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CMS Final Rule Amends Risk Adjustment Data Validation Program

Analysis  |  By John Commins  
   November 25, 2020

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

The Centers for Medicare & Medicaid Services this week issued a final rule to amend the methodology for the Department of Health and Human Services’ risk adjustment data validation (HHS-RADV) program.

After collecting stakeholder feedback, CMS says the final rule "will give states and insurers more stability and predictability, promote program integrity, and foster increased competition."

*These changes will also promote fairness by ensuring that insurers 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 insurers that receive adjustments are receiving adjustments in proportion to the errors identified through HHS-RADV," CMS said.

The first change refines the HHS-RADV error rate calculation, which is based on the insurers' "failure rate," a metric that validates diagnoses and conditions associated with enrollees selected for audit.

The final rule will also:

* Modify grouping 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. The modification will better account for the difficulty in categorizing some conditions and to refine how the error rate calculation measures risk differences among condition groupings.

* Reduce the magnitude of risk score adjustments for insurers close to the threshold used to determine whether an issuer is an outlier. Now, insurers whose failure rates are not significantly different from insurers just inside the threshold may see significant changes to their risk scores and transfers, creating a "payment cliff" for insurers just outside the threshold.

* Modify the error rate calculation in cases where certain outlier insurers 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 changes are based on lessons learned and stakeholder feedback from the initial years of HHS-RADV. It is part of a larger initiative to disincentivize insurers from cherry-picking, younger, healthier, low-risk enrollees.

John Commins is a content specialist and online news editor for HealthLeaders, a Simplify Compliance brand.


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