AIM: To devise a method for reviewing interval cancers that will both educate radiologists and facilitate improvement of breast screening practice. To evaluate different methods for case classification to find one that best serves this purpose. METHOD: The method of peer review and the means by which interval cancers are classified is described. The way in which cases are designated false-negative is an issue of acceptability for radiologists, and so three different methods are evaluated. Each is applied to the data set collected in this region over a 3-year period. RESULTS: For cases read by five readers, when a consensus method was used for classifying cases, the proportion of cases classified as false-negative was 14%. Using a method in which only one of the five readers had to classify a case as false-negative for it to be categorized as such, the proportion of false-negative cases rose to a maximum of 38%. The minimum proportion of cases that could be considered to be false-negative was 6% and was obtained when all five readers had to classify a case as false-negative for it to be so categorized. Consistent with its majority viewpoint, the consensus method gave results for proportions of total cases classified as false-negative which were similar to those given by methods in which cases are classified as false-negative if either three of five readers, or at least 60% of readers, classified it as such. CONCLUSION: For the peer review method to achieve its dual aims of educating radiologists and auditing performance, the participating radiologists must share ownership of the results and view the analysis as fair. The method used to classify interval cancers as false-negative will influence the number so classified. A consensus method has been found to give a result that is both fair and acceptable to our radiologist. Using this method 16% of all reviewed cases were classified as false-negative and 60% as true interval cancers. Britton, P. D. (2001). Clinical Radiology56, 44-49. Copyright 2001 The Royal College of Radiologists.
AIM: To devise a method for reviewing interval cancers that will both educate radiologists and facilitate improvement of breast screening practice. To evaluate different methods for case classification to find one that best serves this purpose. METHOD: The method of peer review and the means by which interval cancers are classified is described. The way in which cases are designated false-negative is an issue of acceptability for radiologists, and so three different methods are evaluated. Each is applied to the data set collected in this region over a 3-year period. RESULTS: For cases read by five readers, when a consensus method was used for classifying cases, the proportion of cases classified as false-negative was 14%. Using a method in which only one of the five readers had to classify a case as false-negative for it to be categorized as such, the proportion of false-negative cases rose to a maximum of 38%. The minimum proportion of cases that could be considered to be false-negative was 6% and was obtained when all five readers had to classify a case as false-negative for it to be so categorized. Consistent with its majority viewpoint, the consensus method gave results for proportions of total cases classified as false-negative which were similar to those given by methods in which cases are classified as false-negative if either three of five readers, or at least 60% of readers, classified it as such. CONCLUSION: For the peer review method to achieve its dual aims of educating radiologists and auditing performance, the participating radiologists must share ownership of the results and view the analysis as fair. The method used to classify interval cancers as false-negative will influence the number so classified. A consensus method has been found to give a result that is both fair and acceptable to our radiologist. Using this method 16% of all reviewed cases were classified as false-negative and 60% as true interval cancers. Britton, P. D. (2001). Clinical Radiology56, 44-49. Copyright 2001 The Royal College of Radiologists.
Authors: Diana S M Buist; Melissa L Anderson; Sebastien J P A Haneuse; Edward A Sickles; Robert A Smith; Patricia A Carney; Stephen H Taplin; Robert D Rosenberg; Berta M Geller; Tracy L Onega; Barbara S Monsees; Lawrence W Bassett; Bonnie C Yankaskas; Joann G Elmore; Karla Kerlikowske; Diana L Miglioretti Journal: Radiology Date: 2011-02-22 Impact factor: 11.105
Authors: Patricia A Carney; Elizabeth Steiner; Martha E Goodrich; Allen J Dietrich; Claudia J Kasales; Julia E Weiss; Todd MacKenzie Journal: Ann Fam Med Date: 2006 Nov-Dec Impact factor: 5.166