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Bioactuarial Models of National Mortality Time Series Data

The incidence and prevalence of chronic degenerative disease in America's elderly population are important determinants of the need for long-term care health services. Though a wide range of data on disease incidence and prevalence is available from a variety of different health studies, a Cong...

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Detalles Bibliográficos
Autores principales: Manton, Kenneth G., Stallard, Eric
Formato: Online Artículo Texto
Lenguaje:English
Publicado: CENTERS for MEDICARE & MEDICAID SERVICES 1982
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4191260/
https://www.ncbi.nlm.nih.gov/pubmed/10309604
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author Manton, Kenneth G.
Stallard, Eric
author_facet Manton, Kenneth G.
Stallard, Eric
author_sort Manton, Kenneth G.
collection PubMed
description The incidence and prevalence of chronic degenerative disease in America's elderly population are important determinants of the need for long-term care health services. Though a wide range of data on disease incidence and prevalence is available from a variety of different health studies, a Congressional Budget Office study (1977) concluded that data limitations are a major factor in the lack of precise national long-term care cost estimates. In this paper, we present a modeling strategy to make better use of existing data by using biomedically motivated actuarial models to integrate multiple data sources into a comprehensive model of population health dynamics. The development of a specific model for application to a disease of interest involves three distinct phases. First, biomedical evidence and data are used to specify a cohort model of chronic disease morbidity and mortality. Second, the model is fitted to cohort mortality data with estimates of its parameters being derived by maximum likelihood procedures. Third, the morbidity distribution in the national population is generated from the parameter estimates. The model is used to examine lung cancer morbidity and mortality patterns for U. S. white and non-white males in 1977. A review of these patterns suggests that, based on current concepts of lung cancer incidence and natural history, over 2 percent of white males in the United States have lung cancer at some stage of development, though most of this prevalence is pre-clinical. The likelihood that these clinically latent morbid patterns will translate into future health care needs is a function not only of incidence and natural history of lung cancer in different birth cohorts, but also of changes in the mortality patterns of other diseases. The model demonstrates that, if for other chronic degenerative diseases a large proportion of future health care needs is determined in the present health state of the population, long-range planning models of national population health dynamics are necessary to anticipate and meet future requirements for long-term care health services.
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spelling pubmed-41912602014-11-04 Bioactuarial Models of National Mortality Time Series Data Manton, Kenneth G. Stallard, Eric Health Care Financ Rev Original Research Article The incidence and prevalence of chronic degenerative disease in America's elderly population are important determinants of the need for long-term care health services. Though a wide range of data on disease incidence and prevalence is available from a variety of different health studies, a Congressional Budget Office study (1977) concluded that data limitations are a major factor in the lack of precise national long-term care cost estimates. In this paper, we present a modeling strategy to make better use of existing data by using biomedically motivated actuarial models to integrate multiple data sources into a comprehensive model of population health dynamics. The development of a specific model for application to a disease of interest involves three distinct phases. First, biomedical evidence and data are used to specify a cohort model of chronic disease morbidity and mortality. Second, the model is fitted to cohort mortality data with estimates of its parameters being derived by maximum likelihood procedures. Third, the morbidity distribution in the national population is generated from the parameter estimates. The model is used to examine lung cancer morbidity and mortality patterns for U. S. white and non-white males in 1977. A review of these patterns suggests that, based on current concepts of lung cancer incidence and natural history, over 2 percent of white males in the United States have lung cancer at some stage of development, though most of this prevalence is pre-clinical. The likelihood that these clinically latent morbid patterns will translate into future health care needs is a function not only of incidence and natural history of lung cancer in different birth cohorts, but also of changes in the mortality patterns of other diseases. The model demonstrates that, if for other chronic degenerative diseases a large proportion of future health care needs is determined in the present health state of the population, long-range planning models of national population health dynamics are necessary to anticipate and meet future requirements for long-term care health services. CENTERS for MEDICARE & MEDICAID SERVICES 1982-03 /pmc/articles/PMC4191260/ /pubmed/10309604 Text en
spellingShingle Original Research Article
Manton, Kenneth G.
Stallard, Eric
Bioactuarial Models of National Mortality Time Series Data
title Bioactuarial Models of National Mortality Time Series Data
title_full Bioactuarial Models of National Mortality Time Series Data
title_fullStr Bioactuarial Models of National Mortality Time Series Data
title_full_unstemmed Bioactuarial Models of National Mortality Time Series Data
title_short Bioactuarial Models of National Mortality Time Series Data
title_sort bioactuarial models of national mortality time series data
topic Original Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4191260/
https://www.ncbi.nlm.nih.gov/pubmed/10309604
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