title: Identification of abnormal screening mammogram interpretation using Medicare claims data.
abstract: OBJECTIVE
  To develop and validate Medicare claims-based approaches for identifying abnormal screening mammography interpretation.
  
  
  METHODS
  Mammography data and linked Medicare claims for 387,709 mammograms performed from 1999 to 2005 within the Breast Cancer Surveillance Consortium (BCSC).
  
  
  METHODS
  Split-sample validation of algorithms based on claims for breast imaging or biopsy following screening mammography.
  
  
  METHODS
  Medicare claims and BCSC mammography data were pooled at a central Statistical Coordinating Center.
  
  
  RESULTS
  Presence of claims for subsequent imaging or biopsy had sensitivity of 74.9 percent (95 percent confidence interval [CI], 74.1-75.6) and specificity of 99.4 percent (95 percent CI, 99.4-99.5). A classification and regression tree improved sensitivity to 82.5 percent (95 percent CI, 81.9-83.2) but decreased specificity (96.6 percent, 95 percent CI, 96.6-96.8).
  
  
  CONCLUSIONS
  Medicare claims may be a feasible data source for research or quality improvement efforts addressing high rates of abnormal screening mammography.
authors: Group Health Research Institute and Department of Biostatistics, University of Washington, 1730 Minor Ave, Suite 1600, Seattle, WA, 98101.
authors: Rebecca A
authors: RA
authors: Hubbard
authors: Weiwei
authors: W
authors: Zhu
authors: Steven
authors: S
authors: Balch
authors: Tracy
authors: T
authors: Onega
authors: Joshua J
authors: JJ
authors: Fenton
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D001706:Biopsy; D001943:Breast Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology; D003951:Diagnostic Errors; D005260:Female; D006801:Humans; D007345:Insurance Claim Review; D008327:Mammography; D006278:Medicare; D012680:Sensitivity and Specificity; D014481:United States
keywords: Breast cancer; Medicare; mammography; quality assessment; screening