CMS RADV White Paper Outlines Potentially Significant Program Changes

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Summary

CMS is considering changes to its commercial market Risk Adjustment Data Validation (RADV) program to improve the accuracy of risk adjustment transfers and to increase stability and predictability for issuers. This follows issuer experiences with the 2017 RADV process in which some issuers saw substantial, unforeseen changes to their risk adjustment transfers. These RADV changes have the potential to impact issuer participation and premiums in future years depending on the direction (positive or negative) and magnitude of those transfers.
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Background

The Affordable Care Act (ACA) created several risk mitigation programs to help equalize enrollee risk pools for issuers in the individual and small group markets. One such program is the risk adjustment (RA) program.

The RA program redistributes plan revenues among issuers in the same state and same market based on the health risk of their enrollees. CMS created the RADV program to help ensure the accuracy of these RA transfers. As designed by CMS, the RADV program determines if the diagnosis code used for risk adjustment is documented in a medical record.

When CMS performed RADV for 2015 and 2016 data, no transfers were made as CMS was testing the program. CMS’ current methodology would base audit-related transfers for a given year on RADV results from the previous year. The first transfers under RADV will be made relative to the 2018 RA results using RADV findings from CMS’ analysis of 2017 data. During that RADV process, 127 of 258 individual market issuers and 329 of 473 small group issuers will see adjustments to 2018 RA transfers. A total of 87 individual market issuers saw negative RADV adjustments (leading to lower payments)—some as much as $58 million. However, transfer payments will not be collected until 2021.

Issuers reported a mixed experience with the RADV program. Issuers and validation entities continued to report widespread challenges obtaining medical records, although significant improvements had been made since the initial 2015 RADV process. The biggest concerns cited continue to be uncertainty related to outlier status and metrics (where the disparate experience between issuers in collecting and reporting information can significantly impact the positioning of outlier metrics) and the fact that changes in participation and premiums between the measurement and RA year can lead to significant payment impacts.

CMS Proposals

CMS has collected significant feedback from issuers and others related to the RADV process. Based on this feedback CMS released a white paper on December 6 to explore certain concerns with the RADV program and to outline potential changes that the department is exploring. CMS is considering potential modifications to 4 specific aspects of the RADV program:

  • Validation Sampling: Explores whether the current enrollee sampling methodology, which is based on Medicare Advantage Risk Adjustment Data Validation (MA-RADV) error rates and results in a sample size of 200 enrollees for most issuers, should be adjusted. Specific changes considered are related to increasing the number of individuals with HCC conditions in the samples (including whether there should be different sample sizes for larger and smaller issuers), and varying the sample size based on HCC outlier status and whether precision targets are met in all HCC groups
  • Outlier Detection: Assesses the sensitivity of the current outlier detection methodology (which uses national weighted-mean HCC failure rate metrics to determine issuer-specific HCC outlier status) and considers options to modify the outlier detection process to more precisely identify true outliers. CMS is interested in exploring issuer-specific confidence intervals (including those that account for an issuer’s historic ability to collect and submit data to validate claims), using machine learning instead of defined formulas, and changes that correct for coding hierarchy issues related to how condition and severity are factored in to RA scores
  • Error Rate Calculation: Examines alternatives to calculating error rate based on the national weighted HCC group mean values to mitigate the magnitude of adjustments and to reduce the “transfer cliff” for outlier issuers near the margins of the confidence intervals. Highlighted changes include smoothing and reducing adjustments by assessing the amount of error off the confidence intervals rather than the national mean and reducing the size of negative error rate adjustments
  • Transfer Timing: Considers 3 options to conduct and apply RADV in the current year by using historical RADV data and trends rather than in the subsequent risk adjustment year. The primary goal is to increase predictability for issuers. The change could also address the impacts that changes in enrollment and premium pricing between the measurement and transfer year can have on RADV adjusted transfer amounts

Issuers may need to perform modeling based on their own experiences to identify the impacts of the potential changes explored in the paper or other changes CMS may consider. While CMS did not specifically propose any changes, intending the comment process to inform future changes, CMS may consider enacting some of the modifications discussed in the white paper in forthcoming regulations—including potentially in the 2021 Notice of Benefit and Payment Parameters that is currently under review at the Office of Management and Budget.

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