#FHIR

I have attached a document that describes the product I have developed called NiPaRobotica Pharmacy. This is an interface I developed that accepts Pharmacy Dispense Requests and converts the line items on the order into dispense dialogues which it sends to pharmacy robots. I deployed the interface into 3 Hospital pharmacies two of which had 6 robots that were arranged in such a way that the dispense chutes channelled medications to desks by the pharmacists sitting in windows serving 1200 patients a day. The robots cut the average waiting time from 2 hours down to one hour.

We are ridiculously good at mastering data. The data is clean, multi-sourced, related and we only publish it with resulting levels of decay that guarantee the data is current. We chose the HL7 Reference Information Model (RIM) to land the data, and enable exchange of the data through Fast Healthcare Interoperability Resources (FHIR®).

Hi folks!

Recently I was in need to setup a local FHIR server using IRIS For Health and I think I found the easiest and simplest way ever.

Just run in terminal these two lines below :

docker run --rm --name my-iris -d --publish 9091:1972 --publish 9092:52773 intersystemsdc/irishealth-community

and

docker exec -it my-iris iris session iris -U "USER" '##class(%ZPM.PackageManager).Shell("install fhir-server")'

And you'll have FHIR server running locally at http://localhost:9092/fhir/r4.

That's it!

The FHIR server will use the latest build of InterSystems IRIS for Health Community Edition and will deploy FHIR server from this app via IPM package in FHIRSERVER namespace.

This is for Mac, so please add in comments how it works in Windows.

This is a very short article as it is really easy to setup a local FHIR server with InterSystems IRIS for Health and IPM Package Manager.

I have challenged to create a bot application using Azure Bot that can retrieve and post data to IRIS for Health.

A patient's data has already been registered in the FHIR repository of IRIS for Health.

The patient's MRN is 1001. His name is Taro Yamada. (in Japanese :山田 太郎)

This bot can post new pulse oximeter readings as an observation resource linked to the patient.

Surely you have all heard about FHIR as the panacea and solution to all interoperability and compatibility problems between systems. Right here we can see one of his classic defenders holding a FHIR resource in his hand and enjoying it immensely:

But for the rest of us mortals we are going to make a small introduction.

Fun or No Fun - how serious is it?

Large language models are stirring up some phenomena in recent months. So inevitably I was playing ChatGPT too over last weekend, to probe whether it would be a complimentary to some BERT based "traditional" AI chatbots I was knocking up, or rather would it simply sweep them away.

Hello, developers!

In this series, I will not show you how to use IRIS for Health, but rather how to use SUSHI, a tool for creating FHIR profiles, as an associated technology.

With the right tools, the profile information (specifications, limitations, extensions, etc.) of a FHIR project can be well organized and published.

Before we begin, what is SUSHI? I will briefly explain it.

New in version 2023.3 (of InterSystems IRIS for Health) is a capability to perform FHIR profile-based validation.

(*)

In this article I'll provide a basic overview of this capability.

If FHIR is important to you, you should definitely try out this new feature, so read on.

Brainstorming the project we would build to showcase in the current female health themed InterSystems FHIR Contest, our girl band decided that we need to do something practical for the ordinary user and to solve some burning issues of the modern life. This discussion led to the idea of creating a project that will help women not to forget their health in daily grind - FemTech Reminder.

I created this application considering how to convert images such as prescription forms into FHIR messages

It recognizes the text in the image through OCR technology and extracts it, which is then transformed into fhir messages through AI (LLA language model).

Finally, sending the message to the fhir server of IntereSystems can verify whether the message meets the fhir requirements. If approved, it can be viewed on the select page.

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.

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.

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.

Description

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

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