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

Content Provider	Scilit
Author	Fenton, Joshua J. Onega, Tracy Zhu, Weiwei Balch, Steven Smith-Bindman, Rebecca Henderson, Louise Sprague, Brian L. Kerlikowske, Karla Hubbard, Rebecca
Copyright Year	2016
Description	Journal: Medical Care 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.
Related Links	http://europepmc.org/articles/pmc3865072?pdf=render https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3865072/pdf
Ending Page	e22
Page Count	8
Starting Page	e15
ISSN	00257079
e-ISSN	15371948
DOI	10.1097/mlr.0b013e3182a303d7
Journal	Medical Care
Issue Number	3
Volume Number	54
Language	English
Publisher	Ovid Technologies (Wolters Kluwer Health)
Publisher Date	2016-03-01
Access Restriction	Open
Subject Keyword	Journal: Medical Care Womens Studies Breast Cancer Screening, Mammography, Validation Studies, Medicare, Quality Assessment
Content Type	Text
Resource Type	Article
Subject	Public Health, Environmental and Occupational Health