Statistical analysis
We examined the association between surgeon-level EMR and surgeon years in practice via linear regression models. To account for differences in the model specifications used for California and New York multivariable risk models, EMRs were standardized by dividing surgeon EMR by the corresponding state’s average mortality rates for isolated CABG, 1.67% for New York and 2.44% for California. This yielded standardized risk relative to each state’s average observed mortality rate. A sensitivity analysis was also performed to ensure EMR was not skewed by surgeons with low case volumes. Observed to expected (O:E) ratios were calculated for each surgeon and analyzed via linear regression with years in practice, with adjustment for case volume. For this O:E ratio regression, case volumes were divided by the average CABG case volumes for the New York and California study periods to account for the longer study period captured in the New York data. We defined statistical significance as p <0.05. All data analysis was performed in R version 3.6.3 (R Foundation for Statistical Computing).