Medical Cost Trajectories and Onsets of Cancer and NonCancer Diseases in US Elderly Population
Time trajectories of medical costs-associated with onset of twelve aging-related cancer and chronic noncancer diseases were analyzed using the National Long-Term Care Survey data linked to Medicare Service Use files. A special procedure for selecting individuals with onset of each disease was develo...
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Series: | Computational and Mathematical Methods in Medicine |
Online Access: | http://dx.doi.org/10.1155/2011/857892 |
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doaj-9acc43120e864536a7c54cfc5890bd332020-11-24T23:19:47ZengHindawi LimitedComputational and Mathematical Methods in Medicine1748-670X1748-67182011-01-01201110.1155/2011/857892857892Medical Cost Trajectories and Onsets of Cancer and NonCancer Diseases in US Elderly PopulationIgor Akushevich0Julia Kravchenko1Lucy Akushevich2Svetlana Ukraintseva3Konstantin Arbeev4Anatoliy I. Yashin5Center for Population Health and Aging, Duke University, Durham, NC 27708, USADuke Cancer Institute, Duke University, Durham, NC 27705, USADuke Cancer Institute, Duke University, Durham, NC 27705, USACenter for Population Health and Aging, Duke University, Durham, NC 27708, USACenter for Population Health and Aging, Duke University, Durham, NC 27708, USACenter for Population Health and Aging, Duke University, Durham, NC 27708, USATime trajectories of medical costs-associated with onset of twelve aging-related cancer and chronic noncancer diseases were analyzed using the National Long-Term Care Survey data linked to Medicare Service Use files. A special procedure for selecting individuals with onset of each disease was developed and used for identification of the date at disease onset. Medical cost trajectories were found to be represented by a parametric model with four easily interpretable parameters reflecting: (i) prediagnosis cost (associated with initial comorbidity), (ii) cost of the disease onset, (iii) population recovery representing reduction of the medical expenses associated with a disease since diagnosis was made, and (iv) acquired comorbidity representing the difference between post- and pre diagnosis medical cost levels. These parameters were evaluated for the entire US population as well as for the subpopulation conditional on age, disability and comorbidity states, and survival (2.5 years after the date of onset). The developed approach results in a family of new forecasting models with covariates.http://dx.doi.org/10.1155/2011/857892 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Igor Akushevich Julia Kravchenko Lucy Akushevich Svetlana Ukraintseva Konstantin Arbeev Anatoliy I. Yashin |
spellingShingle |
Igor Akushevich Julia Kravchenko Lucy Akushevich Svetlana Ukraintseva Konstantin Arbeev Anatoliy I. Yashin Medical Cost Trajectories and Onsets of Cancer and NonCancer Diseases in US Elderly Population Computational and Mathematical Methods in Medicine |
author_facet |
Igor Akushevich Julia Kravchenko Lucy Akushevich Svetlana Ukraintseva Konstantin Arbeev Anatoliy I. Yashin |
author_sort |
Igor Akushevich |
title |
Medical Cost Trajectories and Onsets of Cancer and NonCancer Diseases in US Elderly Population |
title_short |
Medical Cost Trajectories and Onsets of Cancer and NonCancer Diseases in US Elderly Population |
title_full |
Medical Cost Trajectories and Onsets of Cancer and NonCancer Diseases in US Elderly Population |
title_fullStr |
Medical Cost Trajectories and Onsets of Cancer and NonCancer Diseases in US Elderly Population |
title_full_unstemmed |
Medical Cost Trajectories and Onsets of Cancer and NonCancer Diseases in US Elderly Population |
title_sort |
medical cost trajectories and onsets of cancer and noncancer diseases in us elderly population |
publisher |
Hindawi Limited |
series |
Computational and Mathematical Methods in Medicine |
issn |
1748-670X 1748-6718 |
publishDate |
2011-01-01 |
description |
Time trajectories of medical costs-associated with onset of twelve aging-related cancer and chronic noncancer diseases were analyzed using the National Long-Term Care Survey data linked to Medicare Service Use files. A special procedure for selecting individuals with onset of each disease was developed and used for identification of the date at disease onset. Medical cost trajectories were found to be represented by a parametric model with four easily interpretable parameters reflecting: (i) prediagnosis cost (associated with initial comorbidity), (ii) cost of the disease onset, (iii) population recovery representing reduction of the medical expenses associated with a disease since diagnosis was made, and (iv) acquired comorbidity representing the difference between post- and pre diagnosis medical cost levels. These parameters were evaluated for the entire US population as well as for the subpopulation conditional on age, disability and comorbidity states, and survival (2.5 years after the date of onset). The developed approach results in a family of new forecasting models with covariates. |
url |
http://dx.doi.org/10.1155/2011/857892 |
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