- Healthcare fraud, waste, and abuse (FWA) investigators have a tough job. Keeping pace with the latest schemes, continuously weeding through hundreds of false-positive leads, and understanding the right time to pursue a case are just a few of the challenges a health plan’s special investigative unit (SIU) face. When armed with the right information to immediately open a solid case, SIUs can quickly take intelligent action to educate providers, recover funds, or even prevent payment before it is made.
The path from lead to allegation
A turnkey allegation is a ready-to-investigate case referral to a health plan SIU that has been vetted by a team of expert investigative analysts. Instead of simply handing over a list of leads generated from an analytics engine, the investigative team does the legwork of gathering sufficient evidence to determine which cases are worth pursuing so that a health plan’s SIU can open a case with confidence and immediately take action. Imagine there are a total of 10 steps in an FWA case. The investigative team takes the first four or five steps, which are where most of the false-positive leads are uncovered. The idea is to reduce the time and effort a plan puts into researching false-positive leads, thereby increasing their success rate.
Technology helps shorten the path from an allegation to an open case by giving a payer a thorough summary of the allegation along with quick access to the supporting data, providing that which previously had to be acquired from other departments or outside sources. When SIUs are armed with the right information and are able to immediately open a case, they can quickly take action.
Building a turnkey allegation
Preventing healthcare FWA starts with the three Vs of data: variety, volume, and velocity. These characteristics, when incorporated into making complex decision models, increase the likelihood of identifying unusual behavior patterns.
The right data fueling the right analytic models, however, will still only yield interesting flags or alerts of potential FWA. The next, and perhaps most important, piece is evaluation of those alerts by intuitive and trained experts. The strongest mix of experts includes certified coders, registered nurses, and accredited healthcare fraud investigators. Based on their roles, these experts have their own take on what data points are necessary for an investigation. Their collective input covers more scenarios for more complete models. They comb through all of the details surrounding the claims and providers delivered through the analytics, validating a complete allegation.
Lastly, allegation experts couldn’t effectively and efficiently evaluate potential FWA leads without a production tool that provides data visualization and quick access to all of the data involved in the potential referral. Together, all of these components help create a turnkey allegation.
Why patterns are key
It is equally important that plans avoid false positives and wasted investigative efforts on claims that might appear to be fraudulent, wasteful, or abusive, but which, upon further examination, turn out to be legitimate (or explainable). For example, a provider may be highly specialized in their field. A review of available data — such as patient diagnoses and claims history — could reveal that all of the provider’s patients have needs beyond what would normally be expected for the provider’s stated specialty. In this case, an investigative team wouldn’t be interested in pursuing this provider as a review of the data supports the validity of the claims.
On the contrary, an example of a popular pattern that would warrant further investigation is a provider who recognizes the thresholds and billing limitations of a specific payer. For example, if a provider is billing Plan A for six hours of work each day, it won’t likely be flagged as suspect behavior. However, if that same provider is also billing Plans B, C, and D for six to eight hours of work each day, we know this is a logistical impossibility and it opens up an opportunity for investigation.
Through the collaborative effort of various plans pooling data, in conjunction with turnkey allegations, FWA investigators can gain the altitude to recognize patterns that a plan, on its own, may not be able to identify.
Shuying Shen, director of data science, works with all Verisk Health’s Payment solutions and has extensive experience with user feedback and advanced analytics that integrate multiple data sources. Tim McBride, product manager of fraud solutions, is an accredited healthcare fraud investigator and certified professional coder, is responsible for identifying opportunities for enhancement of our existing fraud offerings, identifying innovative solutions and condition development. Ryan Cleverly, director of SIU, is responsible for directing Verisk Health’s Fraud and SIU Operations teams.