Technology growth and expenditure growth in health care

In the United States, health care technology has contributed to rising survival rates, yet health care spending relative to gross domestic product (GDP) has also grown more rapidly than in any other country, say researchers Amitabh Chandra and Jonathan S. Skinner.

Chandra and Skinner developed a model of patient demand and supplier behaviour to explain these parallel trends in technology growth and cost growth.

  • They 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 antiretroviral 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 intensive care unit days among chronically ill patients.
  • 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.

    Source: Amitabh Chandra and Jonathan S. Skinner, Technology Growth and Expenditure Growth in Health Care, National Bureau of Economic Research, April 2011.

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    First published by the National Center for Policy Analysis, United States

    FMF Policy Bulletin/ 10 May 2011
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