How AI can help payers navigate a coming wave of delayed and deferred care

So far insurers have seen healthcare use plummet since the onset of the COVID-19 pandemic.

But experts are concerned about a wave of deferred care that could hit as patients start to return to patients and hospitals — putting insurers on the hook for an unexpected surge of healthcare spending.

Artificial intelligence and machine learning could lend insurers a hand.

“We are using the AI approaches to try to protect future cost bubbles,” said Colt Courtright, chief data and analytics officer at Premera Blue Cross, during a session with Fierce AI Week on Wednesday.

WATCH THE ON-DEMAND PLAYBACK: What Payers Should Know About How AI Can Change Their Business

He noted that people are not going in and getting even routine cancer screenings.

“If people have delay in diagnostics and delay in medical care how is that going to play out in the future when we think about those individuals and the need for clinical programs and the cost and how do we manage that?” he said.

Insurers have started in some ways to incorporate AI and machine learning in several different facets such as claims management and customer service, but insurers are also starting to explore how AI can be used to predict healthcare costs and outcomes.

In some ways, the pandemic has accelerated the use of AI and digital technologies in general.

“If we can predict, forecast and personalize care virtually, then why not do that,” said Rajeev Ronanki, senior vice president and chief digital officer for Anthem, during the session.

The pandemic has led to a boom in virtual telemedicine as the Trump administration has increased flexibility for getting Medicare payments for telehealth and patients have been scared to go to hospitals and physician offices.

But Ronanki said that AI can’t just help with predicting healthcare costs, but also on fixing supply chains wracked by the pandemic.

He noted that the manufacturing global supply chain is extremely optimized, especially with just-in-time ordering that doesn’t require businesses to have a large amount of inventory.

But that method doesn’t really work during a pandemic when there is a “vast imbalance in supply and demand” with personal protective equipment, said Ronanki.

“When you connect all those dots, AI can then be used to configure supply and demand better in anticipation of issues like this,” he said.