Performance of comorbidity, risk adjustment, and functional status measures in expenditure prediction for patients with diabetes.

Journal Article (Journal Article)

OBJECTIVE: To compare the ability of generic comorbidity and risk adjustment measures, a diabetes-specific measure, and a self-reported functional status measure to explain variation in health care expenditures for individuals with diabetes. RESEARCH DESIGN AND METHODS: This study included a retrospective cohort of 3,092 diabetic veterans participating in a multisite trial. Two comorbidity measures, four risk adjusters, a functional status measure, a diabetes complication count, and baseline expenditures were constructed from administrative and survey data. Outpatient, inpatient, and total expenditure models were estimated using ordinary least squares regression. Adjusted R(2) statistics and predictive ratios were compared across measures to assess overall explanatory power and explanatory power of low- and high-cost subgroups. RESULTS: Administrative data-based risk adjusters performed better than the comorbidity, functional status, and diabetes-specific measures in all expenditure models. The diagnostic cost groups (DCGs) measure had the greatest predictive power overall and for the low- and high-cost subgroups, while the diabetes-specific measure had the lowest predictive power. A model with DCGs and the diabetes-specific measure modestly improved predictive power. CONCLUSIONS: Existing generic measures can be useful for diabetes-specific research and policy applications, but more predictive diabetes-specific measures are needed.

Full Text

Duke Authors

Cited Authors

  • Maciejewski, ML; Liu, C-F; Fihn, SD

Published Date

  • January 2009

Published In

Volume / Issue

  • 32 / 1

Start / End Page

  • 75 - 80

PubMed ID

  • 18945927

Pubmed Central ID

  • PMC2606834

Electronic International Standard Serial Number (EISSN)

  • 1935-5548

Digital Object Identifier (DOI)

  • 10.2337/dc08-1099


  • eng

Conference Location

  • United States