Article
· Feb 1 2m read
Mind map your FHIR patient data

According Wikipedia a mind map is a diagram used to visually organize information into a hierarchy, showing relationships among pieces of the whole. It is often created around a single concept, drawn as an image in the center of a blank page, to which associated representations of ideas such as images, words and parts of words are added. Major ideas are connected directly to the central concept, and other ideas branch out from those major ideas.

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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.

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Background

In 2021, I participated as an InterSystems mentor in a hackathon, where a newcomer to FHIR asked me if there was a tool to transform generic JSON data containing basic patient information into FHIR format. I informed her that I didn't know anything like that, unfortunately.

But that idea stays in my mind...

Several months later, in 2022, I came up with an idea to experiment: to train a named entity recognition (NER) to identify FHIR elements into generic texts. The training involved synthetic FHIR data generated by Synthea and the spaCy Python library.

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In the last article we presented the architecture of our SMART On FHIR project, so it's time to get down to business and start configuring all the elements that we are going to need.

We will first start with Auth0.

AUTH0 configuration

We will start by creating an Auth0 account with a valid email, once registered we will have to create our first application, and we will do it from the menu on the left:

Application menu

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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.

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Article
· Jan 29 2m read
Get familiar with FHIR

🔥 Curious about the FHIR standard that everyone's talking about?

📚 Read on for a brief introduction, then try a brand-new learning path to get more in-depth knowledge!

The HL7® FHIR® standard has revolutionized the way healthcare developers take on the challenges of data interoperability. FHIR allows healthcare systems to exchange information seamlessly, and patient data can be consolidated in real time, regardless of where it's stored.

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Sometimes we need to convert FHIR message to HL7 V2, e.g. to register a patient to the PACS system.
In this article, I will explain the steps to achieve the desired by using IRIS FHIR Server production.

Below are the steps we need to follow:

  1. Make sure FHIRServer production is started.
  2. Register Business Service with FHIRServer endpoint.
  3. Define Business Processes to convert FHIR message to SDA and then Convert SDA to HL7 v2.
  4. Post JSON resource to FHIRServer endpoint and get HL7 V2 response.

Let's review the steps in detail.

Step 1. Make sure FHIRServer production is started

Open the production page and make sure Production is started. In the next step, we need to make sure business service HS.FHIRServer.Interop.Service is registered with FHIRServer

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Introduction

I recently participated in a fantastically organized hands-on by @Patrick Jamieson in which an Angular application was configured together with an IRIS FHIR server following the protocols defined by SMART On FHIR and I found it really interesting, so I decided to develop my own Angular application and thus take advantage of what I learned to publish it in the Community.

SMART On FHIR

Let's see what Google tells us about SMART On FHIR:

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Article
· Jan 28 3m read
Fhir-HepatitisC-Predict

Processing FHIR resources with FHIR SQL BUILDER to predict the probability of developing hepatitis C disease

With the development of technology, the medical industry is also constantly advancing, and humans often pay more attention to their own health,
By learning and processing datasets through computers, diseases can be predicted.

Pre condition: Ability to use FHIR and ML
Firstly, our dataset is obtained from kaggle and transformed into FHIR resources based on patient gender, age, ALP or ALT, and imported into the FHIR resource repository

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Hi Community

This document mainly enriches the content of the previous article and introduces the use of the application.

Perhaps you have already read the previous article, but I still want to say,
After completing the initialization operation (including model creation and training), the Fhir HepatitisC Predict application then predicts HepatitisC

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1Background

When I first encountered FHIR, I encountered a problem with its message format. It was difficult for me to determine whether the message I created met the format, and it was also difficult to easily create an FHIR message from scratch.

So, through fhir server of IntereSystemsfhirserver API, I created this application for quickly generating/validating FHIR messages.

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We conclude this series of SMART On FHIR articles with Auth0 and InterSystems IRIS FHIR Repository by reviewing our application developed in Angular 16.

Let's remember what the architecture defined for our solution is like:

Our front-end application corresponds to the second column and as you can see it will be in charge of two things:

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