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Technology Diffusion and Productivity Growth in Health Care


  • Jonathan Skinner
  • Douglas Staiger


Inefficiency in the U.S. health care system has often been characterized as "flat of the curve" spending providing little or no incremental value. In this paper, we draw on macroeconomic models of diffusion and productivity to better explain the empirical patterns of outcome improvements in heart attacks (acute myocardial infarction). In these models, small differences in the propensity to adopt technology can lead to wide and persistent productivity differences across countries -- or in our case, hospitals. Theoretical implications are tested using U.S. Medicare data on survival and factor inputs for 2.8 million heart attack patients during 1986-2004. We find that the speed of diffusion for highly efficient and often low-cost innovations such as beta blockers, aspirin, and primary reperfusion explain a large fraction of persistent variations in productivity, and swamp the impact of traditional factor inputs. Holding technology constant, the marginal gains from spending on heart attack treatments appear positive but quite modest. Hospitals which during the period 1994/95 to 2003/04 raised their rate of technology diffusion (the "tigers") experienced outcome gains four times the gains in hospitals with diminished rates of diffusion (the "tortoises"). Survival rates in low-diffusion hospitals lag by as much as a decade behind high-diffusion hospitals, raising the question of why some hospitals (and the physicians who work there) adopt so slowly.

Suggested Citation

  • Jonathan Skinner & Douglas Staiger, 2009. "Technology Diffusion and Productivity Growth in Health Care," NBER Working Papers 14865, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:14865
    Note: AG HC PR

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    References listed on IDEAS

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    Cited by:

    1. SUGIHARA Shigeru & ICHIMIYA Hiroki & INUI Tomohiko & ITO Yukiko & SAITO Yukiko & IGARASHI Isao & KAWABUCHI Koichi, 2016. "How do Hospitals Adopt Advanced Treatment Techniques? An assessment through the records of AMI patients in Japan," Discussion papers 16035, Research Institute of Economy, Trade and Industry (RIETI).
    2. French, Declan, 2014. "International mortality modelling—An economic perspective," Economics Letters, Elsevier, vol. 122(2), pages 182-186.
    3. Baltagi, Badi H. & Yen, Yin-Fang, 2014. "Hospital treatment rates and spillover effects: Does ownership matter?," Regional Science and Urban Economics, Elsevier, vol. 49(C), pages 193-202.
    4. Badi Baltagi & Francesco Moscone & Elisa Tosetti, 2012. "Medical technology and the production of health care," Empirical Economics, Springer, vol. 42(2), pages 395-411, April.
    5. Juan Contreras & Elena Patel & Ignez Tristao, 2013. "Production Factors, Productivity Dynamics and Quality Gains as Determinants of Healthcare Spending Growth in U.S. Hospitals," Working Papers 2013-13, Banco de MĂ©xico.
    6. John A. Romley & Neeraj Sood, 2013. "Identifying the Health Production Function: The Case of Hospitals," NBER Working Papers 19490, National Bureau of Economic Research, Inc.
    7. Stephen Hall & P. Swamy & George Tavlas, 2012. "Generalized cointegration: a new concept with an application to health expenditure and health outcomes," Empirical Economics, Springer, vol. 42(2), pages 603-618, April.
    8. Raquel Fonseca & Pierre-Carl Michaud & Arie Kapteyn & Titus Galama, 2013. "Accounting for the Rise of Health Spending and Longevity," Cahiers de recherche 1326, CIRPEE.
    9. Laurent Gobillon & Carine Milcent, 2016. "Evaluating the Effect of Ownership Status on Hospital Quality: The Key Role of Innovative Procedures," Annals of Economics and Statistics, GENES, issue 121-122, pages 161-186.
    10. Daysal, N. Meltem, 2012. "Does uninsurance affect the health outcomes of the insured? Evidence from heart attack patients in California," Journal of Health Economics, Elsevier, vol. 31(4), pages 545-563.
    11. repec:kap:atlecj:v:45:y:2017:i:4:d:10.1007_s11293-017-9557-3 is not listed on IDEAS
    12. Jing Hua Zhang, 2015. "Bend the healthcare cost curve without pain? The health outcome after the Medicare reimbursement cut in 1997," International Journal of Health Planning and Management, Wiley Blackwell, vol. 30(2), pages 164-172, April.
    13. Jill R. Horwitz & Charleen Hsuan & Austin Nichols, 2017. "The Role of Hospital and Market Characteristics in Invasive Cardiac Service Diffusion," NBER Working Papers 23530, National Bureau of Economic Research, Inc.
    14. Spyros Arvanitis & Euripidis N. Loukis, 2014. "Investigating the effects of ICT on innovation and performance of European hospitals," KOF Working papers 14-366, KOF Swiss Economic Institute, ETH Zurich.
    15. Amitabh Chandra & Amy Finkelstein & Adam Sacarny & Chad Syverson, 2013. "Healthcare Exceptionalism? Productivity and Allocation in the U.S. Healthcare Sector," NBER Working Papers 19200, National Bureau of Economic Research, Inc.

    More about this item

    JEL classification:

    • H51 - Public Economics - - National Government Expenditures and Related Policies - - - Government Expenditures and Health
    • I1 - Health, Education, and Welfare - - Health
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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