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.

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.

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