Literature DB >> 7754870

A proposal for a national mammography database: content, purpose, and value.

J R Osuch1, M Anthony, L W Bassett, M DeBor, C D'Orsi, R E Hendrick, M Linver, R Smith.   

Abstract

A national mammography database is a centralized, computerized method of data collection consisting of two possible parts: a national mammography audit and a system for monitoring and tracking patients. A national mammography audit refers to collecting and analyzing medical audit data of individual mammography practices at a national level and is a critical step in improving the interpretive component of mammography. The monitoring and tracking component refers to a centralized system that provides women and physicians with a recruitment and follow-up mechanism to optimize participation in mammography services. Both parts of a national mammography database represent important components in the improvement of mammography quality. However, unique scientific, legal, and fiscal concerns are important to consider before establishing a national mammography database.

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Year:  1995        PMID: 7754870     DOI: 10.2214/ajr.164.6.7754870

Source DB:  PubMed          Journal:  AJR Am J Roentgenol        ISSN: 0361-803X            Impact factor:   3.959


  10 in total

1.  MAGIC-5: an Italian mammographic database of digitised images for research.

Authors:  S Tangaro; R Bellotti; F De Carlo; G Gargano; E Lattanzio; P Monno; R Massafra; P Delogu; M E Fantacci; A Retico; M Bazzocchi; S Bagnasco; P Cerello; S C Cheran; E Lopez Torres; E Zanon; A Lauria; A Sodano; D Cascio; F Fauci; R Magro; G Raso; R Ienzi; U Bottigli; G L Masala; P Oliva; G Meloni; A P Caricato; R Cataldo
Journal:  Radiol Med       Date:  2008-06-06       Impact factor: 3.469

2.  Second Opinion Assessment in Diagnostic Mammography at a Breast Cancer Centre.

Authors:  J Lorenzen; A K Finck-Wedel; B Lisboa; G Adam
Journal:  Geburtshilfe Frauenheilkd       Date:  2012-08       Impact factor: 2.915

3.  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

4.  Breast cancer risk estimation with artificial neural networks revisited: discrimination and calibration.

Authors:  Turgay Ayer; Oguzhan Alagoz; Jagpreet Chhatwal; Jude W Shavlik; Charles E Kahn; Elizabeth S Burnside
Journal:  Cancer       Date:  2010-07-15       Impact factor: 6.860

5.  A virtual repository approach to clinical and utilization studies: application in mammography as alternative to a national database.

Authors:  L Ohno-Machado; A A Boxwala; J Ehresman; D N Smith; R A Greenes
Journal:  Proc AMIA Annu Fall Symp       Date:  1997

6.  The ACR BI-RADS experience: learning from history.

Authors:  Elizabeth S Burnside; Edward A Sickles; Lawrence W Bassett; Daniel L Rubin; Carol H Lee; Debra M Ikeda; Ellen B Mendelson; Pamela A Wilcox; Priscilla F Butler; Carl J D'Orsi
Journal:  J Am Coll Radiol       Date:  2009-12       Impact factor: 5.532

7.  Probabilistic computer model developed from clinical data in national mammography database format to classify mammographic findings.

Authors:  Elizabeth S Burnside; Jesse Davis; Jagpreet Chhatwal; Oguzhan Alagoz; Mary J Lindstrom; Berta M Geller; Benjamin Littenberg; Katherine A Shaffer; Charles E Kahn; C David Page
Journal:  Radiology       Date:  2009-04-14       Impact factor: 11.105

8.  Breast Imaging in the Era of Big Data: Structured Reporting and Data Mining.

Authors:  Laurie R Margolies; Gaurav Pandey; Eliot R Horowitz; David S Mendelson
Journal:  AJR Am J Roentgenol       Date:  2015-11-20       Impact factor: 3.959

9.  A logistic regression model based on the national mammography database format to aid breast cancer diagnosis.

Authors:  Jagpreet Chhatwal; Oguzhan Alagoz; Mary J Lindstrom; Charles E Kahn; Katherine A Shaffer; Elizabeth S Burnside
Journal:  AJR Am J Roentgenol       Date:  2009-04       Impact factor: 3.959

10.  Developing a comprehensive database management system for organization and evaluation of mammography datasets.

Authors:  Yirong Wu; Daniel L Rubin; Ryan W Woods; Mai Elezaby; Elizabeth S Burnside
Journal:  Cancer Inform       Date:  2014-10-16
  10 in total

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