Characteristics of High-Performing Radiologists Within Medicare Quality Programs.

Abstract

The aim of this study was to assess radiologists' performance on Medicare quality measures and identify physician characteristics potentially influencing such scores. Medicare quality scores reported by US radiologists in 2015 were obtained from CMS. Associations were explored with publicly available physician characteristic data. Overall, 15,045 radiologists reported 40,427 Medicare quality scores encompassing 25 claims measures, 18 registry measures, and 2 qualified clinical data registry (QCDR) measures. Claims measures included reporting fluoroscopic times (n = 10,152; mean score, 80.3 ± 27.6), carotid ultrasound stenosis (n = 8,940; mean score, 86.8 ± 20.6), inappropriate mammography use of "probably benign" (n = 8,083; mean score, 0.4 ± 3.3), mammography reminders (n = 7,229; mean score, 86.6 ± 29.0), bone scintigraphy correlation (n = 2,712; mean score, 76.0 ± 27.0), and line-related infection prevention (n = 2,226; mean score, 83.3 ± 27.4). Registry measures were reported by ≤17 radiologists. The two QCDR measures were dose index registry participation (n = 246; mean score, 99.5 ± 1.4) and mammography recall rate (n = 77; mean score, 9.0 ± 5.6). Higher scores were observed for radiologists in larger practices (strongest independent predictor), in subspecialized practices, in academic practices, in the South and West, and with fewer years in practice. The fluoroscopic exposure times measure had the best performance scores by musculoskeletal and interventional radiologists, carotid Doppler measure by abdominal radiologists, mammography measures by breast radiologists, bone scintigraphy measure by musculoskeletal and nuclear medicine radiologists, and line infection measure by interventionalists. The dose registry participation QCDR measure had near perfect performance across generalists and subspecialists. Current Medicare performance metrics favor radiologists in larger practices and subspecialized radiologists, possibly reflecting support infrastructures and the narrow focus of most metrics, respectively. These findings may assist targeted data-driven reporting by radiologists and guide efforts to refine existing and develop new metrics.