title: Dual-system utilization affects regional variation in prevention quality indicators: the case of amputations among veterans with diabetes.
abstract: OBJECTIVE
  To determine the impact of dual-system utilization by veterans on regional variation in lower-extremity amputation rates.
  
  
  METHODS
  Retrospective longitudinal cohort analysis.
  
  
  METHODS
  Subjects were veterans with diabetes who used Veterans Health Administration (VHA) care and were dually enrolled in Medicare fee for service in fiscal years (FY) 1997--1999. We evaluated the impact of Centers for Medicare and Medicaid Services (CMS) data on prevalence of baseline foot risk factors, medical comorbidities, and amputations in FY 1997--1998, and ranking of 22 regions using risk-adjusted major and minor amputation rates in FY 1999.
  
  
  RESULTS
  The addition of CMS data significantly increased the prevalence of amputations and risk factors for the 218,528 dually eligible veterans (all Pvalues <.001). In FY 1999, we identified 3.1 minor and 4.5 major amputations per 1000 patients (VHA data) versus 5.5 minor and 8.6 major amputations per 1000 patients (VHA/CMS data); the prevalence of any peripheral vascular condition in FY 1997--1998 was 5.7% (VHA) versus 13.0% (VHA/CMS). The impact of including CMS data varied across regions for amputation outcomes, ranging from an additional 34.3% to 150.7%. Using observed-to-expected amputation ratios and 99% confidence intervals, the addition of CMS data changed the outlier status for 8 of 22 regions for both major and minor amputations.
  
  
  CONCLUSIONS
  Risk covariates and amputation outcomes were substantially underestimated using VHA data only. Our findings demonstrate the importance of evaluating dual-system utilization when conducting program evaluations for healthcare systems with a substantial number of dual enrollees.
authors.affiliation: Center for Healthcare Knowledge Management, Veterans Affairs-New Jersey Healthcare System, East Orange, NJ 07018, USA.
authors.forename: Chin-Lin
authors.initials: CL
authors.lastname: Tseng
authors.forename: Jeffrey D
authors.initials: JD
authors.lastname: Greenberg
authors.forename: Drew
authors.initials: D
authors.lastname: Helmer
authors.forename: Mangala
authors.initials: M
authors.lastname: Rajan
authors.forename: Anjali
authors.initials: A
authors.lastname: Tiwari
authors.forename: Donald
authors.initials: D
authors.lastname: Miller
authors.forename: Stephen
authors.initials: S
authors.lastname: Crystal
authors.forename: Gerald
authors.initials: G
authors.lastname: Hawley
authors.forename: Leonard
authors.initials: L
authors.lastname: Pogach
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000671:Amputation, Surgical / Q000706:statistics & numerical data*; D015897:Comorbidity; D017719:Diabetic Foot / Q000453:epidemiology / Q000601:surgery*; D018588:Fee-for-Service Plans / Q000592:standards / Q000706:statistics & numerical data; D005260:Female; D006787:Hospitals, Veterans / Q000592:standards / Q000706:statistics & numerical data*; D006801:Humans; D008137:Longitudinal Studies; D008297:Male; D008329:Managed Care Programs / Q000592:standards / Q000706:statistics & numerical data; D016344:Medicare Part A / Q000592:standards / Q000706:statistics & numerical data*; D015995:Prevalence; D019984:Quality Indicators, Health Care; D012189:Retrospective Studies; D016896:Treatment Outcome; D014481:United States / Q000453:epidemiology; D014493:United States Department of Veterans Affairs; D014600:Utilization Review / Q000706:statistics & numerical data*; D014728:Veterans / Q000706:statistics & numerical data*