#FHIR

Hello again everyone.

In our previous article we saw how to configure our EMPI to receive FHIR messages. To do this we installed the FHIR Adapter that InterSystems made available to us that configured a REST endpoint to which we could send our FHIR message. We would then get the message and transform it to a %String that we would send via TCP to the output of our EMPI configured in our HSPIDATA namespace.

Alright, it's time to see how we retrieve the message, transform it back to a %DynamicObject and parse it to the class used by the EMPI to store the information.

As said in the previous article about the iris-fhir-generative-ai experiment, the project logs all events for analysis. Here we are going to discuss two types of analysis covered by analytics embedded in the project:

Description

With InterSystems IRIS FHIR Server you can build a Strategy to customize the behavior of the server (see documentation for more details).

This repository contains a Python Strategy that can be used as a starting point to build your own Strategy in python.

This demo strategy provides the following features:

• Update the capability statement to remove the Account resource
• Simulate a consent management system to allow or not access to the Observation resource
  • If the User has sufficient rights, the Observation resource is returned
  • Otherwise, the Observation resource is not returned

Problem

In a fast-paced clinical environment, where quick decision-making is crucial, the lack of streamlined document storage and access systems poses several obstacles. While storage solutions for documents exist (e.g, FHIR), accessing and effectively searching for specific patient data within those documents meaningfully can be a significant challenge.