The Centers for Medicare & Medicaid Services (CMS) on Tuesday issued a final rule to amend the methodology for the U.S. Department of Health and Human Services’ risk adjustment data validation (HHS-RADV) program. The new regulation aims to provide states and payers with more stability and predictability, promote program integrity, and foster competition.

The rule finalizes changes to two technical aspects of the HHS-RADV program, the error rate calculation and the application of HHS-RADV results.

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Updates to the HHS-RADV error rate calculation

CMS has refined the HHS-RADV error rate calculation, the method it uses to determine the adjustments to issuers’ previously calculated risk adjustment risk scores and state transfers based on HHS-RADV results.

This error rate calculation is, in part, based on the issuer’s failure rate, a measure of the issuer’s failure to validate diagnoses and conditions associated with enrollees selected for audit. To avoid adjusting risk adjustment transfers for expected variations, HHS-RADV only adjusts an issuer’s risk score when an issuer’s failure rate goes beyond a certain threshold making them an outlier.

For 2019 benefit year HHS-RADV and beyond, CMS finalized the following three modifications to the error rate calculation:

  • It will now modify the way that it groups medical conditions in HHS-RADV within the same hierarchical condition category (HCC) coefficient estimation groups in risk adjustment to determine failure rates for those HCCs. CMS said in a fact sheet that the change will better account for the difficulty in categorizing certain conditions and to, therefore, refine how the error rate calculation measures risk differences within and between condition groupings.  
  • It will make changes that would reduce the magnitude of risk score adjustments for issuers close to the threshold used to determine whether an issuer is an outlier. Currently, issuers whose failure rates are not significantly different from issuers just inside the threshold may see significant changes to their risk scores and transfers, creating a “payment cliff” for issuers just outside the threshold. Adjusting the magnitude of risk score adjustments intends to mitigate this effect.
  • It will modify the error rate calculation in cases where certain outlier issuers have a negative failure rate. A low failure rate is not always due to more accurate data submission. A low failure rate can also be due to not identifying conditions that should have been reported in risk adjustment.  The final rule refines the error rate calculation to mitigate the impact of adjustments that result from error rates driven by these newly found conditions.

“These changes are intended to strengthen program integrity by reducing possible incentives for issuers to underreport diagnoses during initial risk adjustment data submission,” CMS said. “These changes will also promote fairness by ensuring that issuers are not penalized in HHS-RADV when a difference in diagnosis for an enrollee has no effect on risk, as well as by ensuring that issuers that receive adjustments are receiving adjustments in proportion to the errors identified through HHS-RADV. The changes are based on lessons learned and stakeholder feedback from the initial years of HHS-RADV.

Application of HHS-RADV results

The second change involves the application of HHS-RADV results to adjust the risk scores and transfer amounts for the benefit year being audited. Currently, HHS-RADV generally applies a prospective approach to adjust risk adjustment transfers, meaning HHS-RADV results are used to adjust the subsequent benefit year risk score and transfers. For example, 2017 benefit year HHS-RADV results are generally used to adjust 2018 benefit year transfer amounts. The one exception is for exiting issuers whose HHS-RADV results are currently used to adjust the risk scores and transfer amounts for the benefit year being audited.

CMS said this change addresses concerns about making adjustments to risk scores based on HHS-RADV error rates calculated using prior benefit year data, when an issuer’s risk profile, enrollment, or market participation could change substantially from benefit year to benefit year. It also promotes fairness by avoiding situations where an issuer who newly enters a state market risk pool is subject to HHS-RADV adjustments from a benefit year in which they did not offer plans.