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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Main Authors: Igor Akushevich, Julia Kravchenko, Lucy Akushevich, Svetlana Ukraintseva, Konstantin Arbeev, Anatoliy I. Yashin
Format: Article
Language:English
Published: Hindawi Limited 2011-01-01
Series:Computational and Mathematical Methods in Medicine
Online Access:http://dx.doi.org/10.1155/2011/857892
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spelling 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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