-CAM, X-Ray, Covid-19, HealthShare, IRIS

Purpose

Over the Easter Weekend I touched on some deep learning classifier for Covid-19 Lungs. The demo result seems fine, seemingly matching some academic research publications around that time on this topic. But is it really "fine "?

The class %Compiler.UDL.TextServices arrived in 2015.1, bringing us methods for exporting a class in UDL format (i.e. looking just like we're used to seeing it in Studio), and importing a UDL format definition back into a namespace. Some source control tools including our Deltanji are now able to use UDL format, resulting in diffs that are easier to understand.

The CIO Perspective

Executive Summary

Featuring the results of the HIMSS Analytics Interoperability Study

Introduction