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

Balch, Steven

Fenton, Joshua J.

Henderson, Louise

Hubbard, Rebecca A.

Kerlikowske, Karla

Onega, Tracy

Smith-Bindman, Rebecca

Sprague, Brian L.

Zhu, Weiwei

English

PubMed

Carolina Digital Repository

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

BackgroundThe 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.ObjectivesTo validate a claims-based algorithm that can identify with high positive predictive value (PPV) incident breast cancers that were detected at screening mammography.Research designDevelopment 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).SubjectsFemale 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).MeasuresSensitivity, 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.ResultsAn 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%).ConclusionsA 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

Fenton, Joshua J

Sprague, Brian L

Hubbard, Rebecca A

eScholarship - University of California

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

http://cdr.lib.unc.edu/downloads/s7526j22f

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

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eScholarship - University of California