Literature DB >> 23929404

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

Joshua J Fenton1, Tracy Onega, Weiwei Zhu, Steven Balch, Rebecca Smith-Bindman, Louise Henderson, Brian L Sprague, Karla Kerlikowske, Rebecca A Hubbard.   

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.

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Year:  2016        PMID: 23929404      PMCID: PMC3865072          DOI: 10.1097/MLR.0b013e3182a303d7

Source DB:  PubMed          Journal:  Med Care        ISSN: 0025-7079            Impact factor:   2.983


  17 in total

1.  An approach to identifying incident breast cancer cases using Medicare claims data.

Authors:  J L Freeman; D Zhang; D H Freeman; J S Goodwin
Journal:  J Clin Epidemiol       Date:  2000-06       Impact factor: 6.437

Review 2.  Classification and regression tree analysis in public health: methodological review and comparison with logistic regression.

Authors:  Stephenie C Lemon; Jason Roy; Melissa A Clark; Peter D Friedmann; William Rakowski
Journal:  Ann Behav Med       Date:  2003-12

3.  Overview of the SEER-Medicare data: content, research applications, and generalizability to the United States elderly population.

Authors:  Joan L Warren; Carrie N Klabunde; Deborah Schrag; Peter B Bach; Gerald F Riley
Journal:  Med Care       Date:  2002-08       Impact factor: 2.983

4.  Breast Cancer Surveillance Consortium: a national mammography screening and outcomes database.

Authors:  R Ballard-Barbash; S H Taplin; B C Yankaskas; V L Ernster; R D Rosenberg; P A Carney; W E Barlow; B M Geller; K Kerlikowske; B K Edwards; C F Lynch; N Urban; C A Chrvala; C R Key; S P Poplack; J K Worden; L G Kessler
Journal:  AJR Am J Roentgenol       Date:  1997-10       Impact factor: 3.959

5.  An algorithm for the use of Medicare claims data to identify women with incident breast cancer.

Authors:  Ann B Nattinger; Purushottam W Laud; Ruta Bajorunaite; Rodney A Sparapani; Jean L Freeman
Journal:  Health Serv Res       Date:  2004-12       Impact factor: 3.402

6.  Performance benchmarks for diagnostic mammography.

Authors:  Edward A Sickles; Diana L Miglioretti; Rachel Ballard-Barbash; Berta M Geller; Jessica W T Leung; Robert D Rosenberg; Rebecca Smith-Bindman; Bonnie C Yankaskas
Journal:  Radiology       Date:  2005-06       Impact factor: 11.105

7.  Comparison of screening mammography in the United States and the United kingdom.

Authors:  Rebecca Smith-Bindman; Philip W Chu; Diana L Miglioretti; Edward A Sickles; Roger Blanks; Rachel Ballard-Barbash; Janet K Bobo; Nancy C Lee; Matthew G Wallis; Julietta Patnick; Karla Kerlikowske
Journal:  JAMA       Date:  2003-10-22       Impact factor: 56.272

8.  Using Medicare data to estimate the prevalence of breast cancer screening in older women: comparison of different methods to identify screening mammograms.

Authors:  Whitney M Randolph; Jonathan D Mahnken; James S Goodwin; Jean L Freeman
Journal:  Health Serv Res       Date:  2002-12       Impact factor: 3.402

9.  Use of SEER-Medicare data for measuring cancer surgery.

Authors:  Gregory S Cooper; Beth Virnig; Carrie N Klabunde; Nicola Schussler; Jean Freeman; Joan L Warren
Journal:  Med Care       Date:  2002-08       Impact factor: 2.983

10.  Studying radiation therapy using SEER-Medicare-linked data.

Authors:  Beth A Virnig; Joan L Warren; Gregory S Cooper; Carrie N Klabunde; Nicola Schussler; Jean Freeman
Journal:  Med Care       Date:  2002-08       Impact factor: 2.983

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  17 in total

1.  Evaluating Lung Cancer Screening Uptake, Outcomes, and Costs in the United States: Challenges With Existing Data and Recommendations for Improvement.

Authors:  Ashish Rai; V Paul Doria-Rose; Gerard A Silvestri; K Robin Yabroff
Journal:  J Natl Cancer Inst       Date:  2019-04-01       Impact factor: 13.506

2.  Vulnerable And Less Vulnerable Women In High-Deductible Health Plans Experienced Delayed Breast Cancer Care.

Authors:  J Frank Wharam; Fang Zhang; Jamie Wallace; Christine Lu; Craig Earle; Stephen B Soumerai; Larissa Nekhlyudov; Dennis Ross-Degnan
Journal:  Health Aff (Millwood)       Date:  2019-03       Impact factor: 6.301

3.  Association of State Dense Breast Notification Laws With Supplemental Testing and Cancer Detection After Screening Mammography.

Authors:  Susan H Busch; Jessica R Hoag; Jenerius A Aminawung; Xiao Xu; Ilana B Richman; Pamela R Soulos; Kelly A Kyanko; Cary P Gross
Journal:  Am J Public Health       Date:  2019-03-21       Impact factor: 9.308

4.  Identification of abnormal screening mammogram interpretation using Medicare claims data.

Authors:  Rebecca A Hubbard; Weiwei Zhu; Steven Balch; Tracy Onega; Joshua J Fenton
Journal:  Health Serv Res       Date:  2014-06-28       Impact factor: 3.402

5.  Challenges With Identifying Indication for Examination in Breast Imaging as a Key Clinical Attribute in Practice, Research, and Policy.

Authors:  Julie E Weiss; Martha Goodrich; Kimberly A Harris; Rachael E Chicoine; Marie B Synnestvedt; Steve J Pyle; Jane S Chen; Sally D Herschorn; Elisabeth F Beaber; Jennifer S Haas; Anna N A Tosteson; Tracy Onega
Journal:  J Am Coll Radiol       Date:  2016-10-13       Impact factor: 5.532

6.  Geographic Disparity in the Use of Hypofractionated Radiation Therapy Among Elderly Women Undergoing Breast Conservation for Invasive Breast Cancer.

Authors:  Erin F Gillespie; Rayna K Matsuno; Beibei Xu; Daniel P Triplett; Lindsay Hwang; Isabel J Boero; John P Einck; Catheryn Yashar; James D Murphy
Journal:  Int J Radiat Oncol Biol Phys       Date:  2016-05-12       Impact factor: 7.038

7.  Development and validation of algorithms to differentiate ductal carcinoma in situ from invasive breast cancer within administrative claims data.

Authors:  Jacqueline M Hirth; Sandra S Hatch; Yu-Li Lin; Sharon H Giordano; H Colleen Silva; Yong-Fang Kuo
Journal:  Cancer       Date:  2018-04-18       Impact factor: 6.860

8.  Differential Use of Screening Mammography in Older Women Initiating Metformin versus Sulfonylurea.

Authors:  Jin-Liern Hong; Louise M Henderson; Michele Jonsson Funk; Jennifer L Lund; John B Buse; Virginia Pate; Til Stürmer
Journal:  Pharmacoepidemiol Drug Saf       Date:  2017-03-29       Impact factor: 2.890

9.  Profiling Patient Characteristics Associated With the Intensity of Nurse Care Coordination.

Authors:  Tae Youn Kim; Karen D Marek
Journal:  West J Nurs Res       Date:  2016-09-25       Impact factor: 1.967

10.  Breast Cancer Diagnosis and Treatment After High-Deductible Insurance Enrollment.

Authors:  J Frank Wharam; Fang Zhang; Christine Y Lu; Anita K Wagner; Larissa Nekhlyudov; Craig C Earle; Stephen B Soumerai; Dennis Ross-Degnan
Journal:  J Clin Oncol       Date:  2018-02-28       Impact factor: 44.544

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