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Estimating clinical morbidity due to ischemic heart disease and congestive heart failure: The future rise of heart failure

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  • Bonneux, L.
  • Barendregt, J.J.
  • Meeter, K.
  • Bonsel, G.J.
  • Van der Maas, P.J.

Abstract

Objectives. Many developed countries have seen declining mortality rates for heart disease, together with an alleged decline in incidence and a seemingly paradoxical increase in health care demands. This paper presents a model for forecasting the plausible evolution of heart disease morbidity. Methods. The simulation model combines data from different sources. It generates acute coronary event and mortality rates from published data on incidences, recurrences, and lethalities of different heart disease conditions and interventions. Forecasts are based on plausible scenarios for declining incidence and increasing survival. Results. Mortality is postponed more than incidence. Prevalence rates of morbidity will decrease among the young and middle-aged but increase among the elderly. As the milder disease states act as risk factors for the more severe states, effects will culminate in the most severe disease states with a disproportionate increase in older people. Conclusions. Increasing health care needs in the face of declining mortality rates are no contradiction, but reflect a tradeoff of mortality for morbidity. The aging of the population will accentuate this morbidity increase.

Suggested Citation

  • Bonneux, L. & Barendregt, J.J. & Meeter, K. & Bonsel, G.J. & Van der Maas, P.J., 1994. "Estimating clinical morbidity due to ischemic heart disease and congestive heart failure: The future rise of heart failure," American Journal of Public Health, American Public Health Association, vol. 84(1), pages 20-28.
    • Handle: RePEc:aph:ajpbhl:1994:84:1:20-28_9
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    Cited by:

    1. Pierre-Carl Michaud & Dana Goldman & Darius Lakdawalla & Adam Gailey & Yuhui Zheng, 2009. "International Differences in Longevity and Health and their Economic Consequences," NBER Working Papers 15235, National Bureau of Economic Research, Inc.
    2. Davies, Ruth & Roderick, Paul & Raftery, James, 2003. "The evaluation of disease prevention and treatment using simulation models," European Journal of Operational Research, Elsevier, vol. 150(1), pages 53-66, October.
    3. K. Cooper & S. Brailsford & R. Davies & J. Raftery, 2006. "A review of health care models for coronary heart disease interventions," Health Care Management Science, Springer, vol. 9(4), pages 311-324, November.
    4. Pierre-Carl Michaud & Dana Goldman & Darius Lakdawalla & Yuhui Zheng & Adam Gailey, 2009. "Understanding the Economic Consequences of Shifting Trends in Population Health," NBER Working Papers 15231, National Bureau of Economic Research, Inc.
    5. Atanasijević-Kunc, M. & Drinovec, J. & Ručigaj, S. & Mrhar, A., 2011. "Simulation analysis of coronary heart disease, congestive heart failure and end-stage renal disease economic burden," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 82(3), pages 494-507.
    6. Mark Hayward & Melonie Heron, 1999. "Racial inequality in active life among adult americans," Demography, Springer;Population Association of America (PAA), vol. 36(1), pages 77-91, February.
    7. Eileen Crimmins & Yasuhiko Saito, 2000. "Change in the Prevalence of Diseases Among Older Americans: 1984-1994," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 3(9).

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