TY - JOUR
T1 - Validation of a medicare claims-based algorithm for identifying breast cancers detected at screening mammography
AU - Fenton, Joshua J
AU - Onega, Tracy
AU - Zhu, Weiwei
AU - Balch, Steven
AU - Smith-Bindman, Rebecca
AU - Henderson, Louise
AU - Sprague, Brian L.
AU - Kerlikowske, Karla
AU - Hubbard, Rebecca A.
PY - 2016
Y1 - 2016
N2 - 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 halfsample 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 identi-fication 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.
AB - 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 halfsample 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 identi-fication 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.
KW - Breast cancer screening
KW - Mammography
KW - Medicare
KW - Quality assessment
KW - Validation studies
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U2 - 10.1097/MLR.0b013e3182a303d7
DO - 10.1097/MLR.0b013e3182a303d7
M3 - Article
C2 - 23929404
AN - SCOPUS:84959112192
VL - 54
SP - e15-e22
JO - Medical Care
JF - Medical Care
SN - 0025-7079
IS - 3
ER -