Jing Sasha Jia1, Alexander Lazzaro2, Alcina K Lidder3, Ceyhun Elgin4, Jennifer Alcantara-Castillo3, Steven J Gedde5, Albert S Khouri6, Aakriti Garg Shukla7, Laurence T D Sperber3, Janice C Law8, Yasha S Modi3, Eleanore T Kim3, Jeffrey R SooHoo9, Bryan J Winn10, Royce W Chen11, Lama A Al-Aswad12. 1. Lewis Katz School of Medicine at Temple University, Philadelphia, Pennsylvania. 2. SUNY Downstate Health Sciences University College of Medicine, Brooklyn, New York. 3. NYU Grossman School of Medicine, NYU Langone Health, New York, New York. 4. Columbia University, New York, New York; and Bogazici University, Istanbul, Turkey. 5. Bascom Palmer Eye Institute, University of Miami Miller School of Medicine, Miami, Florida. 6. Institute of Ophthalmology and Visual Science, Rutgers - New Jersey Medical School, Newark, New Jersey. 7. Wills Eye Hospital, Sidney Kimmel Medical College at Thomas Jefferson University, Philadelphia, Pennsylvania. 8. Vanderbilt Eye Institute, Vanderbilt University School of Medicine, Nashville, Tennessee. 9. UCHealth Sue Anschutz-Rodgers Eye Center, University of Colorado School of Medicine, Aurora, Colorado. 10. UCSF Department of Ophthalmology, UCSF School of Medicine, San Francisco, California. 11. Edward S. Harkness Eye Institute, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York. 12. NYU Grossman School of Medicine, NYU Langone Health, New York, New York. Electronic address: Lama.al-aswad@nyulangone.org.
Abstract
PURPOSE: To identify the role of gender and other factors in influencing ophthalmologists' compensation. DESIGN: Cross-sectional study. PARTICIPANTS: U.S. practicing ophthalmologists. METHODS: Between January and March 2020, an anonymous survey was sent to U.S. residency program directors and practicing ophthalmologists who recently completed residency training. Respondents who completed residency ≤ 10 years ago and responded to questions about gender, fellowship training, state of practice, and salary were included. Propensity score match (PSM) analysis was performed with age, academic residency, top residency, fellowship, state median wage, practice type, ethnicity, and number of workdays. Multivariate linear regression (MLR) analysis controlled for additional factors along with the aforementioned variables. MAIN OUTCOME MEASURES: Base starting salary with bonus (SWB) received in the first year of clinical position was the main outcome measure. A multiplier of 1.2 (20%) was added to the base salary to account for bonus. RESULTS: Of 684 respondents, 384 (56% were female, 44% were male) from 68 programs were included. Female ophthalmologists received a mean initial SWB that was $33 139.80 less than that of their male colleagues (12.5%, P = 0.00). The PSM analysis showed an SWB difference of -$27 273.89 (10.3% gap, P = 0.0015). Additionally, SWB differences were calculated with the number of workdays substituted by operating room (OR) days (-$27 793.67 [10.5% gap, P = 0.0013]) and clinic days (-$23 597.57 [8.90% gap, P = 0.0064]) in separate PSM analyses. The SWB differences between genders were significant using MLR analyses, which also controlled for work, clinic, and OR days separately (-$22 261.49, $-18 604.65, and $-16 191.26, respectively; P = 0.017, P = 0.015, P = 0.002, respectively). Gender independently predicted income in all 3 analyses (P < 0.05). Although an association between gender and the attempt to negotiate was not detected, a greater portion of men subjectively reported success in negotiation (P = 0.03). CONCLUSIONS: Female ophthalmologists earn significantly less than their male colleagues in the first year of clinical practice. Salary differences persist after controlling for demographic, educational, and practice type variables with MLR and PSM analyses. These income differences may lead to a substantial loss of accumulated earnings over an individual's career.
PURPOSE: To identify the role of gender and other factors in influencing ophthalmologists' compensation. DESIGN: Cross-sectional study. PARTICIPANTS: U.S. practicing ophthalmologists. METHODS: Between January and March 2020, an anonymous survey was sent to U.S. residency program directors and practicing ophthalmologists who recently completed residency training. Respondents who completed residency ≤ 10 years ago and responded to questions about gender, fellowship training, state of practice, and salary were included. Propensity score match (PSM) analysis was performed with age, academic residency, top residency, fellowship, state median wage, practice type, ethnicity, and number of workdays. Multivariate linear regression (MLR) analysis controlled for additional factors along with the aforementioned variables. MAIN OUTCOME MEASURES: Base starting salary with bonus (SWB) received in the first year of clinical position was the main outcome measure. A multiplier of 1.2 (20%) was added to the base salary to account for bonus. RESULTS: Of 684 respondents, 384 (56% were female, 44% were male) from 68 programs were included. Female ophthalmologists received a mean initial SWB that was $33 139.80 less than that of their male colleagues (12.5%, P = 0.00). The PSM analysis showed an SWB difference of -$27 273.89 (10.3% gap, P = 0.0015). Additionally, SWB differences were calculated with the number of workdays substituted by operating room (OR) days (-$27 793.67 [10.5% gap, P = 0.0013]) and clinic days (-$23 597.57 [8.90% gap, P = 0.0064]) in separate PSM analyses. The SWB differences between genders were significant using MLR analyses, which also controlled for work, clinic, and OR days separately (-$22 261.49, $-18 604.65, and $-16 191.26, respectively; P = 0.017, P = 0.015, P = 0.002, respectively). Gender independently predicted income in all 3 analyses (P < 0.05). Although an association between gender and the attempt to negotiate was not detected, a greater portion of men subjectively reported success in negotiation (P = 0.03). CONCLUSIONS: Female ophthalmologists earn significantly less than their male colleagues in the first year of clinical practice. Salary differences persist after controlling for demographic, educational, and practice type variables with MLR and PSM analyses. These income differences may lead to a substantial loss of accumulated earnings over an individual's career.