Amazon Web Services exec Partovi on where the biggest AI opportunities are in healthcare

machine learning in healthcare
Shez Partovi, M.D., says Amazon Web Services' computing power will enable "game-changing" predictive analytics and precision health. (monsitj/Getty Images)

NEW YORK CITY—Back when Shez Partovi, M.D., was chief digital officer at health system Dignity Health—a California nonprofit system that combined with Catholic Health Initiatives earlier this year to form CommonSpirit Health—his main focus was figuring out how to use technology to create a smoother experience for both patients and physicians.

It's a problem health systems are notoriously bad at, he said.

“If you’ve ever had to log into a healthcare organization’s website and give all your health insurance information, it’s an arduous process and full of friction,” Partovi told FierceHealthcare. A physician and neuroradiologist by training, Partovi said he developed a passion for removing that friction and went on to launch several health IT companies.

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When Amazon Web Services (AWS) came knocking last year, he saw an opportunity to combine his clinical, entrepreneurial and digital experience, he said. "It was an opportunity that I had to jump on,” he said.

Shez Partovi (AWS)

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Since November, Partovi has been leading AWS' healthcare and life sciences division as worldwide director of business development. He works with healthcare organizations to use cloud computing, artificial intelligence and machine learning to improve clinical and operational processes. Partovi spoke with FierceHealthcare during the recent AWS Summit in New York City about the future of cloud computing in healthcare, the potential of AI and machine learning and where he thinks AWS can make the biggest impact in healthcare.

FierceHealthcare: Cloud technology is shifting from simple data storage to cloud infrastructure. What is the future impact of cloud computing in healthcare?

Shez Partovi: On the patient side, the value that cloud brings is that you can do predictive modeling. By applying machine learning and predictive modeling to data, it allows you to predict patient health events.

In a research project, AWS and Cerner looked at 210,000 individuals and were able to predict congestive heart failure 15 months before it set in. I see a future state where health records are sitting in the cloud and predictive modeling is applied where healthcare providers and care teams can anticipate things and intervene, rather than just looking in the rearview mirror. That is an incredible tipping point for individuals. I think that will be game-changing.

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From the physician's side, there’s a lot of news out there about physician frustration and burnout. The real challenge for them is to have the right information at the right time to care for the right patient. Interoperability and data liquidity, getting the right information to the provider, is something that our customers are asking us to help them do. As an example, Orion, a health information exchange company, uses AWS technology to connect payers so they can exchange and share data to improve the care management of patients.

FH: Where do you see the biggest opportunities for AI in healthcare?

SP: One area is clinical forecasting. There’s also operational forecasting and we’re seeing healthcare organizations wanting to, along with predicting a patient event, optimize their operations.

As one example, take a patient who is scheduled for surgery and is admitted the night before. While the patient is in the pre-op waiting room, he or she is told that the surgery has to be rescheduled. Could we have predicted that the patient might have to be rescheduled? Beth Israel Deaconess Medical Center is using AI and machine learning to predict which patients are likely to get their surgeries rescheduled or canceled to improve the patient experience and operations. Using AI and machine learning to predict patient no-shows for clinic appointments can have a huge impact on operations as well.

FH: You've mentioned that AWS wants to take on healthcare's "undifferentiated heavy lifting." Can you give an example of how your company is doing that?

SP: The majority of health and patient data is stored today as unstructured medical text and identifying this information is a manual and time-consuming process. At Fred Hutchinson Cancer Research Center, they are using Amazon Comprehend Medical to help identify patients for clinical trials who may benefit from specific cancer therapies. They used to do that manually, review the charts and try to match it to the protocol eligibility. They have now automated the process, reducing the time to process each document from hours to seconds. 

FH: Where do you see AWS having the biggest impact on healthcare?

SP: Health systems want to do away with the undifferentiated heavy lifting. The core mission is to deliver care, not to build data centers. There is an overarching opportunity for health systems to dispense with things they shouldn’t be doing and focus on the things that they want to be doing.

The other opportunity that we’re seeing a lot of people talk about is precision health, specifically precision diagnostics and precision therapeutics. To precisely treat the individual patient, you need to know exactly their condition at a genomic level and the exact match of medication. Companies like Grail are taking DNA fragments from the blood and analyzing for earlier identification and screening for several different cancers. They are doing that work on AWS.

That same computing power is helping the pharmaceutical industry go from blockbuster drug design to unique and tailored drug design. The greatest potential to elevate the human condition is AWS's ability to support precision diagnostics and precision therapeutics. That’s where I’d love to see AWS make its mark.

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