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42 U.S. Code § 1320a-7m. Use of predictive modeling and other analytics technologies to identify and prevent waste, fraud, and abuse in the Medicare fee-for-service program
(a) Use in the Medicare fee-for-service program
The Secretary shall use predictive modeling and other analytics technologies (in this section referred to as “predictive analytics technologies”) to identify improper claims for reimbursement and to prevent the payment of such claims under the Medicare fee-for-service program.
(b) Predictive analytics technologies requirementsThe predictive analytics technologies used by the Secretary shall—
(1) capture Medicare provider and Medicare beneficiary activities across the Medicare fee-for-service program to provide a comprehensive view across all providers, beneficiaries, and geographies within such program in order to—
(A)
identify and analyze Medicare provider networks, provider billing patterns, and beneficiary utilization patterns; and
(B)
identify and detect any such patterns and networks that represent a high risk of fraudulent activity;
(2)
be integrated into the existing Medicare fee-for-service program claims flow with minimal effort and maximum efficiency;
(3) be able to—
(A)
analyze large data sets for unusual or suspicious patterns or anomalies or contain other factors that are linked to the occurrence of waste, fraud, or abuse;
(B)
undertake such analysis before payment is made; and
(C)
prioritize such identified transactions for additional review before payment is made in terms of the likelihood of potential waste, fraud, and abuse to more efficiently utilize investigative resources;
(4)
capture outcome information on adjudicated claims for reimbursement to allow for refinement and enhancement of the predictive analytics technologies on the basis of such outcome information, including post-payment information about the eventual status of a claim; and
(5)
prevent the payment of claims for reimbursement that have been identified as potentially wasteful, fraudulent, or abusive until such time as the claims have been verified as valid.