Article
· Jan 14 5m read
clinFHIR for developers

This article is intended to describe how the clinFHIR application can be used to help developers both understand FHIR and to develop applications that utilize FHIR artifacts. It’s not intended to be an introduction to FHIR, but rather describe how clinFHIR can help on the learning / development journey.

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Methods written in ObjectScript can use pass-by-reference arguments to return information to the caller. Python doesn’t support pass-by-reference arguments, so Embedded Python in IRIS doesn’t support them either. That's it, that's the end of the post, hope you liked it. 😉 But wait, what about the Classic Rock & Roll?

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Problem

In a fast-paced clinical environment, where quick decision-making is crucial, the lack of streamlined document storage and access systems poses several obstacles. While storage solutions for documents exist (e.g, FHIR), accessing and effectively searching for specific patient data within those documents meaningfully can be a significant challenge.

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The IKO allows for sidecars. The idea behind them is to have direct access to a specific instance of IRIS. If we have mirrored data nodes, the web gateway will (correctly) only give us access to the primary node. But perhaps we need access to a specific instance. The sidecar is the solution.

Building on the example from the previous article, we introduce the sidecar by using a mirrored data node and of course arbiter.

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** Revised Feb-12, 2018

While this article is about InterSystems IRIS, it also applies to Caché, Ensemble, and HealthShare distributions.

Introduction

Memory is managed in pages. The default page size is 4KB on Linux systems. Red Hat Enterprise Linux 6, SUSE Linux Enterprise Server 11, and Oracle Linux 6 introduced a method to provide an increased page size in 2MB or 1GB sizes depending on system configuration know as HugePages.

At first HugePages required to be assigned at boot time, and if not managed or calculated appropriately could result in wasted resources. As a result various Linux distributions introduced Transparent HugePages with the 2.6.38 kernel as enabled by default. This was meant as a means to automate creating, managing, and using HugePages. Prior kernel versions may have this feature as well however may not be marked as [always] and potentially set to [madvise].

Transparent Huge Pages (THP) is a Linux memory management system that reduces the overhead of Translation Lookaside Buffer (TLB) lookups on machines with large amounts of memory by using larger memory pages. However in current Linux releases THP can only map individual process heap and stack space.

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Article
· Mar 3, 2021 4m read
Access to IRIS from Rust

What do you think If I will say you, that very soon you will be able to connect to IRIS from the application written in Rust.

What is Rust

Rust is a multi-paradigm programming language designed for performance and safety, especially safe concurrency. Rust is syntactically similar to C++, but can guarantee memory safety by using a borrow checker to validate references. Rust achieves memory safety without garbage collection, and reference counting is optional. (c) Wikipedia

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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.

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Article
· Nov 30, 2022 14m read
Creating FHIR questionnaires

Intersystems IRIS for Health has excellent support for the FHIR industry standard. The main features are:
1. FHIR Server
2. FHIR Database
3. REST and ObjectScript API for CRUD operations on FHIR resources (patient, questionnaire, vaccines, etc.)

This article demonstrates how to use each of these features, as well as presenting an angular frontend for creating and viewing Quiz-like FHIR resources.

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Article
· Jul 7, 2023 8m read
Iris FHIR Python Strategy

Description

With InterSystems IRIS FHIR Server you can build a Strategy to customize the behavior of the server (see documentation for more details).

Image

This repository contains a Python Strategy that can be used as a starting point to build your own Strategy in python.

This demo strategy provides the following features:

  • Update the capability statement to remove the Account resource
  • Simulate a consent management system to allow or not access to the Observation resource
    • If the User has sufficient rights, the Observation resource is returned
    • Otherwise, the Observation resource is not returned
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We resume our series of articles on the FHIR Adapter tool available to HealthShare HealthConnect and InterSystems IRIS users.

In the previous articles we have presented the small application on which we set up our workshop and showed the architecture deployed in our IRIS instance after installing the FHIR Adapter. In today's article we will see an example of how we can perform one of the most common CRUD (Create - Read - Update - Delete) operations, the reading operation, and we will do it by recovering a Resource.

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This is more for my memory that anything else but I thought I'd share it because it often comes up in comments, but is not in the InterSystems documentation.

There is a wonderful utility called ^REDEBUG that increases the level of logging going into mgr\cconsole.log.

You activate it by

a) start terminal/login

b) zn "%SYS"

c) do ^REDEBUG

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Hi developers!

Maybe you have to implement scenarios that don't require a FHIR repository, but forwarding FHIR requests, manage the responses and maybe run transformations or extract some values in between. Here you will find some examples that can be implemented using InterSystems IRIS For Health o HealthShare Health Connect.

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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.

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Introduction

InterSystems has recently completed a performance and scalability benchmark of IRIS for Health 2020.1, focusing on HL7 version 2 interoperability. This article describes the observed throughput for various workloads, and also provides general configuration and sizing guidelines for systems where IRIS for Health is used as an interoperability engine for HL7v2 messaging.

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Article
· Jul 27, 2021 2m read
IRIS Interoperability Message Bank

I heard about Message Bank when we started redesigning a Health Connect production to run in containers in the cloud. Since there will be multiple IRIS containers, we were directed to utilize Message Bank as one place to view messages and logs from all containers.

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I am demonstrating a use case of how we can create an IRIS Interoperability Production for special use in an external language. InterSystems IRIS, within Interoperability has a framework called Production Extension (PEX), using which we can create productions and program them as per their purpose using external languages like Java, Python etc, and also develop custom inbound and outbound adapters to communicate with other applications.

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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.

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Article
· Jul 24, 2023 20m read
Local K8s Deployment of a FHIR server

k8s

This is a sample to deploy iris-oauth-fhir on k3d with IKO.
* iris-oauth-fhir is a sample to deploy a FHIR server with OAuth2 authentication with InterSystems IRIS for Health as a resource server and Google OpenId as an authorization server.
* k3d is a lightweight wrapper to run k3s (Rancher Lab's minimal Kubernetes distribution) in docker.
* IKO is a tool to deploy InterSystems IRIS for Health on Kubernetes.

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While reviewing our documentation for our ^pButtons (in IRIS renamed as ^SystemPerformance) performance monitoring utility, a customer told me: "I understand all of this, but I wish it could be simpler… easier to define profiles, manage them etc.".

After this session I thought it would be a nice exercise to try and provide some easier human interface for this.

The first step in this was to wrap a class-based API to the existing pButtons routine.

I was also able to add some more "features" like showing what profiles are currently running, their time remaining to run, previously running processes and more.

The next step was to add on top of this API, a REST API class.

With this artifact (a pButtons REST API) in hand, one can go ahead and build a modern UI on top of that.

For example -

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