Google LLC today announced the launch of Google Cloud’s private preview of Healthcare Data Engine, an end-to-end cloud solution for healthcare and life sciences organizations aimed at enabling advanced interoperability for health records.

The objective of the Healthcare Data Engine is to harmonize data from multiple sources – including medical records, claims, clinical trials and research data – allowing operational leaders, doctors, researchers, and clinicians to gain real-time holistic views of records at a glance.

“As we are keenly aware stemming from the pandemic, access to the right information at the right time is critical to save lives,” said Joe Corkery M.D., director of product management at Google Cloud.

The Healthcare Data Engine builds on the existing Google Cloud Healthcare API core functions and is designed to provide insights based on the Fast Healthcare Interoperability Resources standard. FHIR is an electronic record format designed for interoperability.

Every time a patient sees a doctor, a technician or a specialist a medical record is produced – for example, intake notes, X-rays and test results – and all of these can get put into into different systems. If these systems cannot talk to each other effectively, those records cannot be used for diagnosis down the road, or doctors may need to duplicate them across systems at the point of entry.

Google Cloud recently commissioned a survey with The Harris Poll and nearly nine in 10 physicians agreed that data interoperability should be a priority in healthcare right now. Most believed that it would lead to more accurate diagnosis, since it would provide them more complete patient records and allow them to give more personalized patient care.

“We built the Healthcare Data Engine to make it easier for healthcare and life sciences organizations to bring together their data silos to innovate and improve health outcomes,” said Corkery.

Healthcare Data Engine also delivers the power of BigQuery analytics and artificial intelligence to process extremely large datasets of patient data in order to help improve overall population health. For example, Google Cloud provides, for free, several large datasets of population health data on BigQuery that healthcare organizations can combine with their own datasets that can be used to create predictive models to prioritize patients for follow-up.

Delivering insights for Mayo Clinic and other customers

Google Cloud worked extensively with Mayo Clinic on ingesting electronic records and converting them into the FHIR standard. This automation led to processes that could do in an hour what would originally take weeks, and, with the interoperability standard embedded in the Healthcare Data Engine, opened up even more opportunities.

“We were hitting a wall with our ability to innovate on-prem,” said Jim Buntrock, vice-chair of information technology at Mayo Clinic. “By moving to the cloud we’re able to build tools more easily, at scale, in a way that takes advantage of technological advancements in security and privacy to remain at the forefront in data protection.”

One application Mayo built included a heads-up display for the intensive care unit that would assist teams to direct attention where it was needed. The establishment also worked on a mobile app for patients to interact with doctors and nurses, providing a bridge for remote care after they leave the hospital. “We’re working alongside Google Cloud to build a platform for healthcare transformation,” said Buntrock.

The private preview of Healthcare Data Engine will be available through private partners Deloitte, Maven Wave, Quantiphi Inc. and SADA Inc., which will be ready to assist with deployment. Additionally, independent software vendor partners such as Mathematica are launching their own applications integrated with the data engine.

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