Identification of Abnormal Screening Mammogram Interpretation Using Medicare Claims Data

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 ().

Study Design

Split‐sample validation of algorithms based on claims for breast imaging or biopsy following screening mammography.

Data Extraction Methods

Medicare claims and 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 [], 74.1–75.6) and specificity of 99.4 percent (95 percent , 99.4–99.5). A classification and regression tree improved sensitivity to 82.5 percent (95 percent , 81.9–83.2) but decreased specificity (96.6 percent, 95 percent , 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.