New Analysis Exposes Additional Flaws in MedPAC Report
A by FTI Consulting sheds additional light on the flawed assumptions, data and conclusions of the Medicare Payment Advisory Commission鈥檚 (MedPAC鈥檚) 2024 report to Congress 鈥� adding to concerns previously raised by 色控传媒 and stakeholders about MedPAC鈥檚 estimates.
Background: MedPAC鈥檚 Flawed Assertions
MedPAC鈥檚 report incorrectly suggested that Medicare Advantage (MA) enrollees would be significantly less expensive if covered instead under fee-for-service Medicare (FFS).
A key aspect of MedPAC鈥檚 analysis was an assertion of 鈥渇avorable selection鈥� in MA鈥攁n unsubstantiated assumption that healthier-than-average beneficiaries disproportionately enroll in MA, resulting in federal 鈥渙verpayments鈥� to MA plans that are funded via benchmarks based on average FFS costs. MedPAC鈥檚 assertions are based on incorrect assumptions and incomplete data.
FTI鈥檚 Concerns: Data and Methods
FTI found that MedPAC鈥檚 analysis suffers from a dependence on incomplete beneficiary data, excludes important subpopulations, and neglects the role of plan bids in determining the actual costs of the program. For example:
- Extrapolating Results Based on 鈥淪witchers鈥�: MedPAC estimated favorable selection using only FFS data. This leaves out the enrollees who go directly into MA, bypassing FFS, which is a growing contingent of seniors. More than 40% of MA enrollees join MA plans when first eligible for Medicare. If their cost patterns differ from the FFS population, the impact on the analysis could be significant. MedPAC also ignores the possibility that different cost sharing structures in MA might affect consumer utilization of care. While MA plans generally have lower out-of-pocket costs than FFS, MedPAC assumes spending patterns remain consistent for FFS enrollees after switching into MA. This fails to account for 鈥渟witchers鈥� who might forego care in FFS until they enroll in MA, when they can then obtain necessary services.
- Treatment of Key Beneficiary Categories: MedPAC鈥檚 analysis failed to adequately account for how excluding or otherwise accounting for certain categories of beneficiaries affects program spending comparisons. These omissions likely inflate MedPAC鈥檚 favorable selection findings. For example, MedPAC鈥檚 analysis excludes people enrolled only in Medicare Part A 鈥� about 15% of the total FFS population as of 2021. While these people are ineligible for MA, CMS includes them in MA payment calculations which leads to reduced MA benchmarks. A recent shows that a more apples-to-apples comparison of spending that adequately accounts for these ineligible enrollees would show FFS costs 5.9% higher in 2021 if corrected to include only individuals with Parts A and B. In addition, plans serving dual-eligible beneficiaries incur significant extra costs to coordinate care for their enrollees as required by CMS, while FFS does not provide this care coordination. Because MedPAC does not account for these services, it fails to make a fair comparison of the impacts of moving this high-needs population out of managed care.
- Focus on Benchmarks rather than Bids: MedPAC鈥檚 analysis regarding favorable selection calculates spending in MA plans based on benchmarks rather than plan bids. But, as required by law, actual MA payments are based on bids, with the government retaining a share of the savings when bids are below benchmarks. By ignoring the MA bid structure, MedPAC鈥檚 analysis is misleading and overstates the cost impact to taxpayers of moving people into FFS.
MedPAC鈥檚 failure to recognize and adequately explain these significant gaps and methodological blind spots renders its conclusions about favorable selection unreliable and misleading.
More than 34 million seniors and people with disabilities actively choose MA for their Medicare coverage because it provides them with better care for lower costs. Policymakers should not rely on such a fundamentally flawed and speculative analysis to take actions that could harm beneficiaries in this vital part of the Medicare program.
To read the new analysis by FTI Consulting, .