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Predictability of Prescription Drug Expenditures for Medicare Beneficiaries

MCBS data are used to analyze the predictability of drug expenditures by Medicare beneficiaries. Predictors include demographic characteristics and measures of health status, the majority derived using CMS' diagnosis cost group/hierarchical condition category (DCG/HCC) risk-adjustment methodolo...

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Autores principales: Wrobel, Marian V., Doshi, Jalpa, Stuart, Bruce C., Briesacher, Becky
Formato: Online Artículo Texto
Lenguaje:English
Publicado: CENTERS for MEDICARE & MEDICAID SERVICES 2003
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4194808/
https://www.ncbi.nlm.nih.gov/pubmed/15124376
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author Wrobel, Marian V.
Doshi, Jalpa
Stuart, Bruce C.
Briesacher, Becky
author_facet Wrobel, Marian V.
Doshi, Jalpa
Stuart, Bruce C.
Briesacher, Becky
author_sort Wrobel, Marian V.
collection PubMed
description MCBS data are used to analyze the predictability of drug expenditures by Medicare beneficiaries. Predictors include demographic characteristics and measures of health status, the majority derived using CMS' diagnosis cost group/hierarchical condition category (DCG/HCC) risk-adjustment methodology. In prospective models, demographic variables explained 5 percent of the variation in drug expenditures. Adding health status measures raised this figure between 10 and 24 percent of the variation depending on the model configuration. Adding lagged drug expenditures more than doubled predictive power to 55 percent. These results are discussed in the context of forecasting, and risk adjustment for the proposed new Medicare drug benefit.
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spelling pubmed-41948082014-11-04 Predictability of Prescription Drug Expenditures for Medicare Beneficiaries Wrobel, Marian V. Doshi, Jalpa Stuart, Bruce C. Briesacher, Becky Health Care Financ Rev Research Article MCBS data are used to analyze the predictability of drug expenditures by Medicare beneficiaries. Predictors include demographic characteristics and measures of health status, the majority derived using CMS' diagnosis cost group/hierarchical condition category (DCG/HCC) risk-adjustment methodology. In prospective models, demographic variables explained 5 percent of the variation in drug expenditures. Adding health status measures raised this figure between 10 and 24 percent of the variation depending on the model configuration. Adding lagged drug expenditures more than doubled predictive power to 55 percent. These results are discussed in the context of forecasting, and risk adjustment for the proposed new Medicare drug benefit. CENTERS for MEDICARE & MEDICAID SERVICES 2003 /pmc/articles/PMC4194808/ /pubmed/15124376 Text en
spellingShingle Research Article
Wrobel, Marian V.
Doshi, Jalpa
Stuart, Bruce C.
Briesacher, Becky
Predictability of Prescription Drug Expenditures for Medicare Beneficiaries
title Predictability of Prescription Drug Expenditures for Medicare Beneficiaries
title_full Predictability of Prescription Drug Expenditures for Medicare Beneficiaries
title_fullStr Predictability of Prescription Drug Expenditures for Medicare Beneficiaries
title_full_unstemmed Predictability of Prescription Drug Expenditures for Medicare Beneficiaries
title_short Predictability of Prescription Drug Expenditures for Medicare Beneficiaries
title_sort predictability of prescription drug expenditures for medicare beneficiaries
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4194808/
https://www.ncbi.nlm.nih.gov/pubmed/15124376
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