Hello Developers!

Have you ever had to convert HL7v2 messages to FHIR (Fast Healthcare Interoperability Resources) and found the process complicated and confusing? InterSystems is rolling out a new cloud based SaaS offering called HealthShare Message Transformation Services, which makes the process easy.  We are excited to announce an Early Access Preview Program for our new offering, and we would love to have you kick the tires and let us know what you think!  All you need is a free AWS account, with an S3 bucket to drop in your HL7v2 messages, and another S3 bucket to get your FHIR output. 

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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.

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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.

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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®).

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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.

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Article
Evgeny Shvarov · May 28, 2021 1m read
Fetch Upstream in GitHub

Hi colleagues!

Often when we collaborate to someone's repo in GitHub we do the following cycle:

Fork-Clone-Change-Commit-Push-Pull-Request-Merge to the original repo.

This is all great and works fine!

And if we want to make a second collaboration right after the merge you need to perform "Fetch upstream" to your forked repo first to "ingest" your own Pull-request in the original repo.

Geeky git-professionals do it with ease but this was always a headache for me so I usually simply deleted the fork and created a new one.

And today I figured that Github added a new UI feature that I can easily fetch-upstream for my fork with the original one and make it up to date and capable for pull-requests.

Here is where the button is:

This is a relief! )

Wanted to share this relief and productivity tip with you!

Bring more collaborations to Github repos!

And speaking of PR - I just made a PR with docker to Google Cloud Run deployment for the FHIRaaS demo made by @Anton Umnikov for the current FHIR Contest! Looking for more of your contributions!

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Announcement
Patrick Jamieson · Mar 15, 2021
FHIR Analytics

Hi developers,

We have received quite a lot of interest in using SQL on FHIR data. As you know, FHIR data is encoded in the form of a complex directed graph, and thus you can not easily query it with traditional SQL queries or business intelligence tools. Some customers have noticed that the "FHIR search tables" in IRIS for Health have flattened part of the FHIR graph, and have tried to use them for analytics. This is an undocumented and unsupported part of IRIS for Health, and can change without notice.

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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.

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Hi everyone,

I am very pleased to announce that the Readmission Demo has been released as open source. Many thanks to the Solution Factory team that worked hard on making this possible.

Here are the changes:

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Hey Community,

Please join the next InterSystems online programming competition:

🏆 InterSystems FHIR Accelerator Programming Contest 🏆

Submit an application that uses InterSystems FHIR-as-a-service on AWS or helps to develop solutions using InterSystems IRIS FHIR Accelerator.

    Duration: May 10 - June 06, 2021

    Total prize: $8,750 

    👉  Landing page 👈

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    Hey Developers!

    This week is a voting week for the InterSystems IRIS for Health FHIR Contest!

    So, it's time to give your vote to the best FHIR solutions built with InterSystems IRIS for Health.

    🔥 You decide: VOTING IS HERE 🔥

     

    How to vote? This is easy: you will have one vote, and your vote goes either in Experts Nomination or in Community Nomination.

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    Hi Community!

    We're pleased to invite you to the Online meetup with the winners of the InterSystems FHIR programming contest!

    Date & Time: Friday, September 4, 2020 – 11:00 EDT

    What awaits you at this virtual Meetup? 

    • Our winners' bios.
    • Short demos on their applications.
    • A short interview with all the winners about the past contest. Plans for the next contests.

        

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    A simple production that enables FHIR transaction bundles to be loaded into InterSystems® FHIR® Server via Box and Dropbox.  Using the included MFT Connection Components and a 14 liner Custom Business Process, this production will process your transaction bundles to FHIR Resources for immediate consumption with Harry Potter like wizardry.  Great for Hackathons, Research and FHIR® Cocktail parties.

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    Hi guys.

    Recently, I get interest in FHIR in order to run for the IRIS for Health FHIR
    contest
    . As a beginner on this topic, I've heard somewhat about it, but I didn't know how complex and powerful was FHIR. As pointed out by @Henrique Dias here, you can model several aspects of the patient history and other related entities.

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    Google has one intersting tool named Data Studio. This tool allows creating some interactive dashboards, based on your data, available from the internet. It already offers hundreds of connectors to any sort of data developed by the community. As well as some amount of community developed visualizing. And most importantly, Google offers a way to develop your own connector to your data. 

    FHIRaaS provides a REST API, and it's available from the internet. So I've decided to try to create some basic report on data stored there. And in the end, I got this.

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    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.

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    FHIR Terminology Service specification describes a set of operations on CodeSystem, ValueSet and ConceptMap resources. Among those operations, the following four operations appear to be the most widely adopted ones:

    CodeSystem ValueSet
    $lookup
    $validate-code
    $expand
    $validate-code

    Developing a partial implementation of the specification has been an effective way to explore the new FHIR framework introduced in IRIS for Health 2020.1. The implementation includes four operations listed above, and supports read and search interactions for CodeSystem and ValueSet resources.

    It's important to note that the implementation uses plain ObjectScript persistent classes as source terminology tables.

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