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Using Diagnoses to Describe Populations and Predict Costs
The Diagnostic Cost Group Hierarchical Condition Category (DCG/HCC) payment models summarize the health care problems and predict the future health care costs of populations. These models use the diagnoses generated during patient encounters with the medical delivery system to infer which medical pr...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
CENTERS for MEDICARE & MEDICAID SERVICES
2000
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4194673/ https://www.ncbi.nlm.nih.gov/pubmed/11481769 |
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author | Ash, Arlene S. Ellis, Randall P. Pope, Gregory C. Ayanian, John Z. Bates, David W. Burstin, Helen Iezzoni, Lisa I. MacKay, Elizabeth Yu, Wei |
author_facet | Ash, Arlene S. Ellis, Randall P. Pope, Gregory C. Ayanian, John Z. Bates, David W. Burstin, Helen Iezzoni, Lisa I. MacKay, Elizabeth Yu, Wei |
author_sort | Ash, Arlene S. |
collection | PubMed |
description | The Diagnostic Cost Group Hierarchical Condition Category (DCG/HCC) payment models summarize the health care problems and predict the future health care costs of populations. These models use the diagnoses generated during patient encounters with the medical delivery system to infer which medical problems are present. Patient demographics and diagnostic profiles are, in turn, used to predict costs. We describe the logic, structure, coefficients and performance of DCG/HCC models, as developed and validated on three important data bases (privately insured, Medicaid, and Medicare) with more than 1 million people each. |
format | Online Article Text |
id | pubmed-4194673 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2000 |
publisher | CENTERS for MEDICARE & MEDICAID SERVICES |
record_format | MEDLINE/PubMed |
spelling | pubmed-41946732014-11-04 Using Diagnoses to Describe Populations and Predict Costs Ash, Arlene S. Ellis, Randall P. Pope, Gregory C. Ayanian, John Z. Bates, David W. Burstin, Helen Iezzoni, Lisa I. MacKay, Elizabeth Yu, Wei Health Care Financ Rev Research Article The Diagnostic Cost Group Hierarchical Condition Category (DCG/HCC) payment models summarize the health care problems and predict the future health care costs of populations. These models use the diagnoses generated during patient encounters with the medical delivery system to infer which medical problems are present. Patient demographics and diagnostic profiles are, in turn, used to predict costs. We describe the logic, structure, coefficients and performance of DCG/HCC models, as developed and validated on three important data bases (privately insured, Medicaid, and Medicare) with more than 1 million people each. CENTERS for MEDICARE & MEDICAID SERVICES 2000 /pmc/articles/PMC4194673/ /pubmed/11481769 Text en |
spellingShingle | Research Article Ash, Arlene S. Ellis, Randall P. Pope, Gregory C. Ayanian, John Z. Bates, David W. Burstin, Helen Iezzoni, Lisa I. MacKay, Elizabeth Yu, Wei Using Diagnoses to Describe Populations and Predict Costs |
title | Using Diagnoses to Describe Populations and Predict Costs |
title_full | Using Diagnoses to Describe Populations and Predict Costs |
title_fullStr | Using Diagnoses to Describe Populations and Predict Costs |
title_full_unstemmed | Using Diagnoses to Describe Populations and Predict Costs |
title_short | Using Diagnoses to Describe Populations and Predict Costs |
title_sort | using diagnoses to describe populations and predict costs |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4194673/ https://www.ncbi.nlm.nih.gov/pubmed/11481769 |
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