Literature DB >> 22695737

External validation of Medicare claims codes for digital mammography and computer-aided detection.

Joshua J Fenton1, Weiwei Zhu, Steven Balch, Rebecca Smith-Bindman, Karen K Lindfors, Rebecca A Hubbard.   

Abstract

BACKGROUND: While Medicare claims are a potential resource for clinical mammography research or quality monitoring, the validity of key data elements remains uncertain. Claims codes for digital mammography and computer-aided detection (CAD), for example, have not been validated against a credible external reference standard.
METHODS: We matched Medicare mammography claims for women who received bilateral mammograms from 2003 to 2006 to corresponding mammography data from the Breast Cancer Surveillance Consortium (BCSC) registries in four U.S. states (N = 253,727 mammograms received by 120,709 women). We assessed the accuracy of the claims-based classifications of bilateral mammograms as either digital versus film and CAD versus non-CAD relative to a reference standard derived from BCSC data.
RESULTS: Claims data correctly classified the large majority of film and digital mammograms (97.2% and 97.3%, respectively), yielding excellent agreement beyond chance (κ = 0.90). Claims data correctly classified the large majority of CAD mammograms (96.6%) but a lower percentage of non-CAD mammograms (86.7%). Agreement beyond chance remained high for CAD classification (κ = 0.83). From 2003 to 2006, the predictive values of claims-based digital and CAD classifications increased as the sample prevalences of each technology increased.
CONCLUSION: Medicare claims data can accurately distinguish film and digital bilateral mammograms and mammograms conducted with and without CAD. IMPACT: The validity of Medicare claims data regarding film versus digital mammography and CAD suggests that these data elements can be useful in research and quality improvement. ©2012 AACR.

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Year:  2012        PMID: 22695737      PMCID: PMC3422017          DOI: 10.1158/1055-9965.EPI-12-0406

Source DB:  PubMed          Journal:  Cancer Epidemiol Biomarkers Prev        ISSN: 1055-9965            Impact factor:   4.254


  4 in total

1.  How widely is computer-aided detection used in screening and diagnostic mammography?

Authors:  Vijay M Rao; David C Levin; Laurence Parker; Barbara Cavanaugh; Andrea J Frangos; Jonathan H Sunshine
Journal:  J Am Coll Radiol       Date:  2010-10       Impact factor: 5.532

2.  Breast Cancer Surveillance Consortium: a national mammography screening and outcomes database.

Authors:  R Ballard-Barbash; S H Taplin; B C Yankaskas; V L Ernster; R D Rosenberg; P A Carney; W E Barlow; B M Geller; K Kerlikowske; B K Edwards; C F Lynch; N Urban; C A Chrvala; C R Key; S P Poplack; J K Worden; L G Kessler
Journal:  AJR Am J Roentgenol       Date:  1997-10       Impact factor: 3.959

3.  Internal validation of procedure codes on Medicare claims for digital mammograms and computer-aided detection.

Authors:  Joshua J Fenton; Pamela Green; Laura-Mae Baldwin
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2009-08       Impact factor: 4.254

Review 4.  Cancer screening in the United States, 2008: a review of current American Cancer Society guidelines and cancer screening issues.

Authors:  Robert A Smith; Vilma Cokkinides; Otis Webb Brawley
Journal:  CA Cancer J Clin       Date:  2008-04-28       Impact factor: 508.702

  4 in total
  1 in total

1.  Short-term outcomes of screening mammography using computer-aided detection: a population-based study of medicare enrollees.

Authors:  Joshua J Fenton; Guibo Xing; Joann G Elmore; Heejung Bang; Steven L Chen; Karen K Lindfors; Laura-Mae Baldwin
Journal:  Ann Intern Med       Date:  2013-04-16       Impact factor: 25.391

  1 in total

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