Identification of abnormal screening mammogram interpretation using Medicare claims data

Rebecca A. Hubbard, Weiwei Zhu, Steven Balch, Tracy Onega, Joshua J Fenton

Research output: Contribution to journalArticle

2 Scopus citations

Abstract

Objective To develop and validate Medicare claims-based approaches for identifying abnormal screening mammography interpretation. Data Sources Mammography data and linked Medicare claims for 387,709 mammograms performed from 1999 to 2005 within the Breast Cancer Surveillance Consortium (BCSC). Study Design Split-sample validation of algorithms based on claims for breast imaging or biopsy following screening mammography. Data Extraction Methods Medicare claims and BCSC mammography data were pooled at a central Statistical Coordinating Center. Principal Findings 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.

Original languageEnglish (US)
Pages (from-to)290-304
Number of pages15
JournalHealth Services Research
Volume50
Issue number1
DOIs
StatePublished - Feb 1 2015

Keywords

  • Breast cancer
  • mammography
  • Medicare
  • quality assessment
  • screening

ASJC Scopus subject areas

  • Health Policy

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