Validation of a Medicare Claims-based Algorithm for Identifying Breast Cancers Detected at Screening Mammography
Year: 2013
Type: article
Abstract: BACKGROUND: The breast cancer detection rate is a benchmark measure of screening mammography quality, but its computation requires linkage of mammography interpretive performance information with cancer incidence data. A Medicare claims-based measure of detected breast cancers could simplify measurement of this benchmark and facilitate mammography quality assessment and research. OBJECTIVES: To validate a claims-based algorithm that can identify with high positive predictive value (PPV) incident breast cancers that were detected at screening mammography. RESEARCH DESIGN: Development of a claims-derived algorithm using classification and regression tree analyses within a random half-sample of Medicare screening mammography claims followed by validation of the algorithm in the remaining half-sample using clinical data on mammography results and cancer incidence from the Breast Cancer Surveillance Consortium (BCSC). SUBJECTS: Female fee-for-service Medicare enrollees aged 68 years and older who underwent screening mammography from 2001 to 2005 within BCSC registries in 4 states (CA, NC, NH, and VT), enabling linkage of claims and BCSC mammography data (N=233,044 mammograms obtained by 104,997 women). MEASURES: Sensitivity, specificity, and PPV of algorithmic identification of incident breast cancers that were detected by radiologists relative to a reference standard based on BCSC mammography and cancer incidence data. RESULTS: An algorithm based on subsequent codes for breast cancer diagnoses and treatments and follow-up mammography identified incident screen-detected breast cancers with 92.9% sensitivity [95% confidence interval (CI), 91.0%-94.8%], 99.9% specificity (95% CI, 99.9%-99.9%), and a PPV of 88.0% (95% CI, 85.7%-90.4%). CONCLUSIONS: A simple claims-based algorithm can accurately identify incident breast cancers detected at screening mammography among Medicare enrollees. The algorithm may enable mammography quality assessment using Medicare claims alone.
Source: Medical Care
Institutions: University of Vermont, University of North Carolina at Chapel Hill, University of California, San Francisco, Dartmouth Cancer Center, University of California, Davis, Dartmouth College, Group Health Cooperative, University of California Office of the President, University of Washington
Language: English
Subfield: Oncology
Field: Medicine
Domain: Health Sciences
Open Access status: green
Funder: National Cancer Institute
Awards: G1353929375, San Francisco Mammography Registry-A Research Source, G339124968, G4053229109, G407747206, Breast Cancer Surveillance in a Defined Population, G4299498666, G4593227348, G5017971770, G5117928749, G5997123071, G613175501, G640097384, Statistical Coordinating Center for the Breast Cancer Surveillance Consortium, G6702111474, G7313027696, G7594099874, G79717682, G8622805583
OpenAlex ID: W2048568114