AI in Skilled Nursing Facilities Isn’t Just About Robots

Ask any forward-looking senior care expert about what the industry will look like in 30 years, and robots will likely emerge as an answer. Once artificial intelligence (AI) technology advances far enough, the logic goes, the skilled nursing industry could hypothetically solve its persistent staffing problems with cyborg assistants — a solution that’s already gained some moderate traction in Japan.

But equating AI with health care’s long-off future might cause some skilled nursing operators to ignore the feasible opportunities that exist today, even in a landscape of shrinking reimbursements and other competitive pressures.

“AI doesn’t need to be robotic in nature,” Sarah Thomas, senior director of global innovations at Genesis Rehabilitation Services, said during a panel at the recent National Investment Center for Seniors Housing & Care (NIC) Spring Investment Forum in Dallas.

Instead, according to Thomas, AI can be as simple as software that performs data analytics on self-reported patient information and remotely monitored biometrics. Even a small step like that can go a long way in the skilled nursing world, which is somewhat notorious for being farther behind the technological curve than their fellow companies on the long-term care continuum.

“I’m still in buildings where they’re [using] paper charts, and I’m just shocked,” Thomas said. “And then they wonder why census is low.”

Archaic health records are one reason some facilities could see themselves passed over by large health networks, Medicare Advantage plans, and accountable care organizations (ACOs) — all of which are under intense pressure to reduce spending through tighter care coordination.

Don’t just wait for vendors

At this point, those operators that have waited to upgrade their systems should just pick up the phone and call a competitor that’s had success, Thomas said.

“We’re all willing to discuss what’s working and what’s not working,” she said. “We’re always on the phone with each other, even if we’re in a competitive landscape.”

It’s also incumbent on providers to think proactively about the problems that software, artificial intelligence, and better reporting can solve — and wait for the makers of those solutions to develop new programs.

“Gone is the day when we should be having a vendor-driven model,” Thomas said, adding that it’s up to employees across disciplines in communities to identify their pain points. “We shouldn’t just have people knocking on our doors to tell us what we need.”

And the possibilities — and limitations — of AI technology in the skilled nursing setting expand beyond physical robots that can assist residents. Asif Khan, founder and chairman of the Chicago-based senior living software company Caremerge, divided AI capabilities into three categories: descriptive, predictive, and prescriptive.

Simply reporting information isn’t AI, Khan said: The real advancement comes when users can visualize the data in a descriptive way, in which the numbers tell a story.

“The next step is to be predictive. So now you’re visualizing data: How do you use that to predict the future?” he said.

The third step, “prescriptive,” involves AI using the data to both predict the future and suggest possible courses of action for treatment — all with a goal of the AI technology becoming a kind of omniscient care coordinator for a wide variety of settings.

“A key player will become AI that augments the staff and the workers, that keeps track of individual patients irrespective of where you are,” Khan said.

Written by Alex Spanko

Alex Spanko on Twitter
Alex Spanko
Alex covers the long-term health care industry for Aging Media Network, with a specific interest in the intersection of finance and policy. Outside of work, he reads nonfiction, experiments in the kitchen, enjoys pretty much any type of whiskey or scotch, and yells at Mets games — often all at the same time.

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