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The Pragmatist's Guide to Comparative Effectiveness Research

Author

Listed:
  • Amitabh Chandra
  • Anupam B. Jena
  • Jonathan S. Skinner
Abstract
All developed countries have been struggling with a trend toward health care absorbing an ever-larger fraction of government and private budgets. Adopting any treatment that improves health outcomes, no matter what the cost, can worsen allocative inefficiency by paying dearly for small health gains. One potential solution is to rely more heavily on studies of the costs and effectiveness of new technologies in an effort to ensure that new spending is justified by a commensurate gain in consumer benefits. But not everyone is a fan of such studies and we discuss the merits of comparative effectiveness studies and its cousin, cost-effectiveness analysis. We argue that effectiveness research can generate some moderating effects on cost growth in healthcare if such research can be used to nudge patients away from less-effective therapies, whether through improved decision making or by encouraging beefed-up copayments for cost-ineffective procedures. More promising still for reducing growth is the use of a cost-effectiveness framework to better understand where the real savings lie--and the real savings may well lie in figuring out the complex interaction and fragmentation of healthcare systems.

Suggested Citation

  • Amitabh Chandra & Anupam B. Jena & Jonathan S. Skinner, 2011. "The Pragmatist's Guide to Comparative Effectiveness Research," NBER Working Papers 16990, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:16990
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    References listed on IDEAS

    as
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    Cited by:

    1. Boone, Jan, 2013. "Does the market choose optimal health insurance coverage?," CEPR Discussion Papers 9420, C.E.P.R. Discussion Papers.
    2. Cox, James C. & Sadiraj, Vjollca & Schnier, Kurt E. & Sweeney, John F., 2016. "Higher quality and lower cost from improving hospital discharge decision making," Journal of Economic Behavior & Organization, Elsevier, vol. 131(PB), pages 1-16.
    3. Liran Einav & Amy Finkelstein & Heidi Williams, 2016. "Paying on the Margin for Medical Care: Evidence from Breast Cancer Treatments," American Economic Journal: Economic Policy, American Economic Association, vol. 8(1), pages 52-79, February.
    4. Bhardwaj, Ramesh, 2015. "Restraining High and Rising Cancer Drug Prices: Need for Accelerating R&D Productivity and Aligning Prices with Value," MPRA Paper 63405, University Library of Munich, Germany.
    5. David H. Howard & Yu-Chu Shen, 2011. "Comparative Effectiveness Research, COURAGE, and Technological Abandonment," NBER Working Papers 17371, National Bureau of Economic Research, Inc.
    6. Amitabh Chandra & Jonathan Skinner, 2012. "Technology Growth and Expenditure Growth in Health Care," Journal of Economic Literature, American Economic Association, vol. 50(3), pages 645-680, September.
    7. Cox, James C. & Sadiraj, Vjollca & Schnier, Kurt E. & Sweeney, John F., 2016. "Higher quality and lower cost from improving hospital discharge decision making," Journal of Economic Behavior & Organization, Elsevier, vol. 131(PB), pages 1-16.
    8. Alica Stubnova Sparling & David W. Martin & Lillian B. Posey, 2017. "An Evaluation of the Proposed Worker Protection Standard with Respect to Pesticide Exposure and Parkinson’s Disease," Working Papers 6, Davidson College, Department of Economics.
    9. Alica Stubnova Sparling & David W. Martin & Lillian B. Posey, 2016. "An Evaluation of the Proposed Worker Protection Standard with Respect to Pesticide Exposure, and Parkinson’s Disease," Working Papers 16-02, Davidson College, Department of Economics, revised Sep 2016.
    10. Boone, J., 2013. "Does the Market Choose Optimal Health Insurance Coverage," Other publications TiSEM f7691fbf-f770-4714-b1b4-1, Tilburg University, School of Economics and Management.
    11. Wu, Bingxiao & David, Guy, 2022. "Information, relative skill, and technology abandonment," Journal of Health Economics, Elsevier, vol. 83(C).
    12. McCarthy, Ian M., 2016. "Eliminating composite bias in treatment effects estimates: Applications to quality of life assessment," Journal of Health Economics, Elsevier, vol. 50(C), pages 47-58.

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    JEL classification:

    • H51 - Public Economics - - National Government Expenditures and Related Policies - - - Government Expenditures and Health
    • I1 - Health, Education, and Welfare - - Health

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