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doi: 10.1097/MLR.0b013e3182a303d7
Applied Methods

Validation of a Medicare Claims-based Algorithm for Identifying Breast Cancers Detected at Screening Mammography

Fenton, Joshua J. MD, MPH; Onega, Tracy PhD; Zhu, Weiwei MS; Balch, Steven MA, MBA; Smith-Bindman, Rebecca MD, MPH; Henderson, Louise PhD; Sprague, Brian L. PhD; Kerlikowske, Karla MD; Hubbard, Rebecca A. PhD

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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.

Copyright © 2016 Wolters Kluwer Health, Inc. All rights reserved.


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