Microsoft launches Azure API for FHIR to share data in cloud
The software giant is continuing its support for HL7’s Fast Healthcare Interoperability Resources standard with the release of a new tool to help health systems interoperate and share data in the cloud.
Microsoft’s Azure API for FHIR offers healthcare data exchange backed by a managed Platform-as-a-Service (PaaS) offering and is intended for customers developing solutions that integrate healthcare data from one or more systems of record, according to the vendor.
“We are thrilled to release this,” said Heather Jordan Cartwright, general manager of Microsoft Healthcare, who notes that the Azure API is the first in a series of tools that are “specifically designed for the management, ingestion, and enrichment” of data in native FHIR resources.
According to Cartwright, the Azure API for FHIR builds on the release in November 2018 of Microsoft Healthcare’s FHIR Server for Azure, an open source project on GitHub that provides support infrastructure for provisioning in the cloud.
The Azure API is currently available in public preview and the company has more than 25 technology partners in its early access program to now help healthcare organizations build FHIR-enabled services.
“Anyone working with health data can go and access it and start to use it,” comments Cartwright. “It allows you to create and deploy a FHIR service in literally just a few minutes in the cloud environment allowing you to start exchanging data in the native FHIR format.”
“Our customers that are using it really just pay for the underlying database usage and data transfer,” she adds.
Microsoft’s initial release of the Azure API supports FHIR Standard for Trial Use (STU) 3. However, a future version of the API will support FHIR Release 4, the normative version of the interoperability standard published by HL7 in January.
“We’re bullish on FHIR,” concludes Cartwright. “In starting to use the cloud in healthcare, we need to have an open source standard that the entire community can rally around and share data.”
She contends that leveraging the open source standard and the power of the cloud will help to apply machine learning at scale in the healthcare industry by “normalizing the data (in FHIR) and getting it into a (common) format.”