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Identification of Abnormal Screening Mammogram Interpretation Using Medicare Claims Data

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Keywords: Breast cancer;mammography;Medicare;quality assessment;screening

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.

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