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Forecasting coronary heart disease incidence, mortality, and cost: The coronary heart disease policy model

Author

Listed:
  • Weinstein, M.C.
  • Coxson, P.G.
  • Williams, L.W.
  • Pass, T.M.
  • Stason, W.B.
  • Goldman, L.

Abstract

A computer simulation model was developed to project the future mortality, morbidity, and cost of coronary heart disease (CHD) in the United States population. The model contains a demographic-epidemiologic (DE) submodel, which simulates the distribution of coronary risk factors and the conditional incidence of CHD in a demographically evolving population; a 'bridge' submodel, which determines the outcome of the initial CHD event; and a disease history (DH) submodel, which simulates subsequent events in persons with a previous CHD event. The user of the model may simulate the effects of interventions, either preventive (i.e., risk factor modification) or therapeutic, upon mortality, morbidity, and cost for up to a 30-year period. If there were no future changes in risk factors or the efficacy of therapies after 1980, baseline projections indicate that the aging of the population, and especially the maturation of the post-World War II baby-boom generation, would increase CHD prevalence and annual incidence, mortality, and costs by about 40-50 per cent by the year 2010. Unprecedented reductions in risk factors would be required to offset these demographic effects on the absolute incidence of CHD. The specific forecasts could be inaccurate, however, as a consequence of erroneous assumptions or misestimated baseline data, and the model awaits validation based on actual future data.

Suggested Citation

  • Weinstein, M.C. & Coxson, P.G. & Williams, L.W. & Pass, T.M. & Stason, W.B. & Goldman, L., 1987. "Forecasting coronary heart disease incidence, mortality, and cost: The coronary heart disease policy model," American Journal of Public Health, American Public Health Association, vol. 77(11), pages 1417-1426.
  • Handle: RePEc:aph:ajpbhl:1987:77:11:1417-1426_6
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    Cited by:

    1. 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.
    2. 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.
    3. Ankur Pandya & Stephen Sy & Sylvia Cho & Sartaj Alam & Milton C. Weinstein & Thomas A. Gaziano, 2017. "Validation of a Cardiovascular Disease Policy Microsimulation Model Using Both Survival and Receiver Operating Characteristic Curves," Medical Decision Making, , vol. 37(7), pages 802-814, October.
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    12. Meltzer, David, 1997. "Accounting for future costs in medical cost-effectiveness analysis," Journal of Health Economics, Elsevier, vol. 16(1), pages 33-64, February.
    13. Rasstrigin, M. & Kitaev, A. & Pleshackova, E., 2023. "Forecasting spending on orphan diseases to maintain the long-run financial sustainability of healthcare system," Journal of the New Economic Association, New Economic Association, vol. 59(2), pages 120-141.
    14. Mark Roberts & Louise B. Russell & A. David Paltiel & Michael Chambers & Phil McEwan & Murray Krahn, 2012. "Conceptualizing a Model," Medical Decision Making, , vol. 32(5), pages 678-689, September.
    15. William S. Weintraub & Samuel S. Gidding, 2016. "PCSK9 Inhibitors: A Technology Worth Paying For?," PharmacoEconomics, Springer, vol. 34(3), pages 217-220, March.
    16. William Weintraub & Samuel Gidding, 2016. "PCSK9 Inhibitors: A Technology Worth Paying For?," PharmacoEconomics, Springer, vol. 34(3), pages 217-220, March.
    17. James E. Smith & Ralph L. Keeney, 2005. "Your Money or Your Life: A Prescriptive Model for Health, Safety, and Consumption Decisions," Management Science, INFORMS, vol. 51(9), pages 1309-1325, September.
    18. Bob J. H. van Kempen & Bart S. Ferket & Albert Hofman & Sandra Spronk & Ewout Steyerberg & M. G. Myriam Hunink, 2012. "Do Different Methods of Modeling Statin Treatment Effectiveness Influence the Optimal Decision?," Medical Decision Making, , vol. 32(3), pages 507-516, May.
    19. Paul Heidenreich & Mark B. McClellan, 2001. "Trends in Heart Attack Treatment and Outcomes, 1975-1995 -- Literature Review and Synthesis," NBER Chapters, in: Medical Care Output and Productivity, pages 363-410, National Bureau of Economic Research, Inc.
    20. Yizhe Xu & Tom H. Greene & Adam P. Bress & Brian C. Sauer & Brandon K. Bellows & Yue Zhang & William S. Weintraub & Andrew E. Moran & Jincheng Shen, 2022. "Estimating the optimal individualized treatment rule from a cost‐effectiveness perspective," Biometrics, The International Biometric Society, vol. 78(1), pages 337-351, March.
    21. Karen T. Hicklin & Julie S. Ivy & James R. Wilson & Fay Cobb Payton & Meera Viswanathan & Evan R. Myers, 2019. "Simulation model of the relationship between cesarean section rates and labor duration," Health Care Management Science, Springer, vol. 22(4), pages 635-657, December.
    22. Marion S. Rauner & Walter J. Gutjahr & Kurt Heidenberger & Joachim Wagner & Joseph Pasia, 2010. "Dynamic Policy Modeling for Chronic Diseases: Metaheuristic-Based Identification of Pareto-Optimal Screening Strategies," Operations Research, INFORMS, vol. 58(5), pages 1269-1286, October.
    23. Amy O’Sullivan & Jaime Rubin & Joshua Nyambose & Andreas Kuznik & David Cohen & David Thompson, 2011. "Cost Estimation of Cardiovascular Disease Events in the US," PharmacoEconomics, Springer, vol. 29(8), pages 693-704, August.
    24. Salkeld, Glenn & Phongsavan, Philayrath & Oldenburg, Brian & Johannesson, Magnus & Convery, Paula & Graham-Clarke, Peita & Walker, Sheila & Shaw, John, 1997. "The cost-effectiveness of a cardiovascular risk reduction program in general practice," Health Policy, Elsevier, vol. 41(2), pages 105-119, August.
    25. Fildes, Robert, 2006. "The forecasting journals and their contribution to forecasting research: Citation analysis and expert opinion," International Journal of Forecasting, Elsevier, vol. 22(3), pages 415-432.

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