Data analytics to prevent fraud

Michigan Blues' Doug Cedras: Customers expect data analytics

By Alicia Caramenico

FierceHealthPayer: What role does data analytics play in BCBSM's healthcare investigations unit?

Doug Cedras: A significant role. We had a solution we used up until early this year, but it was a rules-based solution and it wasn't giving us the leads we anticipated it would. So we converted and looked for an alternative.

With predictive analytics, we want to get us in a position to identify the fraud as early as we can in the cycle. Because if the fraud goes on for a period of time--say it took a year to identify by traditional means--there's a lot of money that's been paid off and the potential to recover that money is frequently very slim.

The main goal, especially in this environment of cost containment, is to protect our customers' money, and also ensure the integrity of our provider communities.

FHP: How do advanced analytics help insurers effectively prevent improper payments?

Cedras: By catching it earlier in the cycle. Sometimes it's difficult because, for example, you may have a group a providers that are all taking advantage of a weakness within the system. Then your baseline seems to be static, but in reality, you have a number people doing bad things.

The analytics will help us identify those situations: How should we address it? Is there a weakness in the system where we need an edit? Is it an educational situation where we have to go out and educate our providers that we don't expect them to bill in this particular way? There's a lot of value that we can get out of predictive analytics.

The other thing is, our customers expect more analytics from us. They want to know how their money is being spent, they want to know the medical conditions they're experiencing within their group so they can make better decisions in terms of what kinds of benefits to buy.