Factors associated with breast screening radiologists’ annual mammogram reading volume in Italy

La Radiologia medica(2016)

引用 2|浏览22
暂无评分
摘要
Purpose Screening mammogram reading volume (SMRV) and total (screening and clinical) mammogram reading volume (TMRV) per year are strongly associated with the radiologist’s diagnostic performance in breast cancer screening. The current article reports the prevalence and correlates of a SMRV and a TMRV ≥5000 among Italian breast screening radiologists. Materials and methods A questionnaire survey was carried out in 2013–2014 by the Italian Group for Mammography Screening (GISMa). The questionnaire included items of information for radiologist’s experience-related characteristics and for facility-level factors supposedly associated with SMRV and TMRV. Multivariate analysis was performed using backward stepwise multiple logistic regression models. Results Data for 235 radiologists from 51 local screening programmes were received. Of the 222 radiologists who were eligible, 133 (59.9 %) reported a SMRV ≥5000 and 163 (73.4 %) a TMRV ≥5000. Multivariate factors positively associated with both characteristics included: the number of years of experience reading mammograms; the percentage of total working time dedicated to breast imaging and breast care; the participation in diagnostic assessment; and the availability of digital tomosynthesis at facility. Full-time dedication to breast imaging and breast care was associated with the highest odds ratio for a SMRV and a TMRV ≥5000, i.e. 11.80 and 46.74, respectively, versus a percentage of time ≤50 %. An early (<2000) year of implementation of the screening programme and the availability of vacuum-assisted biopsy at facility were associated with a SMRV and, respectively, a TMRV ≥5000. Conclusions Increasing the proportion of radiologists with full-time dedication to breast imaging and breast care qualified as the most effective approach to improve SMRV and TMRV.
更多
查看译文
关键词
Mammogram reading volume,Mammography,Questionnaire,Radiologist,Screening,Survey
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要