Authors: Henderson LM, Benefield T, Marsh MW, Schroeder BF, Durham DD, Yankaskas BC, Bowling JM
Title: The influence of mammographic technologists on radiologists' ability to interpret screening mammograms in community practice.
Journal: Acad Radiol 22(3):278-89
Date: 2015 Mar
Abstract: RATIONALE AND OBJECTIVES: To determine whether the mammographic technologist has an effect on the radiologists' interpretative performance of screening mammography in community practice. MATERIALS AND METHODS: In this institutional review board-approved retrospective cohort study, we included Carolina Mammography Registry data from 372 radiologists and 356 mammographic technologists from 1994 to 2009 who performed 1,003,276 screening mammograms. Measures of interpretative performance (recall rate, sensitivity, specificity, positive predictive value [PPV1], and cancer detection rate [CDR]) were ascertained prospectively with cancer outcomes collected from the state cancer registry and pathology reports. To determine if the mammographic technologist influenced the radiologists' performance, we used mixed effects logistic regression models, including a radiologist-specific random effect and taking into account the clustering of examinations across women, separately for screen-film mammography (SFM) and full-field digital mammography (FFDM). RESULTS: Of the 356 mammographic technologists included, 343 performed 889,347 SFM examinations, 51 performed 113,929 FFDM examinations, and 38 performed both SFM and FFDM examinations. A total of 4328 cancers were reported for SFM and 564 cancers for FFDM. The technologists had a statistically significant effect on the radiologists' recall rate, sensitivity, specificity, and CDR for both SFM and FFDM (P values <.01). For PPV1, variability by technologist was observed for SFM (P value <.0001) but not for FFDM (P value = .088). CONCLUSIONS: The interpretative performance of radiologists in screening mammography varies substantially by the technologist performing the examination. Additional studies should aim to identify technologist characteristics that may explain this variation.
Last Updated: 02 Mar 2015