Microsoft unveils FHIR Server for Azure to advance interoperability, machine learning

New service comes shortly after the software giant aligned with Amazon, IBM, Google, Oracle and Salesforce to remove interoperability barriers.
By Diana Manos
11:31 AM

Microsoft this week announced the release of its open source FHIR Server for the Azure cloud.

Available on GitHub, Microsoft said it is “contributing this open source project to make it easier for all organizations working with healthcare data to leverage the power of the cloud for clinical data processing and machine learning workloads,” in a blog post by Heather Jordan Cartwright, general manager of Microsoft Healthcare.

Cartwright said that FHIR Server for Azure will be the first in a growing set of FHIR services.

WHY IT MATTERS

FHIR is gaining support in the healthcare community as the next generation standards framework for interoperability.

According to Microsoft, its new FHIR Server will provide immediate support infrastructure for working on the cloud, including the ability to map to the Azure Active Directory (Azure AD) and the ability to enable role-based access controls (RBAC).

THE BIGGER TREND

In August 2018, Microsoft joined with Amazon, Google, IBM, and other companies in a commitment to remove barriers for the adoption of technologies that support healthcare interoperability, particularly those that are enabled through the cloud and AI.

Supporting the FHIR standard and investing in open source with the new Azure service is core to that commitment.

ON THE RECORD

Microsoft’s Cartwright wrote: “Building on the shared experience of healthcare standards communities, FHIR offers an extensible data model and a REST API to simplify the implementation and interoperability of health data. We want to make it easier and more secure for organizations working with healthcare data. We’re starting with FHIR Server for Azure, and we plan to enable a broad set of core services in the Microsoft Cloud to support healthcare interoperability standards like FHIR.”

Focus on Artificial Intelligence

In November, we take a deep dive into AI and machine learning.

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