Literature DB >> 22130089

Are radiologists' goals for mammography accuracy consistent with published recommendations?

Sara L Jackson1, Andrea J Cook, Diana L Miglioretti, Patricia A Carney, Berta M Geller, Tracy Onega, Robert D Rosenberg, R James Brenner, Joann G Elmore.   

Abstract

RATIONALE AND
OBJECTIVES: Mammography quality assurance programs have been in place for more than a decade. We studied radiologists' self-reported performance goals for accuracy in screening mammography and compared them to published recommendations.
MATERIALS AND METHODS: A mailed survey of radiologists at mammography registries in seven states within the Breast Cancer Surveillance Consortium (BCSC) assessed radiologists' performance goals for interpreting screening mammograms. Self-reported goals were compared to published American College of Radiology (ACR) recommended desirable ranges for recall rate, false-positive rate, positive predictive value of biopsy recommendation (PPV2), and cancer detection rate. Radiologists' goals for interpretive accuracy within desirable range were evaluated for associations with their demographic characteristics, clinical experience, and receipt of audit reports.
RESULTS: The survey response rate was 71% (257 of 364 radiologists). The percentage of radiologists reporting goals within desirable ranges was 79% for recall rate, 22% for false-positive rate, 39% for PPV2, and 61% for cancer detection rate. The range of reported goals was 0%-100% for false-positive rate and PPV2. Primary academic affiliation, receiving more hours of breast imaging continuing medical education, and receiving audit reports at least annually were associated with desirable PPV2 goals. Radiologists reporting desirable cancer detection rate goals were more likely to have interpreted mammograms for 10 or more years, and >1000 mammograms per year.
CONCLUSION: Many radiologists report goals for their accuracy when interpreting screening mammograms that fall outside of published desirable benchmarks, particularly for false-positive rate and PPV2, indicating an opportunity for education.
Copyright © 2012 AUR. Published by Elsevier Inc. All rights reserved.

Entities:  

Mesh:

Year:  2011        PMID: 22130089      PMCID: PMC3274618          DOI: 10.1016/j.acra.2011.10.013

Source DB:  PubMed          Journal:  Acad Radiol        ISSN: 1076-6332            Impact factor:   3.173


  16 in total

1.  Radiologists' attitudes and use of mammography audit reports.

Authors:  Joann G Elmore; Erin J Aiello Bowles; Berta Geller; Natalia Vukshich Oster; Patricia A Carney; Diana L Miglioretti; Diana S M Buist; Karla Kerlikowske; Edward A Sickles; Tracy Onega; Robert D Rosenberg; Bonnie C Yankaskas
Journal:  Acad Radiol       Date:  2010-06       Impact factor: 3.173

2.  False-positive mammograms--can the USA learn from Europe?

Authors:  Suzanne W Fletcher; Joann G Elmore
Journal:  Lancet       Date:  2005 Jan 1-7       Impact factor: 79.321

3.  Provider's volume and quality of breast cancer detection and treatment.

Authors:  Nicole Hébert-Croteau; Danièle Roberge; Jacques Brisson
Journal:  Breast Cancer Res Treat       Date:  2006-12-21       Impact factor: 4.872

4.  Performance benchmarks for screening mammography.

Authors:  Robert D Rosenberg; Bonnie C Yankaskas; Linn A Abraham; Edward A Sickles; Constance D Lehman; Berta M Geller; Patricia A Carney; Karla Kerlikowske; Diana S M Buist; Donald L Weaver; William E Barlow; Rachel Ballard-Barbash
Journal:  Radiology       Date:  2006-10       Impact factor: 11.105

5.  Role of Adult Learning Theory in Evaluating and Designing Strategies for Teaching Residents in Ambulatory Settings.

Authors:  Tracy L. Laidley; Clarence H. Braddock III
Journal:  Adv Health Sci Educ Theory Pract       Date:  2000       Impact factor: 3.853

Review 6.  Systematic review: the long-term effects of false-positive mammograms.

Authors:  Noel T Brewer; Talya Salz; Sarah E Lillie
Journal:  Ann Intern Med       Date:  2007-04-03       Impact factor: 25.391

7.  When radiologists perform best: the learning curve in screening mammogram interpretation.

Authors:  Diana L Miglioretti; Charlotte C Gard; Patricia A Carney; Tracy L Onega; Diana S M Buist; Edward A Sickles; Karla Kerlikowske; Robert D Rosenberg; Bonnie C Yankaskas; Berta M Geller; Joann G Elmore
Journal:  Radiology       Date:  2009-09-29       Impact factor: 11.105

Review 8.  Screening for breast cancer: an update for the U.S. Preventive Services Task Force.

Authors:  Heidi D Nelson; Kari Tyne; Arpana Naik; Christina Bougatsos; Benjamin K Chan; Linda Humphrey
Journal:  Ann Intern Med       Date:  2009-11-17       Impact factor: 25.391

Review 9.  European guidelines for quality assurance in breast cancer screening and diagnosis. Fourth edition--summary document.

Authors:  N Perry; M Broeders; C de Wolf; S Törnberg; R Holland; L von Karsa
Journal:  Ann Oncol       Date:  2007-11-17       Impact factor: 32.976

10.  Variability in interpretive performance at screening mammography and radiologists' characteristics associated with accuracy.

Authors:  Joann G Elmore; Sara L Jackson; Linn Abraham; Diana L Miglioretti; Patricia A Carney; Berta M Geller; Bonnie C Yankaskas; Karla Kerlikowske; Tracy Onega; Robert D Rosenberg; Edward A Sickles; Diana S M Buist
Journal:  Radiology       Date:  2009-10-28       Impact factor: 11.105

View more
  4 in total

1.  Comparing search patterns in digital breast tomosynthesis and full-field digital mammography: an eye tracking study.

Authors:  Avi Aizenman; Trafton Drew; Krista A Ehinger; Dianne Georgian-Smith; Jeremy M Wolfe
Journal:  J Med Imaging (Bellingham)       Date:  2017-10-27

2.  Mammographic interpretation: radiologists' ability to accurately estimate their performance and compare it with that of their peers.

Authors:  Andrea J Cook; Joann G Elmore; Weiwei Zhu; Sara L Jackson; Patricia A Carney; Chris Flowers; Tracy Onega; Berta Geller; Robert D Rosenberg; Diana L Miglioretti
Journal:  AJR Am J Roentgenol       Date:  2012-09       Impact factor: 3.959

3.  Breast cancer mammographic diagnosis performance in a public health institution: a retrospective cohort study.

Authors:  Juliana M R B Mello; Fernando P Bittelbrunn; Marcio A B C Rockenbach; Guilherme G May; Leonardo M Vedolin; Marilia S Kruger; Matheus D Soldatelli; Guilherme Zwetsch; Gabriel T F de Miranda; Saone I P Teixeira; Bruna S Arruda
Journal:  Insights Imaging       Date:  2017-10-04

4.  How one block of trials influences the next: persistent effects of disease prevalence and feedback on decisions about images of skin lesions in a large online study.

Authors:  Jeremy M Wolfe
Journal:  Cogn Res Princ Implic       Date:  2022-02-02
  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.