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Do Medicare Advantage plans select enrollees in higher margin clinical categories?

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  • Newhouse, Joseph P.
  • McWilliams, J. Michael
  • Price, Mary
  • Huang, Jie
  • Fireman, Bruce
  • Hsu, John

Abstract

The CMS-HCC risk adjustment system for Medicare Advantage (MA) plans calculates weights, which are effectively relative prices, for beneficiaries with different observable characteristics. To do so it uses the relative amounts spent per beneficiary with those characteristics in Traditional Medicare (TM). For multiple reasons one might expect relative amounts in MA to differ from TM, thereby making some beneficiaries more profitable to treat than others. Much of the difference comes from differences in how TM and MA treat different diseases or diagnoses. Using data on actual medical spending from two MA-HMO plans, we show that the weights calculated from MA costs do indeed differ from those calculated using TM spending. One of the two plans (Plan 1) is more typical of MA-HMO plans in that it contracts with independent community providers, while the other (Plan 2) is vertically integrated with care delivery. We calculate margins, or average revenue/average cost, for Medicare beneficiaries in the two plans who have one of 48 different combinations of medical conditions. The two plans’ margins for these 48 conditions are correlated (r=0.39, p<0.01). Both plans have margins that are more positive for persons with conditions that are managed by primary care physicians and where medical management can be effective. Conversely they have lower margins for persons with conditions that tend to be treated by specialists with greater market power than primary care physicians and for acute conditions where little medical management is possible. The two plan's margins among beneficiaries with different observable characteristics vary over a range of 160 and 98 percentage points, respectively, and thus would appear to offer substantial incentive for selection by HCC. Nonetheless, we find no evidence of overrepresentation of beneficiaries in high margin HCC's in either plan. Nor, using the margins from Plan 1, the more typical plan, do we find evidence of overrepresentation of high margin HCC's in Medicare more generally. These results do not permit a conclusion on overall social efficiency, but we note that selection according to margin could be socially efficient. In addition, our findings suggest there are omitted interaction terms in the risk adjustment model that Medicare currently uses.

Suggested Citation

  • Newhouse, Joseph P. & McWilliams, J. Michael & Price, Mary & Huang, Jie & Fireman, Bruce & Hsu, John, 2013. "Do Medicare Advantage plans select enrollees in higher margin clinical categories?," Journal of Health Economics, Elsevier, vol. 32(6), pages 1278-1288.
  • Handle: RePEc:eee:jhecon:v:32:y:2013:i:6:p:1278-1288
    DOI: 10.1016/j.jhealeco.2013.09.003
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    References listed on IDEAS

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    Cited by:

    1. Alice Burns & Tamara Hayford, 2017. "Effects of Medicare Advantage Enrollment on Beneficiary Risk Scores: Working Paper 2017-08," Working Papers 53270, Congressional Budget Office.
    2. Carey, Colleen, 2021. "Sharing the burden of subsidization: Evidence on pass-through from a subsidy revision in Medicare Part D," Journal of Public Economics, Elsevier, vol. 198(C).
    3. Decarolis, Francesco & Guglielmo, Andrea, 2017. "Insurers’ response to selection risk: Evidence from Medicare enrollment reforms," Journal of Health Economics, Elsevier, vol. 56(C), pages 383-396.
    4. Colleen Carey, 2017. "Technological Change and Risk Adjustment: Benefit Design Incentives in Medicare Part D," American Economic Journal: Economic Policy, American Economic Association, vol. 9(1), pages 38-73, February.
    5. Janet Currie & W. Bentley MacLeod, 2017. "Diagnosing Expertise: Human Capital, Decision Making, and Performance among Physicians," Journal of Labor Economics, University of Chicago Press, vol. 35(1), pages 1-43.
    6. Timothy J. Layton & Randall P. Ellis & Thomas G. McGuire, 2015. "Assessing Incentives for Adverse Selection in Health Plan Payment Systems," Boston University - Department of Economics - Working Papers Series wp2015-024, Boston University - Department of Economics.
    7. Sungchul Park & Anirban Basu, 2018. "Alternative evaluation metrics for risk adjustment methods," Health Economics, John Wiley & Sons, Ltd., vol. 27(6), pages 984-1010, June.
    8. McGuire, Thomas G. & Newhouse, Joseph P. & Normand, Sharon-Lise & Shi, Julie & Zuvekas, Samuel, 2014. "Assessing incentives for service-level selection in private health insurance exchanges," Journal of Health Economics, Elsevier, vol. 35(C), pages 47-63.
    9. Francesco Decarolis & Andrea Guglielmo & Clavin Luscombe, 2020. "Open enrollment periods and plan choices," Health Economics, John Wiley & Sons, Ltd., vol. 29(7), pages 733-747, July.
    10. Wynand P. M. M. Ven & René C. J. A. Vliet & Richard C. Kleef, 2017. "How can the regulator show evidence of (no) risk selection in health insurance markets? Conceptual framework and empirical evidence," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 18(2), pages 167-180, March.
    11. Sungchul Park & Anirban Basu & Norma Coe & Fahad Khalil, 2017. "Service-level Selection: Strategic Risk Selection in Medicare Advantage in Response to Risk Adjustment," NBER Working Papers 24038, National Bureau of Economic Research, Inc.
    12. Cici McNamara & Natalia Serna, 2022. "The impact of a national formulary expansion on diabetics," Health Economics, John Wiley & Sons, Ltd., vol. 31(11), pages 2311-2332, November.

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