Abstract
OBJECTIVE. The purpose of this study was to determine whether diagnostic radiologists impart variation into resource use and patient outcomes in emergency department (ED) patients undergoing CT for headache. MATERIALS AND METHODS. This was a single-institution retrospective quality assurance cohort study of 25,596 unique adult ED patients undergoing head CT for headache from January 2012 to October 2017. CT examinations were interpreted by 55 attending radiologists (25 neuroradiologists, 30 radiologists of other specialties) who each interpreted a mean of 1469.8 ± 787.9 CT examinations. Risk adjustment for variables thought to influence outcome included baseline risk (demographics, Elixhauser comorbidity score), clinical factors (vital signs, ED triage and pain scores, laboratory data, hydrocephalus, prior intracranial hemorrhage, neurosurgical consultation within last 12 months), and system factors (time of CT, physician experience, neuroradiology training). Multivariable models were built to analyze the effect of individual radiologists on subsequent outcomes. Any p value less than 0.007 was considered significant after Bonferroni correction. RESULTS. The study found 57.5% (14,718/25,596) of CT interpretations were performed by neuroradiologists, and most patients (98.1% [25,119/25,596]) had no neurosurgical history. After risk adjustment, individual radiologists were not an independent predictor of hospital admission (p = 0.49), 30-day readmission (p = 0.30), 30-day mortality (p = 0.14), or neurosurgical intervention (p = 0.04) but did predict MRI use (p < 0.001; odds ratio [OR] range among radiologists, 0.009-38.2), neurology consultation (p < 0.001; OR range, 0.4-3.2), and neurosurgical consultation (p < 0.001; OR range, 0.1-9.9). CONCLUSION. Radiologists with different skills, experience, and practice patterns appear interchangeable for major clinical outcomes when interpreting CT for headache in the ED, but their differences predict differential use of downstream health care resources. Resource use measures are potential quality indicators in this cohort.