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.

Hi InterSystems Developers!

Recently I've updated the FHIR dev template so that it now publishes an IPM package fhir-server that makes the setup of InterSystems FHIR server a trivial manual or automatic or programmatic procedure one command long.

Please see below how you can benefit from it.

TLDR

USER>zpm "install fhir-server"

All the details below.

In the previous article, we talked about the flow of data to request the test and receive the results of the requested test. Now let's talk about one of the most important messages of HL7v2 standard.

Every time a receiving application accepts a message and consumes the message data, it is expected to send an ACKnowledgement (ACK) message back to the sending application. The sending application is expected to keep on sending a message until it has received an ACK message. It is done to inform the sending application that its message was successfully received, that it is (not) valid in accordance with HL7 rules and, if it is compliant, that it will be processed at some point.

In this article, we'd like to describe Med.me's incubation experience and takeaways, the cross-organizational booking problem, and our approach to solving it.

This exciting story started during one of the regular medtech meetups, where I met @Evgeny Shvarov, senior InterSystems chief of the Developer Community. Following the good old startup rule “pitch wherever you can”, I briefly explained to Evgeny Med.me concept – EHR exchange and appointment scheduling platform to automate and simplify communication between clinics, pharma on one hand and insurance companies, doctors, and patients on the other.

Evgeny listened carefully and replied that InterSystems provides plenty of products to solve the interoperability problems amongst the vast variety of EMRs and kindly advised me to hurry up to apply to the FHIR incubator Caelestinus powered by InterSystems.

That led to a start of an amazing 9-months long road where we were able to ramp up our understanding of interoperability, participate at the InterSystems Global Summit, find new customers and partners, and where the new concept of Resource Availability Exchange was born.

In the previous article, we've seen the structure of one of the most used types of HL7 message - ADT (Admit, Discharge, Transfer) and an example of ADT^A04 with the description of all its fields. Now let's look at another flow of data having to do with ordering and fulfilling the orders of tests. I'm talking about ORM (as of version 2.5 you should use specific messages to order tests, like OMG, OML, OMD, OMS, OMN, OMI, and OMP), ORL and ORU messages. In a very simplified case, the exchange of data may look like this.

Let's look at these messages in more detail.

When creating a PRA (Privileged Routine Application; which by the way is not relevant just for Routines but also for Classes/Methods), it is important to make sure you include a new $ROLES, before calling

Hi, I would like to tell you how easy it is to spin up IRIS for Health docker container in compute engine(VPS) in google cloud.

I know that to run IRIS for Health in AWS is pretty simple and straightforward, but I wanted to tried if its same easy in GCP environment.

Create vm instance. 2GB RAM is more than enough.

I used Debian 11 as Linux distro.

Standart persistent disk is cheaper.

I've been working for 19 years in the technology field, and on this journey, I was able to be part of several projects on numerous fronts; however, the health area is one of the areas that attract me the most.

So whenever we get a chance to create something focused on health, using the FHIR protocol is exciting.

But, a team of 3 IT guys with a tech background would not be enough to deliver something really useful, and for a topic as important as women's health, we brought to the team someone who really understands the subject.