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Can Google's Cloud API Solve Healthcare's Disparate Data Problem?


The company’s track record and finances suggest it could deliver, but there’s a paucity of additional evidence.

Google Cloud API

On Monday, Google announced the launch of their new Cloud Application Programming Interface (API), and shared the lofty goal that they said it could help address — organizing the world’s healthcare and life sciences data, and making it accessible, secure, and useful.

As it stands, that’s one of the biggest problems in healthcare. Data continues to pile up all over, and there’s a lack of procedures in place to help hospital systems, their workforces, and their patients make any sense of it. On top of that, there’s a tremendous amount of noise. New startups emerge every day, promising to hold the panacea for interoperability, data and analytics woes. As more players enter the game, it’s increasingly difficult to weed the snake oil peddlers from those who’ve got the right stuff.

It was only a matter of time before Google—the undisputed king of search, whose throne sits atop a superlative heap of data—was sufficiently tantalized by the enormous opportunity in healthcare (and glaring lack of solutions) to toss their hat in the ring. Their new Cloud API’s goal, as stated above, is only a few words removed from the company’s official mission statement: “To organize the world's information and make it universally accessible and useful.” They’ve delivered upon the latter, but can Google repeat its success in the world of health IT?

That’s yet to be seen. At a presentation at HIMSS 2018, Greg Moore, MD, PhD, vice president of healthcare for Google Cloud, spoke broadly about Cloud API’s potential to “provide machine learning for all,” “bring power to you without having a team of software engineers and data scientists,” and “facilitate workflows.”

The company’s track record and finances suggest it may deliver on those concepts. In fact, it may have already started. Moore pointed to Cloud API’s role in a recent JAMA study, where it successfully leveraged AI to scan medical images and positively identify cases of diabetic retinopathy, to illustrate that its real-world implementation can be a success.

But there’s a paucity of additional evidence to support the notion that Google’s Cloud API will mark the end of the dark ages for interoperability, analytics, artificial intelligence (AI), and machine learning in healthcare. As one analyst said at an earlier HIMSS presentation, “I never understood until I came into healthcare that the industry has the most complicated IT out there, hands down.” Tens of thousands of solution-seeking conference attendees would likely agree.

Following Moore’s overview of Cloud API’s potential, he gave the stage to Will Morris, MD, of the Cleveland Clinic’s IT department, who highlighted the need for cross-industry collaboration across the healthcare spectrum to figure out healthcare interoperability, and urged stakeholders to look outside the box for solutions.

The disparate data problem “isn’t going to be solved by the Cleveland Clinic. It’s not going to be solved by Google. It’s going to be solved by an ecosystem collectively,” Morris said. “We should steal, borrow and share shamelessly, especially with non-traditional health IT folks.”

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