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Diagnosis-Based Risk Adjustment for Medicare Capitation Payments

Using 1991-92 data for a 5-percent Medicare sample, we develop, estimate, and evaluate risk-adjustment models that utilize diagnostic information from both inpatient and ambulatory claims to adjust payments for aged and disabled Medicare enrollees. Hierarchical coexisting conditions (HCC) models ach...

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Detalles Bibliográficos
Autores principales: Ellis, Randall P., Pope, Gregory C., Iezzoni, Lisa I., Ayanian, John Z., Bates, David W., Burstin, Helen, Ash, Arlene S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: CENTERS for MEDICARE & MEDICAID SERVICES 1996
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4193604/
https://www.ncbi.nlm.nih.gov/pubmed/10172666
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author Ellis, Randall P.
Pope, Gregory C.
Iezzoni, Lisa I.
Ayanian, John Z.
Bates, David W.
Burstin, Helen
Ash, Arlene S.
author_facet Ellis, Randall P.
Pope, Gregory C.
Iezzoni, Lisa I.
Ayanian, John Z.
Bates, David W.
Burstin, Helen
Ash, Arlene S.
author_sort Ellis, Randall P.
collection PubMed
description Using 1991-92 data for a 5-percent Medicare sample, we develop, estimate, and evaluate risk-adjustment models that utilize diagnostic information from both inpatient and ambulatory claims to adjust payments for aged and disabled Medicare enrollees. Hierarchical coexisting conditions (HCC) models achieve greater explanatory power than diagnostic cost group (DCG) models by taking account of multiple coexisting medical conditions. Prospective models predict average costs of individuals with chronic conditions nearly as well as concurrent models. All models predict medical costs far more accurately than the current health maintenance organization (HMO) payment formula.
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spelling pubmed-41936042014-11-04 Diagnosis-Based Risk Adjustment for Medicare Capitation Payments Ellis, Randall P. Pope, Gregory C. Iezzoni, Lisa I. Ayanian, John Z. Bates, David W. Burstin, Helen Ash, Arlene S. Health Care Financ Rev Managed Care: Advances in Financing Using 1991-92 data for a 5-percent Medicare sample, we develop, estimate, and evaluate risk-adjustment models that utilize diagnostic information from both inpatient and ambulatory claims to adjust payments for aged and disabled Medicare enrollees. Hierarchical coexisting conditions (HCC) models achieve greater explanatory power than diagnostic cost group (DCG) models by taking account of multiple coexisting medical conditions. Prospective models predict average costs of individuals with chronic conditions nearly as well as concurrent models. All models predict medical costs far more accurately than the current health maintenance organization (HMO) payment formula. CENTERS for MEDICARE & MEDICAID SERVICES 1996 /pmc/articles/PMC4193604/ /pubmed/10172666 Text en
spellingShingle Managed Care: Advances in Financing
Ellis, Randall P.
Pope, Gregory C.
Iezzoni, Lisa I.
Ayanian, John Z.
Bates, David W.
Burstin, Helen
Ash, Arlene S.
Diagnosis-Based Risk Adjustment for Medicare Capitation Payments
title Diagnosis-Based Risk Adjustment for Medicare Capitation Payments
title_full Diagnosis-Based Risk Adjustment for Medicare Capitation Payments
title_fullStr Diagnosis-Based Risk Adjustment for Medicare Capitation Payments
title_full_unstemmed Diagnosis-Based Risk Adjustment for Medicare Capitation Payments
title_short Diagnosis-Based Risk Adjustment for Medicare Capitation Payments
title_sort diagnosis-based risk adjustment for medicare capitation payments
topic Managed Care: Advances in Financing
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4193604/
https://www.ncbi.nlm.nih.gov/pubmed/10172666
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