Medical cost trajectories and onsets of cancer and noncancer diseases in US elderly population.
| dc.contributor.author | Akushevich, Igor | |
| dc.contributor.author | Kravchenko, Julia | |
| dc.contributor.author | Akushevich, Lucy | |
| dc.contributor.author | Ukraintseva, Svetlana | |
| dc.contributor.author | Arbeev, Konstantin | |
| dc.contributor.author | Yashin, Anatoliy I | |
| dc.contributor.editor | Busso, Thierry | |
| dc.coverage.spatial | United States | |
| dc.date.accessioned | 2017-06-06T17:17:44Z | |
| dc.date.available | 2017-06-06T17:17:44Z | |
| dc.date.issued | 2011 | |
| dc.description.abstract | 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. | |
| dc.identifier | ||
| dc.identifier.eissn | 1748-6718 | |
| dc.identifier.uri | ||
| dc.language | eng | |
| dc.publisher | Hindawi Limited | |
| dc.relation.ispartof | Comput Math Methods Med | |
| dc.relation.isversionof | 10.1155/2011/857892 | |
| dc.subject | Aged | |
| dc.subject | Aged, 80 and over | |
| dc.subject | Chronic Disease | |
| dc.subject | Cohort Studies | |
| dc.subject | Comorbidity | |
| dc.subject | Computer Simulation | |
| dc.subject | Data Collection | |
| dc.subject | Female | |
| dc.subject | Forecasting | |
| dc.subject | Health Care Costs | |
| dc.subject | Humans | |
| dc.subject | Male | |
| dc.subject | Medicare | |
| dc.subject | Models, Economic | |
| dc.subject | Models, Statistical | |
| dc.subject | Neoplasms | |
| dc.subject | United States | |
| dc.title | Medical cost trajectories and onsets of cancer and noncancer diseases in US elderly population. | |
| dc.type | Journal article | |
| duke.contributor.orcid | Arbeev, Konstantin|0000-0002-4195-7832 | |
| pubs.author-url | ||
| pubs.begin-page | 857892 | |
| pubs.organisational-group | Center for Population Health & Aging | |
| pubs.organisational-group | Clinical Science Departments | |
| pubs.organisational-group | Duke | |
| pubs.organisational-group | Duke Cancer Institute | |
| pubs.organisational-group | Duke Population Research Center | |
| pubs.organisational-group | Duke Population Research Institute | |
| pubs.organisational-group | Institutes and Centers | |
| pubs.organisational-group | Institutes and Provost's Academic Units | |
| pubs.organisational-group | Physics | |
| pubs.organisational-group | Sanford School of Public Policy | |
| pubs.organisational-group | School of Medicine | |
| pubs.organisational-group | Social Science Research Institute | |
| pubs.organisational-group | Staff | |
| pubs.organisational-group | Surgery | |
| pubs.organisational-group | Surgery, Surgical Sciences | |
| pubs.organisational-group | Trinity College of Arts & Sciences | |
| pubs.organisational-group | University Institutes and Centers | |
| pubs.publication-status | Published | |
| pubs.volume | 2011 |
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