The future is on FHIR for SAS and Microsoft Azure

Microsoft

Written by Trent Norris, HLS Cloud and Data Partner Alliances

 

This blog has been co-authored by Steve Kearney, PharmD, Global Medical Director, SAS.

 

This blog is part of a series in collaboration with our partners and customers leveraging the newly announced Azure Health Data Services. Azure Health Data Services, a platform as a service (PaaS) offering designed to support Protected Health Information (PHI) in the cloud, is a new way of working with unified data—providing care teams with a platform to support both transactional and analytical workloads from the same data store and enabling cloud computing to transform how we develop and deliver AI across the healthcare ecosystem.

 

There is a dichotomy in health care technology. Despite new developments in imaging, diagnostics, treatment, and surgical techniques, the lack of data standardization in the industry has trapped health insights in functional silos. Providers and payers alike struggle to manually reconcile incompatible file formats, which slows the transfer of information and negatively impacts quality care and patient experience.

 

Microsoft, along with partners such as global analytics software company SAS, are driving towards increased interoperability through enabling the use of standards such as Fast Healthcare Interoperability Resources (FHIR®). Together, SAS and Microsoft Azure are building deep technology integrations that unlock value by making disparate data and advanced analytics more accessible to health and life science organizations. With new capabilities such as the integration from Azure Health Data Services to SAS on Azure, the embedded AI capabilities of SAS Health are more efficient and secure, expanding the possibilities of patient-centric innovation and trusted collaboration across the health landscape.

 

FHIR puts the patient at the center of the health care ecosystem. When querying information in the previous HL7 format, the query is answered with the entire patient dataset that must be parsed to find the information desired for predictive modeling. Additionally, data would require harmonization within and across the organization, creating limitations on available data. In contrast, harmonized FHIR datasets persisting on Azure Health Data Services enable FHIR-based requests directed to the specific data points required, speeding up queries to near-real-time and protecting patient data.

 

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