By Tom Sullivan, Healthcare IT News | February 14, 2018

Once the specification gains wider use for data exchange, it will open the doors for more advanced uses of data, including artificial intelligence and machine learning, IBM, Google and Microsoft executives said at HIMSS19.

ORLANDO — HL7’s FHIR (Fast Healthcare Interoperability Resources) is largely seen as an enabler of health data exchange, which of course it is, but executives at IBM, Google and Microsoft said it will also lay the foundation for artificial intelligence and machine learning.

“Interoperability is the cornerstone of our healthcare strategy — teaching cloud to speak the language of healthcare: HL7, FHIR, DICOM,” said Aashima Gupta, global head of healthcare and life sciences at Google Cloud, during a panel discussion here at HIMSS19 on Thursday.

Google, in addition to IBM, Microsoft, Oracle and Salesforce, signed a pledge to remove interoperability barriers back in August 2018 during the Blue Button 2.0 hackathon at the White House. And while the companies have yet to provide specific details they said it will involve cloud computing, FHIR and open APIs.

“We’re competitors in many ways but also very much aligned because without interoperability we can’t really make a change and make a difference,” said Mark Dudman, health of global product and AI development at IBM. “Right now, FHIR is taking systems that don’t interact to talk quickly. We’ve hit that first real target of getting systems to talk, but now we have to talk in volume.”

As that interoperability advances and healthcare systems begin sharing those volumes of data more regularly, it sets the stage for many of today’s biggest trends, including population health, personalized medicine, and emerging technologies such as artificial intelligence and machine learning.

“When we see modern data standards like FHIR emerge, it’s obvious this is a part of the democratization of AI,” said Peter Lee, Microsoft corporate vice president of research. “AI is still very artisanal. It depends on the craftsmanship of highly specialized people.”

The broader goal is not just making data available to PhD’s and data scientists but to build tools that democratize AI, which requires interoperable data as a foundational element.

“FHIR is the gateway to AI and machine learning,” Gupta said. “We want to to have FHIR in our analytics and machine learning tools.”

Twitter: @SullyHIT
Email the writer: tom.sullivan@himssmedia.com