Literature DB >> 10572846

Proficiency test for screening mammography: results for 117 volunteer Italian radiologists.

S Ciatto1, D Ambrogetti, S Catarzi, D Morrone, M Rosselli Del Turco.   

Abstract

OBJECTIVE: To analyse the performance of a large sample of Italian radiologists undergoing a proficiency test for screening mammography.
DESIGN: Evaluation of performance indicators according to reference standards determined by a panel of experts (sensitivity (reference standard > or = 80%), recall rate (reference standard < or = 15%)).
SETTING: 117 Italian radiologists of varying experience (years of practice 0.5-18, average 5.9; mammograms read 500-51,000, average 13,000), all currently reporting clinical mammography and planning to take part in screening in the near future.
RESULTS: Eighty four of 117 (72%) radiologists reached the standard for sensitivity, 88 (75%) reached the standard for recall rate, and only 59 (50%) reached both standards and passed the proficiency test. The probability of passing the test was significantly correlated with mammographic practice (p = 0.015), mammograms read (p = 0.024), and mammograms read/year (p = 0.043). DISCUSSION: The performance of a large sample of Italian radiologists currently reporting clinical mammography was disappointing, indicating the need for proper training of at least 50% of the tested subjects. When implementing organised screening the health authority should set up a proper process for training and accrediting radiologists, and a proficiency test should be part of such a process.

Mesh:

Year:  1999        PMID: 10572846     DOI: 10.1136/jms.6.3.149

Source DB:  PubMed          Journal:  J Med Screen        ISSN: 0969-1413            Impact factor:   2.136


  4 in total

1.  Computer-assisted mammography feedback program (CAMFP) an electronic tool for continuing medical education.

Authors:  Nicole Urban; Gary M Longton; Andrea D Crowe; Mariann J Drucker; Constance D Lehman; Susan Peacock; Kimberly A Lowe; Steve B Zeliadt; Marcia A Gaul
Journal:  Acad Radiol       Date:  2007-09       Impact factor: 3.173

2.  Volume of screening mammography and performance in the Quebec population-based Breast Cancer Screening Program.

Authors:  Isabelle Théberge; Nicole Hébert-Croteau; André Langlois; Diane Major; Jacques Brisson
Journal:  CMAJ       Date:  2005-01-18       Impact factor: 8.262

3.  A machine learning model based on readers' characteristics to predict their performances in reading screening mammograms.

Authors:  Ziba Gandomkar; Sarah J Lewis; Tong Li; Ernest U Ekpo; Patrick C Brennan
Journal:  Breast Cancer       Date:  2022-02-05       Impact factor: 3.307

4.  Comparison of standard and double reading and computer-aided detection (CAD) of interval cancers at prior negative screening mammograms: blind review.

Authors:  S Ciatto; M Rosselli Del Turco; P Burke; C Visioli; E Paci; M Zappa
Journal:  Br J Cancer       Date:  2003-11-03       Impact factor: 7.640

  4 in total

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