Striking a Balance Between Health Analytics and Engaging Features

The InterSystems Iris Fhirserver running on a Raspberry Pi Raspberry running as a FHIRserver

Raspberry running as FHIRserver

About a year ago I wrote some articles about the installation of the HAPI FHIRserver on a Raspberry Pi. At that time, I only knew the basics of the FHIR standard, little about the technology behind FHIR-servers and not much more about the Raspberry. By trying, failing, giving up and trying again I learned a lot.

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.

Swift-FHIR-Iris

iOS app to export HealthKit data to InterSystems IRIS for Health (or any FHIR repository)

Hi Community,

I want to share my experience creating the iris-fhir-portal with FHIR.

I decided to take a step forward and join the IRIS for Health FHIR contest, but I had never worked with FHIR before.

After the FHIR Contest Kick-Off Webinar, where we got an overview of how the IRIS for Health works with FHIR, I started to looking at the FHIR documentation to create my Patient Chart project.

Motivation

The motivation behind the InterLang project is rooted in the innovative integration of LangChain chatbot agents with the Fast Healthcare Interoperability Resources (FHIR) framework to revolutionize conversational social prescriptions in healthcare. This project aims to leverage the rich and standardized data available through FHIR, an emerging standard in healthcare data exchange, to inform and empower these advanced chatbot agents.

Hi everyone!

Just wanted to share here a quick post about my project for the Grand Prix :)

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.

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.

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.

Introduction

This article aims to explore how the FHIR-PEX system operates and was developed, leveraging the capabilities of InterSystems IRIS.

Streamlining the identification and processing of medical examinations in clinical diagnostic centers, our system aims to enhance the efficiency and accuracy of healthcare workflows. By integrating FHIR standards with InterSystems IRIS database Java-PEX, the system help healthcare professionals with validation and routing capabilities, ultimately contributing to improved decision-making and patient care.

In the past, reading information from a bar code was limited to a simple alphanumeric code. The creation of a bar code with more than one dimension (2D), especially the QR Code, allowed to increase the amount and variety of data stored in a bar code. While conventional bar codes are capable of storing a maximum of approximately 20 digits, the QR Code is capable of handling several tens to hundreds of times more information. This revolutionized the markets. Now QR codes are everywhere and can be very useful for storing textual, numeric, alphanumeric and even binary data.

Healthcare interoperability is instrumental in improving patient care, decreasing healthcare provider costs, and providing a more accurate picture to providers. However, with so many different systems, data is formatted in many different ways. There are many standards that have been created to try to solve this problem, including HL7v2, HL7v3, and CDA but each one has its drawbacks.