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Forum for Health Economics & Policy

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1558-9544
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Health and Health Care of Medicare Beneficiaries in 2030

Étienne Gaudette
  • Corresponding author
  • University of Southern California, Schaeffer Center for Health Policy and Economics, Los Angeles, CA, USA
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/ Bryan Tysinger
  • University of Southern California, Schaeffer Center for Health Policy and Economics, Los Angeles, CA, USA
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/ Alwyn Cassil / Dana P. Goldman
  • University of Southern California, Schaeffer Center for Health Policy and Economics, Los Angeles, CA, USA
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Published Online: 2015-11-28 | DOI: https://doi.org/10.1515/fhep-2015-0037

Abstract

On Medicare’s 50th anniversary, we use the Future Elderly Model (FEM) – a microsimulation model of health and economic outcomes for older Americans – to generate a snapshot of changing Medicare demographics and spending between 2010 and 2030. During this period, the baby boomers, who began turning 65 and aging into Medicare in 2011, will drive Medicare demographic changes, swelling the estimated US population aged 65 or older from 39.7 million to 67.0 million. Among the risks for Medicare sustainability, the size of the elderly population in the future likely will have the highest impact on spending but is easiest to forecast. Population health and the proportion of the future elderly with disabilities are more uncertain, though tools such as the FEM can provide reasonable forecasts to guide policymakers. Finally, medical technology breakthroughs and their effect on longevity are most uncertain and perhaps riskiest. Policymakers will need to keep these risks in mind if Medicare is to be sustained for another 50 years. Policymakers may also want to monitor the equity of Medicare financing amid signs that the program’s progressivity is declining, resulting in higher-income people benefiting relatively more from Medicare than lower-income people.

Keywords: aging; health; Medicare; medical innovation; medical spending; microsimulation

References

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About the article

Corresponding author: Étienne Gaudette, University of Southern California, Schaeffer Center for Health Policy and Economics, Los Angeles, CA, USA, e-mail:


Published Online: 2015-11-28

Published in Print: 2015-12-01


Conflict of interest: None declared.

Research funding: National Institute on Aging grants 5P30AG024968 and R56AG045135.

Author statement: The authors did not receive financial support for conducting this study. The authors are grateful to the National Institute on Aging for its support through the Roybal Center for Health Policy Simulation (grant no. P30AG024968) and through Award Number R56AG045135. The content of this article is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.


Citation Information: Forum for Health Economics and Policy, ISSN (Online) 1558-9544, ISSN (Print) 2194-6191, DOI: https://doi.org/10.1515/fhep-2015-0037.

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