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.

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.

Table of Contents

1. Hello Newman
   • Situation
   • Task
   • Action
   • Result
2. Built With
3. Getting Started

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.