Analytics Fuel the Business of Enforcement
The value of analytics is often discussed in connection with improving business but it has also been used to improve fraud enforcement and prevention as well. The Centers for Medicare and Medicaid Services (CMS) announced this month that its Fraud Prevention System (FPS), an "advanced analytics system," has uncovered $820 million in inappropriate payments. The FPS was established in the Small Business Jobs Act of 2010 to use "predictive modeling and other analytics technologies to find and avoid payment of improper Medicare claims." Using analytics in much the same way credit card companies do, the system finds "troublesome billing patterns and outlier claims." CMS indicated in a press release that it intends to use the system not just to identify and prosecute fraud but also to ferret out potential payment issues that are not necessarily the result of illegal intentions but could be "better served by education or data transparency interventions." "We are proving that in a modern health care system you can both fight fraud and avoid creating hassles for the vast majority of physicians who simply want to get paid for services rendered. The key is data," Acting CMS Administrator Andy Slavitt said in a press release. Referring […]
The value of analytics is often discussed in connection with improving business but it has also been used to improve fraud enforcement and prevention as well. The Centers for Medicare and Medicaid Services (CMS) announced this month that its Fraud Prevention System (FPS), an "advanced analytics system," has uncovered $820 million in inappropriate payments. The FPS was established in the Small Business Jobs Act of 2010 to use "predictive modeling and other analytics technologies to find and avoid payment of improper Medicare claims." Using analytics in much the same way credit card companies do, the system finds "troublesome billing patterns and outlier claims." CMS indicated in a press release that it intends to use the system not just to identify and prosecute fraud but also to ferret out potential payment issues that are not necessarily the result of illegal intentions but could be "better served by education or data transparency interventions."
"We are proving that in a modern health care system you can both fight fraud and avoid creating hassles for the vast majority of physicians who simply want to get paid for services rendered. The key is data," Acting CMS Administrator Andy Slavitt said in a press release. Referring to the system's identification in 2014 of $454 million in improper payments, Slavitt declared: "Very few investments have a 10:1 return on taxpayer money."
CMS explained that the analytics help spot potentially improper billing patterns and use information about past billing practices to find fraud. These "predictive models" helped CMS identify questionable payments to a podiatrist and an ambulance provider, for example. CMS Deputy Administrator and Director of the Center for Program Integrity Dr. Shantanu Agrawal emphasized the system's ability to facilitate a more proactive approach to fighting fraud: "The third year results of the Fraud Prevention System demonstrate our commitment to high-yield prevention activities, and our progress in moving beyond the 'pay and chase' model."
The Department of Health and Human Services Office of Inspector General was charged with certifying the savings achieved under the system and determining the return on investment. An OIG report released this month reviewed whether HHS properly reported savings from the use of analytics and whether use of the FPS should be continued, expanded or changed. That report indicates the system yielded more than $133 million in adjusted actual and projected savings for Medicare—$85 million from FPS-initiated administrative actions and $47 million from administrative actions in which an FPS lead "contributed to the existing investigation." Adjusted saving is the amount of identified savings that can actually be achieved. Administrative actions include payment suspension, referral to law enforcement, overpayment recovery, prepayment edits, automatic denials or rejections and even revocation of Medicare billing privileges. The OIG calculated a $2.84 return on investment for each dollar spent.
The OIG's 2015 report on the third year of the system's operation concluded that use of FPS does "enhance[] and should continue to enhance its efforts to prevent fraud, waste and abuse in the Medicare Fee-for-Service program" and it achieved a positive return on investment. However, the report indicates that HHS didn't find it "cost-effective and feasible, at this time" to expand use of predictive analytics in all 50 states "because of policy differences among programs," information technology readiness, resources, and data availability. The OIG also recommended that Medicare contractors be better informed about how to attribute FPS savings and document the impact of FPS leads on administrative actions.
Takeaway: New technologies and use of data benefit not only medical treatment and decisionmaking but detection and prevention of improper billing as well.
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