title: Use of administrative data to risk adjust amputation rates in a national cohort of medicare-enrolled veterans with diabetes.
abstract: BACKGROUND
  A reduction in diabetes-related lower extremity amputations is a national health care priority.
  
  
  OBJECTIVE
  To develop a risk adjustment model for total amputation rates, using claims data.
  
  
  METHODS
  A retrospective longitudinal cohort analysis of veteran clinical users of the Veterans Health Administration (VHA)--Veterans with diabetes who were Medicare nonhealth maintenance organization enrolled in 1997 or 1998. Baseline risks ascertained in 1997 to 1998 were used to adjust Veterans Integrated Service Networks (VISN) amputation rates in 1999.
  
  
  METHODS
  Individual-level amputation outcome in VHA and private hospitals in 1999; VISN-level amputation rates adjusted for age, gender, race, foot risk factors, and macro- and microvascular complications; and rankings of 22 VISNs on amputation rates.
  
  
  RESULTS
  A total of 218,528 patients incurred 3077 (14.1 per 1000) amputations in 1999, with 10.6 to 18.0 amputations per 1000 across 22 VISNs. Age, gender, race, prior amputation, infections, ulcers, peripheral vascular disease, and vascular complications were significant independent predictors of amputation (R = 0.20); demographic variables accounted for < 1% of the variance. The C statistic of the final model was 0.83. VISN rankings using age-, gender-, and race-adjusted rates were not substantially altered compared with rankings using the full risk-adjusted model (Spearman rank correlation, 0.85).
  
  
  CONCLUSIONS
  Addition of foot risk and comorbidity variables increased the discrimination of a predictive model for total amputations in an elderly, largely male population of veterans with diabetes compared with use of demographic data alone. The authors suggest that this model be validated in other settings with availability of individual-level claims data.
authors.affiliation: Center for Healthcare Knowledgement Management, DVA-New Jersey Healthcare System, East Orange, New Jersey 07018, USA.
authors.forename: Chin-Lin
authors.initials: CL
authors.lastname: Tseng
authors.forename: Mangala
authors.initials: M
authors.lastname: Rajan
authors.forename: Donald R
authors.initials: DR
authors.lastname: Miller
authors.forename: Gerald
authors.initials: G
authors.lastname: Hawley
authors.forename: Stephen
authors.initials: S
authors.lastname: Crystal
authors.forename: Minge
authors.initials: M
authors.lastname: Xie
authors.forename: Anjali
authors.initials: A
authors.lastname: Tiwari
authors.forename: Monika
authors.initials: M
authors.lastname: Safford
authors.forename: Leonard
authors.initials: L
authors.lastname: Pogach
mesh_terms: D017677:Age Distribution; D000368:Aged; D000671:Amputation, Surgical / Q000706:statistics & numerical data*; D015331:Cohort Studies; D048909:Diabetes Complications / Q000601:surgery*; D005260:Female; D006801:Humans; D038801:International Classification of Diseases; D035002:Lower Extremity / Q000601:surgery*; D008297:Male; D006278:Medicare / Q000706:statistics & numerical data*; D008875:Middle Aged; D012189:Retrospective Studies; D020379:Risk Adjustment; D017678:Sex Distribution; D014481:United States; D014493:United States Department of Veterans Affairs / Q000706:statistics & numerical data*