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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
Ash, Arlene S.
Ellis, Randall P.
Pope, Gregory C.
Ayanian, John Z.
Bates, David W.
Burstin, Helen
Iezzoni, Lisa I.
MacKay, Elizabeth
Yu, Wei
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UMass Chan Affiliations
Document Type
Journal Article
Publication Date
2001-08-03
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Abstract
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.
Source
Health Care Financ Rev. 2000 Spring;21(3):7-28. Link to article on publisher's site
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PubMed ID
11481769