Currently Viewing:
The American Journal of Managed Care November 2014
The Correlation of Family Physician Work With Submitted Codes and Fees
Richard Young, MD, and Tiffany L. Overton, MPH
Population Targeting and Durability of Multimorbidity Collaborative Care Management
Elizabeth H.B. Lin, MD, MPH; Michael Von Korff, ScD; Do Peterson, MS; Evette J. Ludman, PhD; Paul Ciechanowski, MD, MPH; and Wayne Katon, MD
Have Prescription Drug Brand Names Become Generic?
Alfred B. Engelberg, JD
Currently Reading
Will Medicare Advantage Payment Reforms Impact Plan Rebates and Enrollment?
Lauren Hersch Nicholas, PhD, MPP
Medical Cost Burdens Among Nonelderly Adults With Asthma
Emily Carrier, MD, and Peter Cunningham, PhD
The Role of Retail Pharmacies in CVD Prevention After the Release of the ATP IV Guidelines
William H. Shrank, MD, MSHS; Andrew Sussman, MD; and Troyen A. Brennan, MD, JD
Care Coordination Measures of a Family Medicine Residency as a Model for Hospital Readmission Reduction
Wayne A. Mathews, MS, PA-C
Medication Adherence and Readmission After Myocardial Infarction in the Medicare Population
Yuting Zhang, PhD; Cameron M. Kaplan, PhD; Seo Hyon Baik, PhD; Chung-Chou H. Chang, PhD; and Judith R. Lave, PhD
Reasons for Emergency Department Use: Do Frequent Users Differ?
Kelly M. Doran, MD, MHS; Ashley C. Colucci, BS; Stephen P. Wall, MD, MS, MAEd; Nick D. Williams, MA, PhD; Robert A. Hessler, MD, PhD; Lewis R. Goldfrank, MD; and Maria C. Raven, MD, MPH
Switching from Multiple Daily Injections to CSII Pump Therapy: Insulin Expenditures in Type 2 Diabetes
Guy David, PhD; Max Gill, MBA, Candace Gunnarsson, EdD; Jeff Shafiroff, PhD; and Steven Edelman, MD
Service Setting Impact on Costs for Bevacizumab-Treated Oncology Patients
Nicole M. Engel-Nitz, PhD; Elaine B. Yu, PharmD, MS; Laura K. Becker, MS; and Art Small, MD
Influence of Hospital and Nursing Home Quality on Hospital Readmissions
Kali S. Thomas, PhD; Momotazur Rahman, PhD; Vincent Mor, PhD; and Orna Intrator, PhD

Will Medicare Advantage Payment Reforms Impact Plan Rebates and Enrollment?

Lauren Hersch Nicholas, PhD, MPP
Medicare Advantage enrollment decreases with lower rebates for supplemental benefits. Upcoming ACA reforms are predicted to reduce MA enrollment where traditional Medicare costs are low.

To assess the relationship between Medicare Advantage (MA) plan rebates and enrollment and simulate the effects of Affordable Care Act (ACA) payment reforms.

Study Design and Methods
First difference regressions of county-level MA payment and enrollment data from CMS from 2006 to 2010.

A $10 decrease in the per member/per month rebate to MA plans was associated with a 0.20 percentage point (0.9%) decrease in MA penetration (P <.001) and a 7.1% decline in the average MA enrollee’s risk score (P <.001). These effects are small overall, but larger in counties with low levels of traditional Medicare spending; a $10 decrease in monthly rebates was associated with a 0.64 percentage point decline in MA penetration and a 10% decrease in risk score. ACA reforms are predicted to reduce the level of rebates in lower-spending counties, leading to enrollment decreases of 1.7 to 1.9 percentage points in the lowest-spending counties. The simulation predicts that the disenrollment would come from MA enrollees with higher risk scores.

MA enrollment responds to availability of supplemental benefits supported by rebates. ACA provisions designed to lower MA spending will predominantly affect Medicare beneficiaries living in counties where MA plans may be unable to offer a comparable product at a price similar to that of traditional Medicare.

Am J Manag Care. 2014;20(11):917-924

In many counties, payments to Medicare Advantage (MA) plans exceed average tra- ditional Medicare (TM) spending. Affordable Care Act (ACA) reforms designed to reduce payments may also reduce plans’ supplemental benefit offerings.
  • Lower MA plan rebates were associated with decreases in MA enrollment, especially by beneficiaries with higher risk scores (expected utilization).
  • The enrollment response was larger in counties with low TM spending.
  • ACA payment reforms are predicted to have small effects on enrollment, especially in counties where MA plan costs are belowTM costs, despite relatively large rebate reductions.
Private plans have been offered as an alternative to traditional, fee-for-service Medicare (TM) for over 30 years. Despite optimism that managed care would reduce Medicare spending, policy changes starting with the 2003 Medicare Modernization Act have ensured higher payment rates (relative to TM) to private plans in all counties through the Medicare Advantage (MA) program.1 In 2006, CMS introduced a bid system to determine payments to plans.

CMS sets annual, county-level payment benchmarks, the maximum monthly amount it will reimburse a private plan to provide standard Medicare benefits to an average-risk enrollee. Historically, benchmarks were not directly tied to cost of care in the county, though this will change under Afford- able Care Act (ACA) reforms.2 MA plans “bid” the amount it costs them to provide Medicare benefits in the counties they will enter. When bids are below the benchmarks, plans receive a rebate covering part of the difference between the benchmark and their bid (risk-adjusted by case-mix), which must be used to provide an actuarially equivalent amount of additional benefits or reduced premiums to enrollees. This approach aims to use competition between plans to lower Medicare expenditures while increasing supplemental benefits.3

Rebates were initially set at 75% of the difference between the benchmark and the bid. ACA changes will gradually reduce this to 50%, 65%, or 70% of the difference, depending on a plan’s quality rating.3 ACA provisions will also tie county benchmarks to TM spending (from 95% of expected spending in the highest cost regions to 115% in the lowest cost regions). More generous benchmarks relative to plans’ true costs imply larger rebate amounts. Plans can use these rebates to offer benefits such as more comprehensive drug coverage that will attract sicker enrollees, or benefits that attract healthier enrollees such as fitness programs and preventive care.4-7 Prior research has found a positive relationship between overall payments to MA plans and firm and beneficiary participation.4,8-10 However, profound variation in average Medicare spending and the cost of care across geographic regions means that a higher payment rate in one county versus another does not necessarily mean that plans in the higher-rate county offer more generous supplemental benefits.

This study used newly available administrative data detailing the average rebates paid to MA plans between 2006 and 2010 to examine the relationship between rebates, a direct measure of supplemental benefit generosity, and 2 measures of MA enrollment (penetration rates and average MA risk scores), and to assess the extent that these results varied in counties with low versus high TM spending. Results are used to simulate the enrollment response to ACA policy changes. To date, little is known about whether these changes would be passed on to MA enrollees through supplemental benefit reductions, or if they would simply reduce plan profits.2 Understanding the impacts of benchmark reductions and changes to the rebate formula has important implications for ACA implementation and future Medicare spending projections.



I analyzed publicly available CMS data detailing county-level MA benchmarks from 2006 to 2010 linked to information about payments, enrollment, and patient risk scores reported at the county by plan-type level. These files were combined with information about average TM spending adjusted for labor costs from the Dartmouth Atlas of Health Care. I included MA enrollment in health maintenance organizations, local and regional preferred provider organizations, and private fee-for-service plans (excluding private plans available to certain subgroups of beneficiaries, such as employer-sponsored plans). Because CMS reports information aggregated at the county by plan-type level, risk scores and rebates are enrollment-weighted averages across these plan types.

Enrollment: Enrollment was measured as the proportion of Medicare beneficiaries enrolled in an MA plan (penetration) and the average MA risk score. Risk scores are a summary measure of expected utilization used to adjust payments for enrollee health relative to the “average” Medicare beneficiary (risk score of 1). Higher scores indicate higher levels of expected utilization.

Rebates: Plan rebates, adjusted to 2010 dollars using the Consumer Price Index (results were unchanged whether we used the overall or medical Consumer Price Index for adjustment), represent the dollar value of supplemental benefits offered. While detailed benefit data are not available for the study years, rebates are positively correlated with availability of 2 generous plan offerings; availability of at least 1 zero-premium plan with prescription drug coverage (P = .40); and availability of a zero-premium plan with expanded prescription drug coverage (P = .38). CMS calculates each plan’s actual rebate using benchmarks and risk scores that account for the plan’s enrollee profile across all markets served, rather than for each plan-county combination. Thus the county-level average rebates analyzed capture variation in plans’ cost of providing care in each local market and each plan’s risk profile across markets. Under the ACA, rebates are further adjusted based on plans’ quality “star” ratings. The ACA simulation assumes a 65% rebate, corresponding to a plan with a quality rating between 3.5 and 4.5 out of 5 stars. As of 2012, the majority of plans and enrollment were between 3 and 5 stars.11

Statistical Methods

I estimated first-difference regressions of the change in county-level MA enrollment measures from the previous year on changes in average plan rebates and control variables to test the hypothesis that Medicare beneficiaries change their MA enrollment decisions in response to plan generosity. These models capture the immediate enrollment effects of rebate changes relative to the prior year and control for time-invariant characteristics of each county that may be related to MA payments and enrollment.

ΔEnrollct = β ΔRebatect + a ΔMarketct + g ΔCostct + Time + εct

Regressions controlled for the number of firms offering at least 1 MA plan, the MA market Herfindahl–Hirschman index (HHI), and the cost of providing care in the county. The HHI ranges from 0 to 1 and measures market competition. Higher scores indicate lower levels of competition, with 1 indicating that market enrollment is concentrated in a single plan. Enrollment and patient acuity may increase in more competitive markets, as beneficiaries have access to a more diverse choice set and may be more likely to find a plan appropriate for their needs. Local costs were measured by the ratio of price-adjusted average TM spending to unadjusted TM spending from the Dartmouth Atlas of Health Care. Price-adjusting accounts for factors like local wage rates that make some markets more costly.12 Regressions included a constant term and indicator variables for the years 2008 to 2010 to account for other factors influencing MA enrollment and plan rebates over time.13

Regressions were weighted by county Medicare enrollment (aged 65 years and up). Since ACA benchmarks are tied to TM spending, regressions were estimated first by pooling all counties, then separately for counties in the lower versus higher halves of per capita TM spending.

ACA Predictions

Regression coefficients and 2010 data were combined with aggregate information about 2013 plan bids from the Medicare Payment Advisory Commission to estimate the change in rebates and corresponding enrollment response that would be expected under an immediate transition to full implementation of ACA benchmarks and rebates.11 The ACA benchmarks are 115% of expected TM spending in the quartile of counties with lowest TM spending, 107.5% in the next quartile, and 100% and 95% in the third- and fourth-highest quartiles, respectively. Figure 1 shows the 25th, 50th, and 75th percentile of plan bids and ACA benchmarks (relative to TM spending) by spending quartile. I assume that each county’s average bid follows the reported percentages of local TM spending and create an average measure that is the mean of the 3 reported bids.


Sample Characteristics

The sample includes 3180 continental United States counties. ACA quartiles are county-rather than population-weighted; nearly 45% of Medicare beneficiaries lived in the highest spending quartile (Table 1). MA penetration averaged 22.9%, increasing from 19% in 2006 to 26% in 2010. MA benchmarks, payments, and rebates were highest in high TM counties. Monthly per enrollee rebates averaged $87 in the highest TM counties, compared with $52 to $57 in the first through third TM quartiles. MA enrollment was more common and had higher risk scores in high TM counties (mean risk score 1.01 in the highest quartile, 0.87 in the lowest). Rebates and risk scores fell over time, although MA penetration and county benchmarks (in constant dollars) increased (Figure 2).

Regression Results

Copyright AJMC 2006-2020 Clinical Care Targeted Communications Group, LLC. All Rights Reserved.
Welcome the the new and improved, the premier managed market network. Tell us about yourself so that we can serve you better.
Sign Up