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Technology Growth and Expenditure Growth in Health Care

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  • Amitabh Chandra
  • Jonathan Skinner

Abstract

In the United States, health care technology has contributed to rising survival rates, yet health care spending relative to GDP has also grown more rapidly than in any other country. We develop a model of patient demand and supplier behavior to explain these parallel trends in technology growth and cost growth. We show that health care productivity depends on the heterogeneity of treatment effects across patients, the shape of the health production function, and the cost structure of procedures such as MRIs with high fixed costs and low marginal costs. The model implies a typology of medical technology productivity: (I) highly cost-effective "home run" innovations with little chance of overuse, such as anti-retroviral therapy for HIV, (II) treatments highly effective for some but not for all (e.g., stents), and (III) "gray area" treatments with uncertain clinical value such as ICU days among chronically ill patients. Not surprisingly, countries adopting Category I and effective Category II treatments gain the greatest health improvements, while countries adopting ineffective Category II and Category III treatments experience the most rapid cost growth. Ultimately, economic and political resistance in the United States to ever-rising tax rates will likely slow cost growth, with uncertain effects on technology growth. (JEL H51, I11, I18, O31)

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Bibliographic Info

Article provided by American Economic Association in its journal Journal of Economic Literature.

Volume (Year): 50 (2012)
Issue (Month): 3 (September)
Pages: 645-80

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Handle: RePEc:aea:jeclit:v:50:y:2012:i:3:p:645-80

Note: DOI: 10.1257/jel.50.3.645
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Citations

Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. Medical expenditure and technology growth
    by Economic Logician in Economic Logic on 2011-05-27 14:57:00
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Cited by:
  1. Amitabh Chandra & Jonathan Holmes & Jonathan Skinner, 2013. "Is This Time Different? The Slowdown in Healthcare Spending," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 47(2 (Fall)), pages 261-323.
  2. Michel Dumont & Peter Willemé, 2013. "Working Paper 02-13 - Machines that go ‘ping’: medical technology and health expenditures in OECD countries," Working Papers 1302, Federal Planning Bureau, Belgium.
  3. Alex R. Horenstein & Manuel S. Santos, 2012. "A Cross-Country Analysis of Health Care Expenditures," Working Papers, University of Miami, Department of Economics 2013-05, University of Miami, Department of Economics.
  4. Jeffrey Clemens, 2013. "The Effect of U.S. Health Insurance Expansions on Medical Innovation," NBER Working Papers 19761, National Bureau of Economic Research, Inc.
  5. Jill R. Horwitz & Daniel Polsky, 2014. "Challenges to Regulatory Decentralization: Lessons from State Health Technology Regulation," NBER Working Papers 19801, National Bureau of Economic Research, Inc.
  6. Martin Gaynor & Kate Ho & Robert Town, 2014. "The Industrial Organization of Health Care Markets," NBER Working Papers 19800, National Bureau of Economic Research, Inc.
  7. repec:exc:wpaper:2013-09 is not listed on IDEAS
  8. Abe Dunn & Eli Liebman & Adam Hale Shapiro, 2012. "Decomposing medical-care expenditure growth," Working Paper Series, Federal Reserve Bank of San Francisco 2012-26, Federal Reserve Bank of San Francisco.
  9. Levaggi, R. & Moretto, M. & Pertile, P., 2012. "Static and dynamic efficiency of irreversible health care investments under alternative payment rules," Journal of Health Economics, Elsevier, Elsevier, vol. 31(1), pages 169-179.
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  11. Yiyan Liu & Ginger Zhe Jin, 2013. "Employer Contribution and Premium Growth in Health Insurance," NBER Working Papers 19760, National Bureau of Economic Research, Inc.
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