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Technology Growth and Expenditure Growth in Health Care

Author

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  • Amitabh Chandra
  • Jonathan S. 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 U.S. to ever-rising tax rates will likely slow cost growth, with uncertain effects on technology growth.

Suggested Citation

  • Amitabh Chandra & Jonathan S. Skinner, 2011. "Technology Growth and Expenditure Growth in Health Care," NBER Working Papers 16953, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:16953
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    References listed on IDEAS

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    1. Medical expenditure and technology growth
      by Economic Logician in Economic Logic on 2011-05-27 19:57:00

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    2. Freedman, Seth & Lin, Haizhen & Simon, Kosali, 2015. "Public health insurance expansions and hospital technology adoption," Journal of Public Economics, Elsevier, vol. 121(C), pages 117-131.
    3. Lavergne, Miriam Ruth & Barer, Morris & Law, Michael R. & Wong, Sabrina T. & Peterson, Sandra & McGrail, Kimberlyn, 2016. "Examining regional variation in health care spending in British Columbia, Canada," Health Policy, Elsevier, vol. 120(7), pages 739-748.
    4. 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, vol. 31(1), pages 169-179.
    5. Levaggi, Rosella & Moretto, Michele & Pertile, Paolo, 2014. "Two-part payments for the reimbursement of investments in health technologies," Health Policy, Elsevier, vol. 115(2), pages 230-236.
    6. Jeffrey Clemens & Joshua D. Gottlieb, 2014. "Do Physicians' Financial Incentives Affect Medical Treatment and Patient Health?," American Economic Review, American Economic Association, vol. 104(4), pages 1320-1349, April.
    7. Sean Dougherty & Luca Lorenzoni & Alberto Marino & Fabrice Murtin, 2022. "The impact of decentralisation on the performance of health care systems: a non-linear relationship," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 23(4), pages 705-715, June.
    8. Rosella Levaggi & Michele Moretto & Paolo Pertile, 2012. "DRGs: the link between investment in technologies and appropriateness," Working Papers 31/2012, University of Verona, Department of Economics.
    9. Joseph Doyle & John Graves & Jonathan Gruber, 2019. "Evaluating Measures of Hospital Quality: Evidence from Ambulance Referral Patterns," The Review of Economics and Statistics, MIT Press, vol. 101(5), pages 841-852, December.
    10. Astolfi, Roberto & Lorenzoni, Luca & Oderkirk, Jillian, 2012. "Informing policy makers about future health spending: A comparative analysis of forecasting methods in OECD countries," Health Policy, Elsevier, vol. 107(1), pages 1-10.
    11. Zack Cooper & Amanda E. Kowalski & Eleanor Neff Powell & Jennifer Wu, 2017. "Politics, Hospital Behavior, and Health Care Spending Effect Methods to Examine Treatment Effect Heterogeneity in Experiments for the Young and Privately Insured?," Cowles Foundation Discussion Papers 3006, Cowles Foundation for Research in Economics, Yale University.
    12. Zack Cooper & Amanda E. Kowalski & Eleanor Neff Powell & Jennifer Wu, 2017. "Politics, Hospital Behavior, and Health Care Spending," Cowles Foundation Discussion Papers 2106, Cowles Foundation for Research in Economics, Yale University.
    13. Zack Cooper & Amanda E. Kowalski & Eleanor Neff Powell & Jennifer Wu, 2017. "Politics, Hospital Behavior, and Health Care Spending Effect Methods to Examine Treatment Effect Heterogeneity in Experiments for the Young and Privately Insured?," Cowles Foundation Discussion Papers 3006, Cowles Foundation for Research in Economics, Yale University.
    14. Joseph Doyle & John Graves & Jonathan Gruber, 2015. "Uncovering Waste in U.S. Healthcare," NBER Working Papers 21050, National Bureau of Economic Research, Inc.
    15. Zack Cooper & Amanda E Kowalski & Eleanor N Powell & Jennifer Wu, 2017. "Politics and Health Care Spending in the United States," NBER Working Papers 23748, National Bureau of Economic Research, Inc.
    16. Katherine Baicker & Amitabh Chandra, 2011. "Aspirin, angioplasty and proton beam therapy: the economics of smarter health-care spending," Proceedings - Economic Policy Symposium - Jackson Hole, Federal Reserve Bank of Kansas City, pages 197-235.
    17. Proksch, Dorian & Busch-Casler, Julia & Haberstroh, Marcus Max & Pinkwart, Andreas, 2019. "National health innovation systems: Clustering the OECD countries by innovative output in healthcare using a multi indicator approach," Research Policy, Elsevier, vol. 48(1), pages 169-179.
    18. Anne Mason & Idaira Rodriguez Santana & María José Aragón & Nigel Rice & Martin Chalkley & Raphael Wittenberg & Jose-Luis Fernandez, 2019. "Drivers of health care expenditure: Final report," Working Papers 169cherp, Centre for Health Economics, University of York.

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    JEL classification:

    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • I1 - Health, Education, and Welfare - - Health
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior

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