Work

Identification of Abnormal Screening Mammogram Interpretation Using Medicare Claims Data

Year: 2014

Type: article

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.

Source: Health Services Research

DOI: 10.1111/1475-6773.12194

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