Assessment of Differences in Academic Rank and Compensation by Gender and Race/Ethnicity Among Academic Radiation Oncologists in the United States

PURPOSE: Advancing equity, diversity, and inclusion in the physician workforce is essential to providing high-quality and culturally responsive patient care and has been shown to improve patient outcomes. To better characterize equity in the field of radiation oncology, we sought to describe the current academic radiation oncology workforce, including any contemporary differences in compensation and rank by gender and race/ethnicity. METHODS AND MATERIALS: We conducted a retrospective cohort study using data from the Society of Chairs of Academic Radiation Oncology Programs (SCAROP) 2018 Financial Survey. Multivariable logistic regression models were used to identify factors associated with associate or full professor rank. Compensation was compared by gender and race/ethnicity overall and stratified by rank and was further analyzed using multivariable linear regression models. RESULTS: Of the 858 academic radiation oncologists from 63 departments in the United States in the sample, 33.2% were female, 65.2% were White, 27.2% were Asian, and 7.6% were underrepresented in medicine (URiM). There were 44.0% assistant professors, 32.0% associate professors, and 22.8% full professors. Multivariable logistic regression analysis for factors associated with associate or full professor rank did not reveal statistically significant associations between gender or race/ethnicity with academic rank (odds ratio [OR], 0.86; 95% confidence interval [CI], 0.56-1.32; P = .48 for gender; OR, 0.81; 95% CI, 0.5-1.30; P = .37 for Asian vs White; and OR, 0.69; 95% CI, 0.31-1.55; P = .37 for URiM vs White), but CIs were wide due to sample size, and point estimates were <1. Similarly, multivariable linear regression analysis modeling the log relative total compensation did not detect statistically significant differences between radiation oncologists by gender (–1.7%; 95% CI, –6.8% to 3.4%; P = .51 for female vs male) or race/ethnicity (–1.6%; 95% CI, –7.3% to 4.0%; P = .57 for Asian vs White and –3.0%; 95% CI, –12.1% to 6.0%; P = .51 for URiM vs White). CONCLUSIONS: The low numbers of women and faculty with URiM race/ethnicity in this radiation oncology faculty sample limits the ability to compare career trajectory and compensation by those characteristics. Given that point estimates were <1, our findings do not contradict larger multispecialty studies that suggest an ongoing need to monitor equity.