OBJECTIVE The study objective was to determine whether previously documented effects of clinical decision support on computed tomography for pulmonary embolism in the emergency department (ie, decreased use and increased yield) are due to a decrease in unwarranted variation. We evaluated clinical decision support effect on intra- and inter-physician variability in the yield of pulmonary embolism computed tomography (PE-CT) in this setting. METHODS The study was performed in an academic adult medical center emergency department with 60,000 annual visits. We enrolled all patients who had PE-CT performed 18 months pre- and post-clinical decision support implementation. Intra- and inter-physician variability in yield (% PE-CT positive for acute pulmonary embolism) were assessed. Yield variability was measured using logistic regression accounting for patient characteristics. RESULTS A total of 1542 PE-CT scans were performed before clinical decision support, and 1349 PE-CT scans were performed after clinical decision support. Use of PE-CT decreased from 26.5 to 24.3 computed tomography scans/1000 patient visits after clinical decision support (P < .02); yield increased from 9.2% to 12.6% (P < .01). Crude inter-physician variability in yield ranged from 2.6% to 20.5% before clinical decision support and from 0% to 38.1% after clinical decision support. After controlling for patient characteristics, the post-clinical decision support period showed significant inter-physician variability (P < .04). Intra-physician variability was significant in 3 of the 25 physicians (P < .04), all with increased yield post-clinical decision support. CONCLUSIONS Overall PE-CT yield increased after clinical decision support implementation despite significant heterogeneity among physicians. Increased inter-physician variability in yield after clinical decision support was not explained by patient characteristics alone and may be due to variable physician acceptance of clinical decision support. Clinical decision support alone is unlikely to eliminate unwarranted variability, and additional strategies and interventions may be needed to help optimize acceptance of clinical decision support to maximize returns on national investments in health information technology.