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Forecasting Health Status Changes in an Aging U.S. Population: Assessment of the Current Status and Some Proposals

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Forecasting in the Social and Natural Sciences

Abstract

Much interest has been recently focused on forecasting population health changes such as population aging and life expectancy increases at advanced ages, qualitative changes in health and survival, changes in federal reimbursement systems, and the need to forecast for long-range capital investment in specialized health facilities. Recent efforts at forecasting health and morbidity changes in the population are reviewed in this paper and the recent lack of methodological innovation in health forecasting strategies is examined. Two forecasting models—stochastic compartmental systems and mixed multivariate continuous state-discrete state processes—are described. We show how these models can be applied to health forecasting using existing data, how they can be used in a complementary fashion to improve health projections made from any one type of data, and how the mixed multivariate stochastic process model can be used to evaluate assumptions made in the compartment modeling approach.

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Author information

Authors and Affiliations

  1. Demographic Studies, Duke University, Durham, North Carolina, USA

    Kenneth G. Manton

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  1. Kenneth G. Manton
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Editors and Affiliations

  1. Department of Sociology, Duke University, Durham, NC, USA

    Kenneth C. Land

  2. N.C.A.R., Boulder, CO, USA

    Stephen H. Schneider

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© 1987 D. Reidel Publishing Company

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Manton, K.G. (1987). Forecasting Health Status Changes in an Aging U.S. Population: Assessment of the Current Status and Some Proposals. In: Land, K.C., Schneider, S.H. (eds) Forecasting in the Social and Natural Sciences. Springer, Dordrecht. https://doi.org/10.1007/978-94-009-4011-6_8

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  • DOI: https://doi.org/10.1007/978-94-009-4011-6_8

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-010-8279-2

  • Online ISBN: 978-94-009-4011-6

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