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Tradeoffs in cardiovascular disease prevention, treatment, and research

Author

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  • George Miller

  • Matthew Daly
  • Charles Roehrig

Abstract

It is widely believed that the US health care system needs to transition from a culture of reactive treatment of disease to one of proactive prevention. As a tool for understanding the appropriate allocation of spending to prevention versus treatment (including research into improved prevention and treatment), a simple Markov model is used to represent the flow of individuals among states of health, where the transition rates are governed by the magnitude of appropriately-lagged expenditures in each of these categories. The model estimates the discounted cost and discounted effectiveness (measured in quality adjusted life years or QALYs) associated with a given spending mix, and it allows computing the marginal cost-effectiveness associated with additional spending in a category. We apply the model to explore interactions of alternative investments in cardiovascular disease (CVD) and to identify an optimal spending mix. Under the assumptions of our model structure, we find that the marginal cost-effectiveness of prevention of CVD varies with changes in spending on treatment (and vice versa), and that the optimal mix of CVD spending (i.e., the spending mix that maximizes the overall QALYs achieved) would, indeed, shift spending from treatment to prevention. Copyright Springer Science+Business Media New York 2013

Suggested Citation

  • George Miller & Matthew Daly & Charles Roehrig, 2013. "Tradeoffs in cardiovascular disease prevention, treatment, and research," Health Care Management Science, Springer, vol. 16(2), pages 87-100, June.
    • Handle: RePEc:kap:hcarem:v:16:y:2013:i:2:p:87-100
    DOI: 10.1007/s10729-012-9215-x
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    References listed on IDEAS

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    1. Jonathan Skinner & Douglas Staiger, 2015. "Technology Diffusion and Productivity Growth in Health Care," The Review of Economics and Statistics, MIT Press, vol. 97(5), pages 951-964, December.
    2. Frank R. Lichtenberg, 2006. "The Impact of New Laboratory Procedures and Other Medical Innovations on the Health of Americans, 1990-2003: Evidence from Longitudinal, Disease-Level Data," NBER Working Papers 12120, National Bureau of Economic Research, Inc.
    3. Homer, J.B. & Hirsch, G.B., 2006. "System dynamics modeling for public health: Background and opportunities," American Journal of Public Health, American Public Health Association, vol. 96(3), pages 452-458.
    4. Tassey, Gregory, 2005. "The disaggregated technology production function: A new model of university and corporate research," Research Policy, Elsevier, vol. 34(3), pages 287-303, April.
    5. Heffley, Dennis R., 1982. "Allocating health expenditures to treatment and prevention," Journal of Health Economics, Elsevier, vol. 1(3), pages 265-290, December.
    6. Frank R. Lichtenberg, 2014. "Has Medical Innovation Reduced Cancer Mortality?," CESifo Economic Studies, CESifo Group, vol. 60(1), pages 135-177.
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