Tune in Thursday, June 11 at 2:00 PM EDT

Federal healthcare systems are under increasing pressure to do more than deliver care. They are also responsible for managing risk at an enormous scale. Billions of dollars are lost each year to fraud, waste and abuse, yet in many cases, the cost of investigating and recovering improper payments exceeds the value of the claims themselves. This has led to a persistent “pay and chase” model, where questionable claims are paid first and only reviewed later, if at all. With increased scrutiny from oversight bodies and initiatives like the Task Force to Eliminate Fraud, agencies are under pressure to rethink this approach. The challenge moved beyond simply identifying fraud to doing so early enough, and efficiently enough, to make intervention worthwhile.

In this webcast, we’ll explore how federal healthcare leaders are shifting fraud detection closer to the point of payment by rethinking data architectures and distributing decision-making. We’ll discuss how AI and edge computing can help agencies move from retrospective review to real-time risk assessment, reducing improper payments while lowering the cost of enforcement. The conversation will focus on how bringing intelligence to where decisions are made can strengthen program integrity without slowing down care delivery.