Optum Enterprise Analytics Steve Griffiths and Dr. Arthur Forni speak with Business Insider via Skype.
- Optum, the health services arm of America’s largest insurer United Health Group, is trying to make the data it collects smarter using artificial intelligence.
- Using this data, Optum is seeing if it can predict who will develop atrial fibrillation , a heart condition that can lead to strokes.
- “I think that’s where we’re going, to be able to solve some of the most wicked problems in healthcare,” Kerrie Holley, a technical fellow within Optum’s technology, said.
Optum, the $91 billion business within UnitedHealth Group , has its hands on a lot of information , from clinical data to information about healthcare consumers.
The organization on its own has 140,000 employees, who work with 124 million members and 300 health plans.
Now, it’s exploring what it can do with that all information to make people healthier using artificial intelligence, an endeavor titled OptumIQ.
“It’s the coming together of the data, the analytics, and the expertise in the context of all of our businesses,” Steve Griffiths senior vice president and chief operating officer of Optum Enterprise Analytics, told Business Insider. “So we work collectively with each of our business lines to understand the intelligence within various products.”
The idea is that by applying artificial intelligence to the massive amounts of data that comes from all of Optum’s businesses, it can predict when someone might get sick and solve problems healthcare experts can’t on their own.
While that can be an incredibly far-reaching task, Griffiths said the hope is to come up with applications that are actually useful: “AI with an ROI,” is how he puts it.
“We’re not just creating a whole bunch of stuff. It’s innovation with a purpose,” he said.
Much of that focuses on finding ways AI can help doctors when they’re seeing patients. Kerrie Holley, a technical fellow at Optum’s technology unit explained the benefit of AI to medicine as being able to step in and change the course of a particular treatment, as opposed to just observing what will happen.
For example, being able to not just answer “If I take an aspirin, will my headache be cured?” but then answer: “Was it aspirin that stopped my headache?” Getting to the point where Optum can answer that question might take a while, Holley said, though he expects it to happen within the next decade.
“I think that’s where we’re going, to be able to solve some of the most wicked problems in healthcare,” Holley said.
The market for AI in healthcare is expected to grow to $6.6 billion by 2021 . And for a healthcare company like UnitedHealth, catching problems like atrial fibrillation and diabetes earlier could help the company save money later down the line in the form of costlier claims from hospital visits .
Introducing AI to help with diagnosing — and one day potentially treating — patients could be a key element in bringing down the cost of healthcare in America. The US spends about twice as much as other high-income countries on healthcare — approaching 18% of the GDP. And the health outcomes, or how well people fare with their health, are often worse than other countries.
Applying AI to help care for patients hasn’t been entirely as simple as plugging in the technology. For example, i n July, Stat News reported that IBM’s Watson supercomputer had provided “unsafe and incorrect” cancer treatments.
Using AI in the doctor’s office
One of the projects Optum is starting with to see how AI can actually be useful in doctors’ offices revolves around predicting a particular heart condition in patients.
The condition, atrial fibrillation , is a common problem in which people have an irregular heartbeat that’s associated with an increased risk of stroke and heart disease. Because it can happen in episodes , it can be hard to detect in the doctor’s office, Dr. Arthur Forni, an infectious disease doctor at Westchester, New York-based WestMed who’s working with Optum on its trial, told Business Insider.
Using a training set of health insurance claims and clinical data that Optum had, along with five years’ worth of electronic medical record data, the team created a system to predict who might get atrial fibrillation. When looking at data from 1,000 patients, the model was able to detect 70% of the patients who were diagnosed with atrial fibrillation. It’s planning on developing a proactive study to see if the system can predict which patients might develop atrial fibrillation over a few months. Should the AI do a good job of predicting that, doctors could then use that data to keep a closer eye on those patients to keep them healthy.
“This could be a new way of abstracting data and presenting it back to the doctor,” Forni said. But there are some caveats that his team has worried about, such as whether insurance would pay for it and whether patients who are flagged with early signs of the condition will be unnecessarily stressed about the diagnosis.
Ultimately, if that study pans out, Griffiths expects to go beyond atrial fibrillation to use the data Optum collects to predict who might develop some of the most common health conditions like diabetes.
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