Can AI make your health insurance better? Posted on : Jun 24 - 2017

Healthcare and Artificial Intelligence (AI) are each very much in the news right now. The United State Senate has released draft legislation for the repeal the Affordable Care Act (aka "Obamacare"), leaving some Americans with trepidation about their coverage. Meanwhile, the phrases "machine learning" (ML) and "artificial intelligence" can inspire concerns of their own.

What if there were a way to combine healthcare coverage with machine learning to try and make delivery of services not just more efficient (which many worry can be code for "less generous") but more proactive as well? Could this cut costs and enhance care? Could it help payers optimize customer care beyond the blunt metric of keeping customer service call durations low?

Healthy tech?

One company thinks so. Accolade, and its Maya Intelligence Engine, which it announced just last week, use ML and AI towards these very ends. While the company has the perhaps ambiguous ambition of delivering the "most personalized healthcare experience," it seems also to be applying both data science and common sense to help insurance companies do a better job of helping their customers.

When I spoke with Mike Hilton, Accolade's Chief Product Officer this week, he explained to me that the conventional model in health care is to target the sickest 5% of its customer population, conduct some outreach to them and maybe do some predictive analytics on what their next course of action should be. Hilton says customers don't tend to like this approach and participation rates for these outreach efforts on the part of the customer is very low.

Beyond the 5%

Accolade's approach is to cast a much wider net, targeting not just the 5% of the customer population in the most acute states of illness, but to include lots of healthy customers as well. Targeting younger members, who may be quite healthy, has merits too -- because those may be the very same members who, for example, bristle at filing claims, or naively use out-of-network providers and are hesitant to call and ask for clarification about a high bill they may receive. View More