CMS Issues Final Rule Authorizing Extrapolation as Part of RADV Audits

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Stoel Rives - Health Law Insider®

As a result of a new rule published on February 1, 2023, at 88 Fed. Reg. 6643, Medicare Advantage (MA) organizations soon will be facing enhanced exposure from Risk Adjustment Data Validation (RADV) audits. Under the new rule, effective for audits of payment years 2018 and after, Centers for Medicare & Medicaid Services (CMS) will use extrapolation to calculate MA organizations’ repayment obligations based on RADV audit findings. While CMS did not adopt any specific extrapolation methodology and plans to use methodologies appropriate to the specific audit, it will be focused on contracts identified as being high-risk for improper payments using statistical modeling, data analytics, or both. CMS does commit to disclosing the extrapolation methodology used in connection with any particular audit so that MA organizations will know how their repayment obligation was calculated. Notwithstanding its prior proposal to do so (https://www.cms.gov/Research-Statistics-Data-and-Systems/Monitoring-Programs/recovery-audit-program-parts-c-and-d/Other-Content-Types/RADV-Docs/RADV-Methodology.pdf), CMS did not adopt a Fee-For-Service Adjuster in RADV Audits.  Relying on a recent D.C. Circuit decision, CMS takes the position that the obligation to report and return overpayments is not subject to the “actuarial equivalence” provision of the statute (42 U.S.C. § 1395w-23(a)(1)(C)) that applies to the risk adjustment payment methodology. UnitedHealthcare Ins. Co. v. Becerra, 16 F.4th 867, 885-86 (D.C. Cir. 2021), cert denied, 142 S. Ct. 2851 (2022).

CMS believes that as much as 7% of total aggregate payments made to MA organizations constitute overpayments and expects the new rule to recover more than $479 million in excess payments when implemented in full in 2025.  The new rule is certain to be challenged in court; nonetheless, MA organizations would be well-advised to continue efforts to shore up and enhance compliance programs and procedures to minimize or avoid errors in coding submissions.

DISCLAIMER: Because of the generality of this update, the information provided herein may not be applicable in all situations and should not be acted upon without specific legal advice based on particular situations.

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