Comparison of the predictive validity of diagnosis-based risk adjusters for clinical outcomes

Laura A. Petersen, Kenneth Pietz, LeChauncy D. Woodard, Margaret M Byrne

Research output: Contribution to journalArticle

102 Citations (Scopus)

Abstract

Objectives: Many possible methods of risk adjustment exist, but there is a dearth of comparative data on their performance. We compared the predictive validity of 2 widely used methods (Diagnostic Cost Groups [DCGs] and Adjusted Clinical Groups [ACGs]) for 2 clinical outcomes using a large national sample of patients. Methods: We studied all patients who used Veterans Health Administration (VA) medical services in fiscal year (FY) 2001 (n = 3,069,168) and assigned both a DCG and an ACG to each. We used logistic regression analyses to compare predictive ability for death or long-term care (LTC) hospitalization for age/gender models, DCG models, and ACG models. We also assessed the effect of adding age to the DCG and ACG models. Results: Patients in the highest DCG categories, indicating higher severity of illness, were more likely to die or to require LTC hospitalization. Surprisingly, the age/gender model predicted death slightly more accurately than the ACG model (c-statistic of 0.710 versus 0.700, respectively). The addition of age to the ACG model improved the c-statistic to 0.768. The highest c-statistic for prediction of death was obtained with a DCG/age model (0.830). The lowest c-statistics were obtained for age/gender models for LTC hospitalization (c-statistic 0.593). The c-statistic for use of ACGs to predict LTC hospitalization was 0.783, and improved to 0.792 with the addition of age. The c-statistics for use of DCGs and DCG/age to predict LTC hospitalization were 0.885 and 0.890, respectively, indicating the best prediction. Conclusions: We found that risk adjusters based upon diagnoses predicted an increased likelihood of death or LTC hospitalization, exhibiting good predictive validity. In this comparative analysis using VA data, DCG models were generally superior to ACG models in predicting clinical outcomes, although ACG model performance was enhanced by the addition of age.

Original languageEnglish
Pages (from-to)61-67
Number of pages7
JournalMedical Care
Volume43
Issue number1
StatePublished - Jan 1 2005

Fingerprint

Long-Term Care
Costs and Cost Analysis
Hospitalization
diagnostic
Group
hospitalization
statistics
Veterans Health
costs
United States Department of Veterans Affairs
Age Groups
death
Risk Adjustment
age group
gender
Logistic Models
risk adjustment
Regression Analysis
medical services
health

Keywords

  • Adjusted clinical groups
  • Age
  • Capitation
  • Diagnostic cost groups
  • Long-term care
  • Mortality
  • Predictive validity
  • Risk adjustment

ASJC Scopus subject areas

  • Nursing(all)
  • Public Health, Environmental and Occupational Health
  • Health(social science)
  • Health Professions(all)

Cite this

Petersen, L. A., Pietz, K., Woodard, L. D., & Byrne, M. M. (2005). Comparison of the predictive validity of diagnosis-based risk adjusters for clinical outcomes. Medical Care, 43(1), 61-67.

Comparison of the predictive validity of diagnosis-based risk adjusters for clinical outcomes. / Petersen, Laura A.; Pietz, Kenneth; Woodard, LeChauncy D.; Byrne, Margaret M.

In: Medical Care, Vol. 43, No. 1, 01.01.2005, p. 61-67.

Research output: Contribution to journalArticle

Petersen, LA, Pietz, K, Woodard, LD & Byrne, MM 2005, 'Comparison of the predictive validity of diagnosis-based risk adjusters for clinical outcomes', Medical Care, vol. 43, no. 1, pp. 61-67.
Petersen LA, Pietz K, Woodard LD, Byrne MM. Comparison of the predictive validity of diagnosis-based risk adjusters for clinical outcomes. Medical Care. 2005 Jan 1;43(1):61-67.
Petersen, Laura A. ; Pietz, Kenneth ; Woodard, LeChauncy D. ; Byrne, Margaret M. / Comparison of the predictive validity of diagnosis-based risk adjusters for clinical outcomes. In: Medical Care. 2005 ; Vol. 43, No. 1. pp. 61-67.
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