#integration-required

For historic reasons we've got a mix of ADT feeds coming out of our PAS (TrakCare) to a wide range of downstream systems. In particular, there are some that are direct from TrakCare to the downstream systems, and many more that pass through Ensemble as our integration engine.

This is complicating management of the integrations, and so we'd like everything to go through the integration engine. In other words move from the flow in the top of the diagram to the flow in the bottom of the diagram:

So we want to build a couple of pass-through interfaces in Ensemble that respond identically to the

This article will cover turning over control of provisioning the InterSystems Kubernetes Operator, and starting your journey managing your own "Cloud" of InterSystems Solutions through Git Ops practices. This deployment pattern is also the fulfillment path for the PID^TOO||| FHIR Breathing Identity Resolution Engine.

Git Ops

I encourage you to do your own research or ask your favorite LLM about Git Ops, but I can paraphrase it here for you as we understand it.

Summary

A Quick start to include InterSystems IRIS Tables in Data Build Tool using Python.

It uses the sqlalchemy plugin with sqlalchemy-iris which enables the iris strategy for duckdb as a source for a dbt project.

EDIT: If you stumbled here on Google Geuse for "iris dbt", your best bet is to checkout dbt-iris for the native adapter implementation that follows dbt guidelines.

Im out of town for the Python meetup in Cambridge, but will submit to the InterSystems Python Programming Contest starting in September.

How to include IRIS Data into your Google Big Query Data Warehouse and in your Data Studio data explorations.  In this article we will be using Google Cloud Dataflow to connect to our InterSystems Cloud SQL Service  and build a job to persist the results of an IRIS query in Big Query on an interval.  If you were lucky enough to get access to Cloud SQL at Global Summit 2022 as mentioned in "InterSystems IRIS: What's New, What's Next", it makes the example a snap, but you can pull this off with any publicly or vpc accessible listener you have provisioned instead.

Prerequ

Hi,

This is Jayanth from OAK Technologies.

Hope you are all doing well!!

We have a position for InterSystems IRIS Technology Role for our client if anyone is interested, please drop your resume to jayanth@oaktechinc.com

Job Role: IRIS technology role

Location: Chicago, Illinois (Remote Work)

Contract:1+ Year W2 OR 1099 Contact 

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.

Ill start with a short video tour of the production, the MFT Connections, and the Oauth2 app configuration for Box and Dropbox on IRIS, and follow up with some step by steppers to get you going with

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®).

We are also a high performing, full stack team, and like to keep our operational resources on task, so managing the underlying infrastructure to host the FHIR® data repository for purposes of ingestion and consumption is not in the cards for us.

Put the InterSystems FHIR Server to work at the HL7 FHIR Connectathon in Baltimore last weekend, posting bundles, getting all RESTy with resources, and interrogating the Vulcan Implementation Guide. We straddled the Real World Data (RWD) and Schedule of Activity (SoA) projects for Vulcan IG folks moving the ball forward connecting clinical research and healthcare data. We employed a pretty decent approach to meet the requirements,

Myself along with InterSystems peeps (Huy, Russell, Regilo), were on the hook to support the FHIR Server and data appropriation for the event, if you have ever

Wanted to have a FHIR Story in the back pocket to share with the participants on a dead simple series of calls against the FHIR Server for anybody in the mindset of emitting metrics from a device to FHIR.
 

Presentation:
https://docs.google.com/presentation/d/1AY8_P7qEZe5b_3DVJGqWnVlBbNubQdk…
Postman Collection:

https://www.postman.com/brighstreetgroup/workspace/mit-grand-hack-2022/…

Want a commercial grade FHIR® Implementation included in your micro service ecosystem and barely have enough time to fill out your Health plan elections?

Here is a quick way to invite the InterSystems® FHIR®Accelerator Service to your Kubernetes Microservice party for immediate use. The solution uses Nginx proxy ninja moves to get the job done. Though rustic and bound to create some technical arguments, I am pretty happy with the results until this community tells me otherwise, so FHIR® away as they say but it would be great if you heard me out first.

Disclaimer

You will see secrets in

Deploying InterSystems HealthShare code, supporting lookups and artifacts like ssl certs, keys etc is relatively straight forward using Gitlab Runners.  Not only does this approach enable managing the code base and deploying with git type workflows, but it also lends to a speedy recovery and repeatable environments for some implementations.

For those of you with HealthShare specific experience, I think we could agree that is an oversimplification of the process with all the moving actors of a HealthShare implementation, but this does provide some insight on how to get things deployed with a

Hello Newman

So given the STAR method on how to introduce Newman with this effort, here it goes.

SITUATION

We are facing a Production implementation of a FHIRIS® Resource Server, fronted with a robust API Manager, Web Gateways for speed and availability, though not entirely relevant, the implementation is on Public Cloud, namely, Amazon

If you are looking for a slick way to integrate your IRIS solution in the Amazon Web Services ecosystem, server less application, or boto3 powered python script, using the IRIS Python Native API could be the way to go. You don't have to build out to far with a production implementation until you'll need to reach out and get something or set something in IRIS to make your application do its awesome sauce, so hopefully you will find value in this article and build something that matters or doesn't matter at all to anybody else but you as that is equally important.

Loading your IRIS Data to your Google Cloud Big Query Data Warehouse and keeping it current can be a hassle with bulky Commercial Third Party Off The Shelf ETL platforms, but made dead simple using the iris2bq utility.

Let's say IRIS is contributing to workload for a Hospital system, routing DICOM images, ingesting HL7 messages,  posting FHIR resources, or pushing CCDA's to next provider in a transition of care.  Natively, IRIS persists these objects in various stages of the pipeline via the nature of the business processes and anything you included along the way.  Lets send that up to Google Big Query to augment and compliment the rest of our Data Warehouse data and ETL (Extract Transform Load) or ELT (Extract Load Transform) to our hearts desire.

A reference architecture diagram may be worth a thousand words, but 3 bullet points may work out a little bit better:

• It exports the data from IRIS into DataFrames
• It saves them into GCS as .avro to keep the schema along the data: this will avoid to specify/create the BigQuery table schema beforehands.
• It starts BigQuery jobs to import those .avro into the respective BigQuery tables you specify.

 For Global Summit 2016, I set out to showcase a Reference Architecture I had been working on for a National Provider Directory solution with State Level Instances and a National Instance all running HealthShare Provider Directory and all running on AWS Infrastructure.

In short, I wanted to highlight:

• The implementation of Amazon Web Services to provision the infrastructure, including the auto-creation of the state level instances through Cloud Formation.
• The use of the HSPD Broadcast functionality to Notify Upstream Systems Changes in Master Provider Data.
• The implementation of a transformation of the standard Broadcast Object to HL7 MFN for interoperability.
• The principals of Master Data Management applied to the Provider Directory.