Managing information policy compliance to prevent fraud

Our company has done some work associated with understanding and preventing health care fraud. We’ve been consulting with one client on a master data management program that focuses on provider data and how characteristics of providers and relationships among them can be leveraged to ultimately look for fraud patterns. In another situation, we worked with the client to understand the types of real-time fraud analytics algorithms and applications that can be integrated into an investigation workbench that helps analysts quickly assess potential fraud scenarios.

The estimates of the costs of health care fraud range from a conservative $68 billion to as high as $230 billion (and possibly more). Health care fraud prevention is a sticky topic, though, as it must strike a balance between two diametrically opposed outcomes.

The first is the desire to streamline claims submission and payment processing so providers will be paid promptly, which encourages their ongoing participation in the health care network. The second is the need to continuously screen and filter claims to find potentially suspicious submissions and prevent payment of fraudulent claims. If you are too ambitious in ensuring prompt payment, you may be limited in how much screening can be done, since the time to screen will impact fast payment. Alternatively, the more you screen, the better chance you have of finding and preventing payments to those committing fraud.