What is most important: identify, eliminate, recover or (PLOT TWIST) prevent?
Coming off of a strong week of meetings with my clients and listening to their real pain points coupled with listening to hours of the podcast Do You Know This Man, and incessant Elizabeth Holmes reading and consumption, I sit on my 6am flight feeling prolific with one cup of strong coffee (read it in my voice, cwahfee) and laptop booted.
We know that the overpayment on healthcare claims costs payers millions of unnecessary dollars per year which makes post-payment claim analysis, data analytics, medical record review and overpayment/recovery solutions a critical component of FWA detection.
Payers use advanced analytics solutions to detect, eliminate, and recover overpayments. Why does this technology work? Red flags help identify and quantify potential errors without delaying the claims process. In order to identify potential fraudulent claims, payers deploy many red flag technologies, including predictive fraud modeling claim scoring. What the payers do after deriving leads from the claim scoring models depends on the payer’s strategies and operations. After high-risk claims are identified, should they go on for further investigation? Larger payers typically use more anti-fraud technology than smaller plans, which rely heavily on the observations and intuitions of claim adjusters and/or tips from the members, or those who are related to the provider.
Beyond advanced analytics, claim scoring, alerts, red flags, and workflow processing to divert high-risk claims to further investigation, other resources are used by the Special Investigations Units of payers to detect fraud patterns. As we talk with our clients, we often hear that the patterns and schemes that are shared in the industry among SIUs and CMS programs are often not useful, whether it is a time factor or because detection and investigation does not drive elimination and prevention, which is where the real money is wasted. Yes, shared data and schemes are helpful, but not when they are too late and the provider is already under investigation. Yes, there is a lot of great sharing in the industry of investigators … BUT, early intervention and lower-risk claims open a bigger real-life gap that is often unaddressed at payers. Why? So glad you asked, because there is already too much to do for the SIU and it might not be worth their time/expense from an ROI perspective or because it might cause too much provider abrasion.
One area that is gaining considerable traction in the FWA world, as part of that advanced analytics suite of fraud prevention and detection, is the shortening of the gap between the submission of a claim and the analysis of the claim for FWA. The “real time” or “near real time” analysis is probably one of the most important parts of any FWA approach. Taking data that is aged (and the definition of aged will depend on with whom you speak), means that the claims have been adjudicated, the fraud gone undeterred, and the money likely gone. One or two-year-old data that is being mined today is of little value. As FWA tools get better at predicting FWA patterns and outliers, so too are the fraudulent providers at masking their schemes. “Real time,” and “nearly real time” are the only ways to work to stem the prevalence of FWA.
Over the years, we have seen SIU teams fight with the provider network folks at their very own company because they are both incentivized and measured based upon the very divergent KPIs. Perhaps if a payer unequivocally set up a “Pay Just Correct Claims” culture, we would see less strife between the differing strategies (finance vs sales). We see this at companies all the time outside of healthcare. Sales team sells something and then finance and/or operations cannot deliver it within the budget sold. Sure, sales wants to land more sales, but finance wants to drive profitability. To the plans, more lives and more members, keeping providers and patients happy. However, this is met with the struggle of keeping them happy, which is costly, and often means paying for things that are not correct. So, what if a payer went from a “fewer dropped calls” (phone company proud models) feel to a bank vibe where no incorrect checks can be cashed? Bank fraud doesn’t happen that often, at least I hope not. What could payers learn from banks? Could we prevent more?
By Jeanmarie Loria