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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.

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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 14865.

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Date of creation: Apr 2009
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Handle: RePEc:nbr:nberwo:14865
Note: AG HC PR
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  8. repec:cup:cbooks:9780521851442 is not listed on IDEAS
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  10. Eaton, Jonathan & Kortum, Samuel, 1999. "International Technology Diffusion: Theory and Measurement," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 40(3), pages 537-70, August.
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  17. Coleman, Wilbur II, 2004. "Comment on: "Cross-country technology adoption: making the theories face the facts"," Journal of Monetary Economics, Elsevier, vol. 51(1), pages 85-87, January.
  18. Phelps, Charles E., 2000. "Information diffusion and best practice adoption," Handbook of Health Economics, in: A. J. Culyer & J. P. Newhouse (ed.), Handbook of Health Economics, edition 1, volume 1, chapter 5, pages 223-264 Elsevier.
  19. Parente, Stephen L & Prescott, Edward C, 1994. "Barriers to Technology Adoption and Development," Journal of Political Economy, University of Chicago Press, vol. 102(2), pages 298-321, April.
  20. David M. Cutler & Mark McClellan & Joseph P. Newhouse & Dahlia Remler, 1998. "Are Medical Prices Declining? Evidence From Heart Attack Treatments," The Quarterly Journal of Economics, MIT Press, vol. 113(4), pages 991-1024, November.
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