title: In search of the perfect comorbidity measure for use with administrative claims data: does it exist?
abstract: BACKGROUND
  Numerous measures of comorbidity have been developed for health services research with administrative claims.
  
  
  OBJECTIVE
  We sought to compare the performance of 4 claims-based comorbidity measures.
  
  
  METHODS
  We undertook a retrospective cohort study of 5777 Medicare beneficiaries ages 66 and older with stage III colon cancer reported to the Surveillance, Epidemiology, and End Results Program between January 1, 1992 and December 31, 1996.
  
  
  METHODS
  Comorbidity measures included Elixhauser's set of 30 condition indicators, Klabunde's outpatient and inpatient indices weighted for colorectal cancer patients, Diagnostic Cost Groups, and the Adjusted Clinical Group (ACG) System. Outcomes included receipt of adjuvant chemotherapy and 2 year noncancer mortality.
  
  
  RESULTS
  For all measures, greater comorbidity significantly predicted lower receipt of chemotherapy and higher noncancer death. Nested logistic regression modeling suggests that using more claims sources to measure comorbidity generally improves the prediction of chemotherapy receipt and noncancer death, but depends on the measure type and outcome studied. All 4 comorbidity measures significantly improved the fit of baseline regression models for both chemotherapy receipt (baseline c-statistic 0.776; ranging from 0.779 after adding ACGs and Klabunde to 0.789 after Elixhauser) and noncancer death (baseline c-statistic 0.687; ranging from 0.717 after adding ACGs to 0.744 after Elixhauser).
  
  
  CONCLUSIONS
  Although some comorbidity measures demonstrate minor advantages over others, each is fairly robust in predicting both chemotherapy receipt and noncancer death. Investigators should choose among these measures based on their availability, comfort with the methodology, and outcomes of interest.
authors.affiliation: Department of Family Medicine, University of Washington, Seattle, Washington 98195-4982, USA. lmb@fammed.washington.edu
authors.forename: Laura-Mae
authors.initials: LM
authors.lastname: Baldwin
authors.forename: Carrie N
authors.initials: CN
authors.lastname: Klabunde
authors.forename: Pam
authors.initials: P
authors.lastname: Green
authors.forename: William
authors.initials: W
authors.lastname: Barlow
authors.forename: George
authors.initials: G
authors.lastname: Wright
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D015331:Cohort Studies; D003110:Colonic Neoplasms; D015897:Comorbidity; D005260:Female; D006801:Humans; D007344:Insurance Claim Reporting; D008297:Male; D006278:Medicare; D012189:Retrospective Studies; D018426:SEER Program