Breast subspecialty radiologists make up less than 10% of all radiologists, and most mammograms in the US are interpreted by general Radiologists. The demand for all radiologists to interpret screening mammograms is projected to increase as the U.S. population ages and more women comply with screening guidelines.
Just Recently, the Harvey L Neiman Health Policy Institute and the American College of Radiology National Mammography Database committee published a study investigating characteristics that are associated with the best screening mammography practices. The study concluded geography, breast sub-specialization, diagnostic mammography performance, and diagnostic ultrasound are associated with better screening mammography performance.
This study looked at a data span of 11 years from the National Mammography Database and used the largest sample of radiologists with verified demographic and workforce data. The study included 1,223 radiologists. For each metrics individually, 52%-77% of radiologists demonstrated performance in the acceptable range. 31.7% of radiologists had acceptable performance for all metrics. The study concluded that those who perform diagnostic mammography, breast sub-specialists, and western and midwestern radiologists were most likely to achieve acceptable performance rates. Those who perform breast ultrasound were least likely to have metrics of acceptable performance.
Unfortunately, researchers say the factors that predict performance are poorly understood. Cindy Lee, MD, FACMQ, FSBI, assistant professor of radiology at NYU Grossman School of Medicine, has been quoted as saying, “It was interesting that in many cases certain characteristics predicted higher performance in some areas and, at the same time, lower performance on others.”
For example, radiologists who have more years of experience, who are breast imagers, and who are in academic practice, are more likely to have higher recall rates. On the other hand, they are also more likely to detect ductal carcinoma in situ, have higher cancer detection rates which, in turn, helps reduce breast cancer mortality. “This example highlights the importance of assessing performance across measures holistically versus individual metrics in isolation, supporting guidance in the ACR BI-RADS atlas,” Lee says.
