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Association of a Simulated Institutional Gender Equity Initiative With Gender-Based Disparities in Medical School Faculty Salaries and Promotions

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Importance Despite progress in narrowing gender-based salary gaps, notable disparities persist in the scientific community. The significance of pay difference may be underestimated, with little data evaluating its effect on lifetime wealth after accounting for factors like time to promotion and savings. Objectives To characterize gender disparities in salary and assess the outcomes associated with a gender equity initiative (GEI). Design, Setting, and Participants Quality improvement study with simulations of salary and additional accumulated wealth (AAW) using retrospectively reviewed Johns Hopkins University School of Medicine annual salary and promotion data. All academic faculty were included in the faculty salary analysis from 2005 (n = 1481) and 2016 (n = 1885). Main Outcomes and Measures Salary and longitudinal promotion data from 2005 to 2016 were used to estimate gender-based differences in salary and time to promotion. The effect of these differences on total salary and AAW, including retirement and salary-based investments, was simulated for a representative male and female faculty member over a 30-year career in 3 scenarios: (1) pre-GEI, (2) post-GEI, and (3) in real time for GEI, beginning with and progressing through these initiatives. Results Analyses of salaries of 1481 faculty (432 women) in 2005 and 1885 faculty (742 women) in 2016 revealed that a decade after GEI implementation, the overall mean (SE) salary gap by gender decreased from −2.6% (1.2%) (95% CI, −5.6% to −0.3%) to −1.9% (1.1%) (95% CI, −4.1% to 0.3%). Simulation of pre-GEI disparities correlated with male faculty collecting an average lifetime AAW of $501 416 more than the equivalent woman, with disparities persisting past retirement. The AAW gap decreased to $210 829 in the real-time GEI simulation and to $66 104 using post-GEI conditions, reflecting success of GEI efforts. Conclusions and Relevance Even small gender-based salary gaps are associated with substantial differences in lifetime wealth, but an institutional commitment to achieving equitable promotion and compensation for women can appreciably reduce these disparities. The findings of this study support broad implementation of similar initiatives without delay, as results may take more than a decade to emerge. A modifiable version of the simulation is provided so that external users may assess the potential disparities present within their own institutions.
Original Investigation | Medical Education
Association of a Simulated Institutional Gender Equity Initiative
With Gender-Based Disparities in Medical School Faculty Salaries
and Promotions
Avani D. Rao, MD; Sarah E. Nicholas, MD; Bartlomiej Kachniarz, MD, MBA; Chen Hu, MS, PhD; Kristin J. Redmond, MD, MPH; Curtiland Deville, MD; Jean L. Wright, MD;
Brandi R. Page, MD; Stephanie Terezakis,MD; Akila N. Viswanathan, MD, MPH; Theodore L. DeWeese, MD; Barbara A. Fivush, MD; Sara R. Alcorn, MD, MPH
Abstract
IMPORTANCE Despite progress in narrowing gender-based salary gaps, notable disparities persist
in the scientific community. The significance of pay difference may be underestimated, with little
data evaluating its effect on lifetime wealth after accounting for factors like time to promotion
and savings.
OBJECTIVES To characterize gender disparities in salary and assess the outcomes associated with a
gender equity initiative (GEI).
DESIGN, SETTING, AND PARTICIPANTS Quality improvement study with simulations of salary and
additional accumulated wealth (AAW) using retrospectively reviewed Johns Hopkins University
School of Medicine annual salary and promotion data. All academic faculty were included in the
faculty salary analysis from 2005 (n = 1481) and 2016 (n = 1885).
MAIN OUTCOMES AND MEASURES Salary and longitudinal promotion data from 2005 to 2016
were used to estimate gender-based differences in salary and time to promotion. The effect of these
differences on total salary and AAW, including retirement and salary-based investments, was
simulated for a representative male and female faculty member over a 30-year career in 3 scenarios:
(1) pre-GEI, (2) post-GEI, and (3) in real time for GEI, beginning with and progressing through these
initiatives.
RESULTS Analyses of salaries of 1481 faculty (432 women) in 2005 and 1885 faculty (742 women)
in 2016 revealed that a decade after GEI implementation, the overall mean (SE) salary gap by gender
decreased from −2.6% (1.2%) (95% CI, −5.6% to −0.3%) to −1.9% (1.1%) (95% CI, −4.1% to 0.3%).
Simulation of pre-GEI disparities correlated with male faculty collecting an average lifetime AAW of
$501 416 more than the equivalent woman, with disparities persisting past retirement. The AAW gap
decreased to $210 829 in the real-time GEI simulation and to $66 104 using post-GEI conditions,
reflecting success of GEI efforts.
CONCLUSIONS AND RELEVANCE Even small gender-based salary gaps are associated with
substantial differences in lifetime wealth, but an institutional commitment to achieving equitable
promotion and compensation for women can appreciably reduce these disparities. The findings of
this study support broad implementation of similar initiatives without delay, as results may take more
than a decade to emerge. A modifiable version of the simulation is provided so that external users
may assess the potential disparities present within their own institutions.
JAMA Network Open. 2018;1(8):e186054. doi:10.1001/jamanetworkopen.2018.6054
Key Points
Question What is the true magnitude of
differences in salary, time to promotion,
and accumulated wealth between male
and female faculty, and how are these
measures associated with a set of
institutional gender equity initiatives?
Findings In this quality improvement
simulation study of salaries of 1481
faculty, the salary gap and time to
promotion decreased after
implementation of gender equity
initiatives; however, small persistent
differences were still associated with
substantial disparities.
Meaning Residual gender-based salary
gaps may lead to substantial differences
in accumulated wealth over the career
course and into retirement, but
institution-wide promotion of equity
initiatives can slowly begin to narrow
the disparity.
+Invited Commentary
+Supplemental content
Author affiliations and article information are
listed at the end of this article.
Open Access. This is an open access article distributed under the terms of the CC-BY License.
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Introduction
Although antidiscrimination laws and policies have improved the position of women over time,
gender-based compensation disparities for women in science have persisted.
1-4
From the available
reports, compensation for men exceeds that for women by approximately 7% to 8% among US
physician researchers,
2,3
nearly 20% among Japanese surgeons,
5
and 25% to 40% between
scientists in public sectors in Europe
6,7
even after controlling for other factors such as years of
experience and rank.
With increasing attention on such inequities faced by female scientists, the Johns Hopkins
University School of Medicine (JHUSOM) reviewed institutional data and noted that there was a lag
in promotion of women to full professorship despite the presence of a significant proportion of
women at the lower faculty ranks. In response, the JHUSOM created the Committee on Faculty
Development and Gender in 2002. The committee first investigated barriers to career promotion by
(1) reviewing faculty representation, attrition, and promotion rates for women; (2) conducting faculty
surveys and departmental director interviews to identify sources of differences in career
progression; and (3) performing annual faculty salary analyses (FSAs) to track salary inequities. The
committee then offered specific recommendations, summarized in the Box.
An oversight committee was created in 2006 to supervise implementation of these
recommendations. In particular, leadership used annual FSAs to target remediation actions toward
departments with higher salary gaps. Committees created templates that standardized criteria for
promotion across departments. Financial and human resources were allotted for the recruitment and
retention of women faculty. The Office of Women in Science and Medicine was created to increase
pathways to leadership, and more than 600 women have participated in its programming to date. To
increase transparency of efforts, JHUSOM continues to publish annual FSAs and interval reports on
the status of women.
Collectively, these efforts—referred to as gender equity initiatives (GEI)—have narrowed salary
and promotional gaps at the JHUSOM. However, a small overall gender-based salary difference of
1.9% persists. While our institutional goal is to achieve 0% difference by the 2018 fiscal year, others
may argue that such single-digit residual gaps are relatively insignificant, thus negating the need for
additional intensive measures to eliminate them completely. Yet when accounting for the cumulative
effect of salary inequity on retirement and investment savings, compounded with issues such as
increased time to promotion (TTP) and longer life expectancy for women, the total impact of even
small gaps may have profound implications for lifetime earning potential and retirement for women.
To better illustrate the true costs of salary inequities, we have simulated the total disparity in lifetime
wealth created by residual gender-based salary differences over the course of a career and into
retirement. In doing so, we highlight the impact of more than a decade of work at JHUSOM and offer
our GEI efforts as a potential framework for use across institutions with the goal of eliminating
this gap.
Methods
Source Data
Annual FSAs were conducted for all JHUSOM faculty members for fiscal years 2005 to 2016,
including information on department, self-reported gender, degree, rank, years in rank, and fiscal
year salary. Data for both MD and non-MD faculty were considered in our evaluation. For the
purposes of our analysis, annual salary for a given fiscal year included full-time equivalent base salary
and supplemental salary for administrative, educational, or clinical roles. Bonus salary data were not
available. All salary values were reported in US dollars. This study met the criteria for institutional
review board review waiver. The authors followed Standards for Quality Improvement Reporting
Excellence (SQUIRE) 2.0 reporting guidelines for reporting quality improvement.
Box. Summary of Recommendations
From the 2005 Final Report
of the Committee on Faculty
Development and Gender From the Johns
Hopkins University School of Medicine
Key Recommendations
Elevate the goal of gender equity to an
essential mission of the institution
Achieve salary equity through continued
close review of faculty salary analyses,
with leadership directing actions toward
departments with salary disparities in
an effort to narrow the gap
Discourage meetings and conferences
from being scheduled outside of normal
business hours to promote inclusion of
women
Dedicate financial resources toward the
recruitment and retention of women to
senior faculty ranks
Expand sexual harassment educational
curriculum
Interview departing women faculty to
identify root causes for attrition
Create a standing oversight committee to
monitor issues related to gender equity
Conduct a faculty survey in 3 years to
assess progress
JAMA Network Open | Medical Education Faculty Career Outcomes Associated With a Simulated Gender Equity Initiative
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Deidentified information from annual FSAs was analyzed by the Johns Hopkins Bloomberg
School of Public Health and published internally to the JHUSOM community. Each FSA reported
unadjusted mean annual salary by gender, subcategorized by faculty rank (assistant professor,
associate professor, or professor) and degree (MD vs non-MD). Annual FSA reports also estimated
gender-based difference in mean annual salary using multivariable linear regressions. These
regressions applied a logarithmic transformation to salary to minimize the impact of outliers and
adjusted for gender, department, department-specific rank, degree, and years in rank. As per model
specifications, the resultant regression coefficients for gender corresponded to the estimated
percentage difference in salary comparing women with otherwise similar men, with negative values
indicating women earning less than men. Regression models available in the FSA included the overall
gender difference and the rank-specific gender difference in salary.
Median TTP by gender was obtained from registrar records for 2 cohorts of faculty hired at the
rank of assistant professor or associate professor. The pre-GEI era cohort reflects TTP for faculty
hired between 1989 and 1990 (prior to GEI implementation) and was examined in November 2005.
The GEI era cohort was hired between 2005 and 2017 and was examined in January 2018.
Outcome Measures and Simulated Scenarios
Simulations were performed to model the association of gender-based differences in salary and TTP
with estimated annual salary and additional accumulated wealth (AAW) over the course of a 30-year
career for otherwise identical representative male and female full-time faculty members. In the
simulation, the faculty was hired as an assistant professor and promoted to associate professor and
then professor. Corresponding salary and TTP were estimated using gender- and rank-specific mean
and median values for these variables from annual FSA and registrar cohort data, respectively. To
demonstrate the impact of institutional efforts to decrease the compensation gap on AAW, we
simulated 3 scenarios:
1. Pre-GEI: Gender-based differences in salary over the career course were estimated using the 2005
fiscal year FSA. Gender differences in TTP at each promotion were obtained using pre-GEI era
cohort data. As such, this scenario simulates gender differences for lifetime AAW for a faculty
member hired in pre-GEI conditions and for whom the pre-GEI salary and TTP inequities remained
constant throughout the career course.
2. Post-GEI: Gender differences in salary over the career course were estimated using the 2016 fiscal
year FSA. Gender differences in TTP were obtained using GEI era cohort data. As such, this
scenario reflects the conditions faced by a faculty member hired in post-GEI conditions and thus
subject to narrowed salary and TTP gaps throughout the career course.
3. Real-time GEI: Data from the 2005 fiscal year FSA were used to simulate baseline gender
differences in salary for an assistant professor hired at that time. Gender differences in TTP were
estimated using GEI era cohort data. At the time of promotion from assistant professor to
associate professor (in xyears for the man and yyears for the woman) and from associate
professor to professor (in x′ years for the man and y′ years for the woman), an increase in the
gender-specific salary reflecting values reported in the corresponding year’s FSA were applied as
follows: baseline salary + (x, x′, y, y′). Thus, this scenario simulates the potential impact of salary
and promotional differences for a faculty member hired in pre-GEI conditions but subject to the
real-time efforts of the GEI.
To assess the differential effects of gender inequities by promotional rank, a secondary set of
simulations were applied to each of the 3 scenarios described. In these simulations, the
representative faculty members’ careers took the following paths: (1) no promotion beyond assistant
professor, (2) promotion only to associate professor, or (3) promotion through full professor
(equivalent to the assumptions of the scenarios described).
For each scenario, we created a projection of both annual salary and AAW based on gender
differences in salaries and TTP over the course of a 30-year career.
JAMA Network Open | Medical Education Faculty Career Outcomes Associated With a Simulated Gender Equity Initiative
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Annual Salary
In all 3 scenarios, the starting salary of the representative male assistant professor was set at
$108 750, which is the average of the mean salaries for a male MD and male non-MD assistant
professor from the 2005 FSA. To ensure that comparisons were made between otherwise similar
men and women, we calculated the corresponding female assistant professor’s salary using the rank-
specific gender difference in salary for a given scenario, as estimated by the FSA’s adjusted linear
regression model. This approach was again repeated at each appropriate time for promotion to
associate professor and to professor. Simulations of salary before and after the GEI assumed a 3%
annual increase for cost of living for each year at a given rank until promotion.
8
Additional Accumulated Wealth
Additional accumulated wealth included estimated retirement savings and other salary-based
investments accrued over time. A standard employer contribution to the pretax retirement account
was set at 12% of gross income, reflecting our institutional practice. Each simulation included a pretax
retirement account deposited with maximal employee contributions throughout the 30-year career.
Initial maximum contributions were indexed to an inflation rate of 2%
9
and set at $18 000 through
age 50 as per US federal regulations, with an additional 33% catch-up contribution after age 50.
Take-home pay was estimated as monies received from salary after employee pretax retirement
contributions and deduction of marginal tax rate of 33.45% (8% local, 24% US federal income, and
1.45% Medicare). The simulation assumed equivalent standard of living—and thus equivalent annual
expenses—for both genders. For the simulation, we set the annual expenses equal to the lowest
take-home pay between the genders. Any take-home pay in excess of annual expenses for a given
gender was assumed to be invested in a long-term diversified portfolio.
The equity and bond composition used for retirement and salary-based investments is
described in the eFigure in the Supplement. Expected rate of investment returns were 7% for equity
markets and 3% for bond markets, based on an assumed risk-free rate of 2%, equity risk premium
of 5%, and bond risk premium of 1%.
10,11
Postretirement Wealth
Using the real-time GEI scenario, we calculated postretirement AAW and income, starting with total
AAW accrued at the time of simulated retirement by gender. Additional contribution of retirement
savings to gross postretirement income was calculated based on a graduated annuity with a 20/80
equity/bond investment portfolio return and 2% inflation-adjusted income growth throughout
retirement. We used US Social Security Life Tables
12
to estimate life expectancy and anticipate years
in retirement by gender. Differences in postretirement wealth available for use over the course of
remaining life were compared between genders.
Statistical Considerations
In addition to reporting outcomes for the JHUSOM, a goal of our study was to create an editable
version of the simulation that external users could modify to reflect conditions faced at their own
institutions. In light of this aim, our methodology was selected to optimize generalizability and use
types of data most likely to be accessible. However, our ability to accurately estimate measures of
variance or perform tests of significance for our own institutional data was compromised in order to
meet this greater goal of generalizability.
For example, to protect faculty privacy, the annual FSA information analyzed at JHUSOM is not
published at an individual level; instead, it is best considered as repeated cross-sectional data. We
anticipated this to be the most likely level of available data for external users as well. However, the
deidentified nature of the data prohibited us from direct longitudinal analysis of career trajectories
for specific faculty over time. Moreover, subgroups used to report aggregate measures of central
tendency, regression coefficients, and variance were not uniform within or across FSA reports. To
enhance comparability, some subgroups (such as MD and non-MD faculty) were combined. Given
JAMA Network Open | Medical Education Faculty Career Outcomes Associated With a Simulated Gender Equity Initiative
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these limitations, we determined that we could not accurately specify the large number of
assumptions needed in order to capture variance and perform hypothesis testing for outcomes like
AAW by gender. Microsimulation methods were considered but ultimately not used because the
detailed procedures required to calibrate such simulations to our population would potentially
compromise applicability to external users.
As per FSA analyses, the adjusted regression coefficients and standard errors reflecting the
estimated overall and rank-specific gender difference in salary were reported, and 95% confidence
intervals were specified.
Simulation projections were developed and displayed using Microsoft Excel 2016 and Shiny
version 1.0.5 (RStudio).
Results
A total of 1481 faculty (432 women) in 2005 and 1885 faculty (742 women) in 2016 completed the
FSA. Table 1 shows participant characteristics from the pre- and post-GEI cohorts. In 2005, 31% of
full-time faculty were women, as compared with 39% in 2016. In an adjusted analysis, women’s
salaries were estimated to be a mean (SE) of −2.6% (1.2%) (95% CI, −5.6% to −0.3%) lower than
Table 1. DescriptiveStatistics of Faculty Cohorts Included in Pre-GEI and Post-GEI and Variables Used in Each of the 3 Simulation Scenarios
Characteristic Pre-GEI Post-GEI Real-time
Starting year FSA data 2005 2016 NA
FSA faculty demographic characteristics, No. (%)
Total faculty 1481 1885 NA
Women 452 (31) 742 (39) NA
Men 1029 (69) 1143 (61) NA
Assistant professor, No. (%) 705 897 NA
Women 274 (39) 443 (49) NA
Men 431 (61) 454 (51) NA
Associate professor, No. (%) 390 509 NA
Women 108 (28) 195 (38) NA
Men 282 (72) 314 (62) NA
Professor, No. (%) 386 489 NA
Women 70 (18) 114 (23) NA
Men 316 (82) 375 (77) NA
Assistant professor annual salary for men, $ 108 750
a
108 750
a
108 750
a
Adjusted mean (SE) difference in salary between female vs male assistant
professor [95% CI], %
b
−2.90 (1.6) [−6.0 to 0.2]
a
−3.40 (1.5) [−6.3 to −0.4]
c
−2.90 (1.6) [−6.0 to 0.2]
a
Time to promotion from assistant to associate professor, y
Women 6 4.5 4.5
Men 5 4.9 4.9
Associate professor annual salary for men, $ 159 342
d
154 701
d
156 350
e
Adjusted mean (SE) difference in salary between female vs male associate
professor [95% CI], %
b
−3.60 (2.5) [−8.5 to 1.3]
a
−0.60 (2.1) [−4.6 to 3.6]
c
−3.70 (2.3) [−8.2 to 0.7]
e
Time to promotion from associate to professor, y
Women 7.8 5.3 5.3
Men 6.3 4.4 4.4
Professor annual salary for men, $ 239 749
d
225 987
d
217 450
f
Adjusted mean (SE) difference in salary between female vs male professor
[95% CI], %
b
−1.50 (2.8) [−7.0 to 4.0]
a
0.10 (2.5) [−4.7 to 5.2]
c
−1.5 (2.5) [−6.2 to 3.4]
f
Abbreviations: FSA, faculty salary analysis; GEI, gender equity initiatives; NA, not
applicable.
a
Data from the 2005 FSA.
b
Negative values indicate that women earned less than men.
c
Data from the 2016 FSA.
d
The 2005 FSA mean salary for men at a designated rank, adjusted for a 3% annual
increase to account for cost of living per year corresponding to time to male promotion.
e
Data from 2009 FSA.
f
Data from the 2014 FSA.
JAMA Network Open | Medical Education Faculty Career Outcomes Associated With a Simulated Gender Equity Initiative
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men’s salaries in 2005 across rank, with the overall gap narrowing to −1.9% (1.1%) (95% CI, −4.1% to
0.3%) in 2016. Salary differences generally narrowed with increasing academic rank.
Simulated Association of Gender With Wealth in 3 Scenarios
Figure 1 demonstrates annual salary and AAW over the course of a 30-yearcareer for an equivalent
newly hired woman vs man in the pre-GEI, post-GEI, and real-time GEI scenarios. Salary and TTP data
used for each scenario are outlined in Table 1.
Pre-GEI conditions (Figure 1A) resulted in an additional $501 416 AAW collected by the male
faculty. This was composed of $35 000 from growth of employer retirement contributions and
$466 415 from salary-based investments. Post-GEI (Figure 1B), the male faculty collected an
additional $66 104 AAW, composed of $4831 from growth of employer retirement contributions and
$61 273 from salary-based investments. Narrowed gaps in both TTP and compensation at associate
professor and professor ranks in the post-GEI scenario corresponded to a reduction in the pre-GEI
gender difference in AAW by 87%.
Real-time GEI simulation (Figure 1C) revealed the AAW gap was reduced to $210 829, composed
of $15 883 from growth of employer retirement contributions and $194 946 from salary-based
investments. The real-time GEI scenario was associated with a reduced pre-GEI gender difference in
AAWby58%.
Secondary Simulations for Differential Association by Rank
Figure 2 demonstrates secondary simulations performed to assess for differential effects of gender
inequities by academic rank. Differences in AAW were consistent across all 3 scenarios for faculty
remaining at the assistant professor rank throughout their careers. This is attributable to a starting
salary gap of 2.9% to 3.4% across scenarios for this rank. Post-GEI gender differences in AAW were
minimal for faculty promoted to associate professor or professor. For the real-time GEI scenario,
Figure 1. Simulations of the Association of Gender-Based Inequities With Compensation and Promotion From Assistant to Full Professor
2 500 000
2 000 000
1 500 000
1 000 000
500 000
2 500 000
2 000 000
1 500 000
1 000 000
500 000
450 000
375 000
300 000
225 000
150 000
75 000
2 500 000
2 000 000
1 500 000
1 000 000
500 000
0
0
450 000
375 000
300 000
225 000
150 000
75 000
0
450 000
375 000
300 000
225 000
150 000
75 000
0
0
AAW, $
Years in Career
Pre-GEI
A
302520151050
AAW, pre-GEI, men
AAW, pre-GEI, women
AAW, $
Years in Career
Real time
C
302520151050
AAW, real time, men
AAW, real time, women
Salary, $
Years in Career
302520151050
Salary, pre-GEI, men
Salary, pre-GEI, women
Salary, $
Years in Career
302520151050
Salary, post-GEI, men
Salary, post-GEI, women
Salary, $
Years in Career
302520151050
Salary, real-time, men
Salary, real-time, women
0
AAW, $
Years in Career
Post-GE
B
302520151050
AAW, post-GEI, men
AAW, post-GEI, women
Simulations reflect pre–gender equity initiatives (GEI) (A), post-GEI (B), and real-time (C)
scenarios. Whereas gender differences in annual salary are small across time in all 3
scenarios, the cumulative effect of salary and promotion disparities results in a
significant difference in additional accumulated wealth (AAW) in the pre-GEI and real-
time scenarios of $501 416 and $210829, respectively. The AAW narrows to $66104
using post-GEI conditions, reflecting success of GEI efforts.
JAMA Network Open | Medical Education Faculty Career Outcomes Associated With a Simulated Gender Equity Initiative
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persistent salary gaps correlated with larger gender differences in AAW compared with those in the
post-GEI era despite similarly narrowed TTP gaps.
Association of Life Span With Retirement Income
Life expectancy in the United States for a woman now aged 35 years is 82.25 years, as compared with
78.22 years for a man aged 35 years. Thus, a woman can expect to spend 17.25 years in retirement
past age 65 years as compared with 13.22 years for her male counterpart. To account for lower AAW
and longer life expectancy, a woman would have to spend $0.60 for every $1 spent by her male
counterpart in order for her resources to last through retirement (Figure 3A) in the pre-GEI scenario.
For the real-time and post-GEI scenarios, this corresponds to women spending $0.68 to $0.73,
respectively, for every $1 spent by their male counterparts. Were a woman to spend her retirement
funds at the same rate as her male counterpart, the woman would be expected to deplete her
Figure 2. Simulations of the Association of Gender-Based Inequities With Compensation and Promotion
in Different Career Paths
600 000
500 000
400 000
300 000
200 000
100 000
0
Gender Difference in AAW, $
Pre-GEI Post-GEI Real-Time GEI
No promotion
from assistant
professor
Promotion from assistant
professor to associate
professor only
Promotion from
assistant professor
through professor
Variations of pre–gender equity initiatives (GEI), post-
GEI, and real-time scenarios to simulate the difference
in additional accumulated wealth (AAW) by gender
that may be experienced had both the male and
female faculty members taken the following 30-year
career paths: (1) no promotion beyond assistant
professor, (2) promotion only to associate professor, or
as simulated in the manner described in the text, (3)
progressing through the ranks to full professor. The
magnitude of differences in AAW is smallest in the
post-GEI scenario due to significant narrowing of
gender-based salary and promotional gaps. Residual
AAW differences are most pronounced when the male
and female faculty are not promoted beyond assistant
professor due to baseline salary gaps of 2.9% to 3.4%
across scenarios.
Figure 3. Simulated Postretirement Wealth and Income by Gender
2 500 000
2 000 000
1 500 000
1 000 000
500 000
0
Retirement Account Value, $
Time After Career (Based on Average Life Expectancy by Gender), y
Differential rate of postretirement spending by gender
A
20151050
Men
Women
3 000 000
2 000 000
1 000 000
0
–1 000 000
–2 000 000
–3 000 000
Retirement Account Value, $
Time After Career (Based on Average Life Expectancy by Gender), y
Identical rate of postretirement spending by gender
B
20151050
Men
Women
In this simulation of postretirement wealth and income by gender over the course of
retirement years for the representative woman as compared with her male counterpart
in the pre–gender equity initiatives (GEI), time from retirement to death was 17.25 years
for the woman and 13.22 years for the man. Panel A shows the rateof spending required
for each gender to use all postretirement wealth and income prior to death. Owing to the
cumulative effect of salary and promotional disparities over her career course, a female
faculty would be required spend her retirement savings at a rate 40% slower than her
male counterpart to compensate for less retirement savings and longer life expectancy.
Panel B demonstrates both genders spending postretirement wealth and income at an
identical rate (set to the rate used by male faculty in A). Were she to spend her retirement
wealth at the same rate as her male counterpart, her resources would be depleted 7
years prior to her death (represented by deficit of funds below the zero line).
JAMA Network Open | Medical Education Faculty Career Outcomes Associated With a Simulated Gender Equity Initiative
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account 7 years before her death in the pre-GEI scenario (Figure 3B) and 5 years and 4 years before
her death in the real-time and post-GEI scenarios, respectively.
Modifiable Simulation for External Users
To encourage external users to assess the effect of potential inequities faced at their own institutions,
a modifiable version of our simulation can be found at https://dayflowerio.shinyapps.io/sra-gender-
gap-r-shiny/. Default values entered reflect assumptions made for the pre-GEI scenario. Users can adjust
these values to investigate the impact of assumptions made within our simulation.
Discussion
Our simulations demonstrate that even single-digit gender differences in salaries are associated with
substantial inequities in accumulated lifetime wealth over the course of an academic career in
medicine, particularly when accounting for differences in promotional trajectory. In our pre-GEI
simulation, this was related to a difference of more than half a million dollars in AAW. Moreover, these
differences may track into retirement, where a woman would be required to spend her retirement
savings at a rate 40% slower than her male counterpart to compensate for less retirement savings
and longer life expectancy. To our knowledge, this is the first publication to describe the cumulative,
nonlinear association of gender differences in salary and TTP with lifetime wealth for women
in science.
Importantly, our analyses display the positive impact of an institutional commitment to
eliminating gender inequities. By thoroughly investigating barriers faced by women faculty, the
JHUSOM achieved an overall reduction of the salary gap from 2.6% to 1.9% and near equity in TTP
between genders over the course of a decade. In our simulations, this was linked to a 7.6-fold
reduction in the AAW gap as compared with pre-GEI conditions. Moreover, these data highlight that
outcomes of directed change are not seen immediately; therefore, institutions without GEI in place
should implement similar efforts promptly to prevent further delays in progress toward
gender equity.
While much of the discussion to date has focused on gender-based salary gaps, our data
emphasize the importance of TTP. In post-GEI conditions, the overall salary disparity of 1.9% was
largely driven by persistent statistically significant gaps faced by women in the assistant professor
rank, with salary differentials narrowing to near parity for associate professors and professors.
Because GEI efforts also reduced TTP differences, the effect of early salary inequities on AAW was
minimized for those promoted to higher ranks. Yet as Figure 2 demonstrates, AAW gaps remained
substantial for women who were not promoted. Because women hold less than one-half and
one-third of associate professor and professor positions in the United States, respectively,
13,14
these
data underscore the need to prioritize career development and supportive programs to encourage
retention and promotion of qualified women to senior positions.
Additional steps may be required to further improve gender equity in science. Foremost,
institutions must actively encourage women to enter and remain in the field. A recent survey showed
that 35% of academic medical institutions did not have programs in place to support recruitment,
promotion, and retention of women.
15
Training in negotiation skills,
16
education about implicit
bias,
17,18
coaching and mentoring, and financial support for professional development programs may
further promote a supportive environment for women.
13
Additionally, institutions must commit to
integrating women into leadership roles.
Limitations
A potential limitation of our study is that the nature of our source data limited our ability to perform
tests of significance for outcomes of interest such as AAW differences by gender. As noted, we
selected our methodology to optimize generalizability for external users, including through the use
of our modifiable simulation platform. In turn, this platform enables users to evaluate the effects of
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their own institutional differences in salary by gender or other demographic characteristics of
interest.
A second limitation is that we performed analyses with adjusted A+B data, as base salary (part
A) was not reported separately. This could confound gender-based differences in salary if women are
less likely to participate in or be compensated for administrative, educational, or clinical roles (part
B). Moreover, we did not include bonus salary (part C) in our assessment. To address this, data on
each separate component of salary will be acquired individually in future FSAs.
Our salary data were also averaged across MD vs non-MD faculty and adjusted for department.
Because faculty who are not MDs or who work in women-predominant specialties are often paid
less,
2,19
our simulations may not fully characterize the association of gender inequities with wealth
for these subgroups. However, review of unadjusted average salaries of non-MD faculty suggests a
decrease in salary gaps over time that parallels implementation of GEI. In the pre-GEI era, unadjusted
percentage differences in A+B salary for women vs men were −9.2%, −6.7%, and −7.5% for assistant
professor, associate professor, and professor non-MD faculty, respectively. By 2016, these gaps
changed to −3.8%, −7.5%, and −6.4%, respectively.
Additionally, it is noted that available data were not stratified by race/ethnicity. Women of all
major underrepresented minority groups in the United States earn less than white women, and
women in general earn less than men of the same ethnic or racial group.
20
Thus, the association of
gender-based disparities with wealth might be compounded by race/ethnicity.
21
This remains an
underreported subject, and future studies must be aimed at understanding the added difficulties
faced by women in science who are also members of underrepresented minority groups.
Although we have demonstrated that the effects of workplace gender disparities can persist
past retirement, our analysis assumed that the representative male and female faculty began their
careers equally without debt. In the United States, the median total debt among medical school
graduates was $185 000 in 2015.
22
Because repayment of educational debt generally occurs during
the first 10 to 20 years of employment, this coincides with the time of greatest disparity between the
salaries of women and men. Thus, a female faculty with existing debt may find herself less likely than
her male counterpart to make maximum retirement contributions or other investments during
repayment. As demonstrated in our simulations, these early gender-based differences could be
expected to magnify with time. Again, the association may be even greater for women in
underrepresented minority groups, whose educational debt is often higher than that of their white
counterparts.
22
Because educational debt is associated with lower job satisfaction
23
and physician
burnout,
24,25
it may contribute to attrition rates of women in science.
Conclusions
We have demonstrated the association of a program to support women faculty with substantially
narrowed gender-based salary and TTP differences. Future challenges include maintaining
momentum to address small residual gaps and extending research to include other components
affecting wealth such as baseline debt and differences by race and ethnicity.
ARTICLE INFORMATION
Accepted for Publication: October 24, 2018.
Published: December 21, 2018. doi:10.1001/jamanetworkopen.2018.6054
Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2018 Rao AD et al.
JAMA Network Open.
Corresponding Author: Sara R. Alcorn, MD, MPH, Department of Radiation Oncology and Molecular Radiation
Sciences, Johns Hopkins University School of Medicine, 401 N Broadway, Weinberg Ste 1440, Baltimore, MD 21231
(salcorn2@jhmi.edu).
Author Affiliations: Department of Radiation and Molecular Radiation Sciences, Johns Hopkins University School
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of Medicine, Baltimore, Maryland (Rao, Nicholas, Redmond, Deville, Wright, Page, Terezakis, Viswanathan,
DeWeese, Alcorn); Department of Plastic and Reconstructive Surgery, Johns Hopkins University School of
Medicine, Baltimore, Maryland (Kachniarz); Department of Oncology—Biostatistics and Bioinformatics, Johns
Hopkins University School of Medicine, Baltimore, Maryland (Hu); Department of Pediatrics, Johns Hopkins
University School of Medicine, Baltimore, Maryland (Fivush).
Author Contributions: Dr Alcorn had full access to all of the data in the study and takes responsibility for the
integrity of the data and the accuracy of the data analysis.
Concept and design: Rao, Nicholas, Redmond, Deville, Wright, Page, Terezakis, Viswanathan, DeWeese,
Fivush, Alcorn.
Acquisition, analysis, or interpretation of data: Rao, Nicholas, Kachniarz, Hu, Wright, Alcorn.
Drafting of the manuscript: Rao, Nicholas, Kachniarz, Deville, Wright, Fivush, Alcorn.
Critical revision of the manuscript for important intellectual content: Rao, Nicholas, Kachniarz, Hu, Redmond,
Deville, Wright, Page, Terezakis, Viswanathan, DeWeese, Alcorn.
Statistical analysis: Rao, Kachniarz, Hu, Deville, Alcorn.
Administrative, technical, or material support: Nicholas, Kachniarz, DeWeese.
Supervision: Rao, Redmond, Deville, Page, Terezakis, Viswanathan, Fivush, Alcorn.
Conflict of Interest Disclosures: Dr Hu reported grants from the National Cancer Institute, personal fees from
Merck, and personal fees from Varian Medical Systems outside the submitted work. Dr DeWeeserepor ted grants
from the National Institutes of Health (NIH), grants from the Commonwealth Foundation, and other support from
Digital Harmonic outside the submitted work. Dr Alcorn reported personal fees from Johns Hopkins Hospital and
grants from the NIH outside the submitted work. No other disclosures were reported.
Additional Contributions: Janice Clements, PhD, and Kimberly Skarupski, PhD,both of Johns Hopkins University
School of Medicine, Baltimore, Maryland, provided mentorship in facilitating this study, efforts for collection of
data that were used in this study,and editing assistance. They were not compensated for their contributions.
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eFigure. Graduated Annuity Estimates Used for Retirement and Salary-Based Investments
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Objectives This study aimed to assess residents’ and fellows’ knowledge of finance principles that may affect their personal financial health. Methods A cross-sectional, anonymous, web-based survey was administered to a convenience sample of residents and fellows at two academic medical centers. Respondents answered 20 questions on personal finance and 28 questions about their own financial planning, attitudes, and debt. Questions regarding satisfaction with one’s financial condition and investment-risk tolerance used a 10-point Likert scale (1=lowest, 10=highest). Of 2,010 trainees, 422 (21%) responded (median age 30 years; interquartile range, 28-33). Results The mean quiz score was 52.0% (SD = 19.1). Of 299 (71%) respondents with student loan debt, 144 (48%) owed over $200,000. Many respondents had other debt, including 86 (21%) with credit card debt. Of 262 respondents with retirement savings, 142 (52%) had saved less than $25,000. Respondents’ mean satisfaction with their current personal financial condition was 4.8 (SD = 2.5) and investment-risk tolerance was 5.3 (SD = 2.3). Indebted trainees reported lower satisfaction than trainees without debt (4.4 vs. 6.2, F (1,419) = 41.57, p < .001). Knowledge was moderately correlated with investment-risk tolerance (r=0.41, p < .001), and weakly correlated with satisfaction with financial status (r=0.23, p < .001). Conclusions Residents and fellows had low financial literacy and investment-risk tolerance, high debt, and deficits in their financial preparedness. Adding personal financial education to the medical education curriculum would benefit trainees. Providing education in areas such as budgeting, estate planning, investment strategies, and retirement planning early in training can offer significant long-term benefits.
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Importance: Limited evidence exists on salary differences between male and female academic physicians, largely owing to difficulty obtaining data on salary and factors influencing salary. Existing studies have been limited by reliance on survey-based approaches to measuring sex differences in earnings, lack of contemporary data, small sample sizes, or limited geographic representation. Objective: To analyze sex differences in earnings among US academic physicians. Design, setting, and participants: Freedom of Information laws mandate release of salary information of public university employees in several states. In 12 states with salary information published online, salary data were extracted on 10 241 academic physicians at 24 public medical schools. These data were linked to a unique physician database with detailed information on sex, age, years of experience, faculty rank, specialty, scientific authorship, National Institutes of Health funding, clinical trial participation, and Medicare reimbursements (proxy for clinical revenue). Sex differences in salary were estimated after adjusting for these factors. Exposures: Physician sex. Main outcomes and measures: Annual salary. Results: Among 10 241 physicians, female physicians (n = 3549) had lower mean (SD) unadjusted salaries than male physicians ($206 641 [$88 238] vs $257 957 [$137 202]; absolute difference, $51 315 [95% CI, $46 330-$56 301]). Sex differences persisted after multivariable adjustment ($227 783 [95% CI, $224 117-$231 448] vs $247 661 [95% CI, $245 065-$250 258] with an absolute difference of $19 878 [95% CI, $15 261-$24 495]). Sex differences in salary varied across specialties, institutions, and faculty ranks. For example, adjusted salaries of female full professors ($250 971 [95% CI, $242 307-$259 635]) were comparable to those of male associate professors ($247 212 [95% CI, $241 850-$252 575]). Among specialties, adjusted salaries were highest in orthopedic surgery ($358 093 [95% CI, $344 354-$371 831]), surgical subspecialties ($318 760 [95% CI, $311 030-$326 491]), and general surgery ($302 666 [95% CI, $294 060-$311 272]) and lowest in infectious disease, family medicine, and neurology (mean income, <$200 000). Years of experience, total publications, clinical trial participation, and Medicare payments were positively associated with salary. Conclusions and relevance: Among physicians with faculty appointments at 24 US public medical schools, significant sex differences in salary exist even after accounting for age, experience, specialty, faculty rank, and measures of research productivity and clinical revenue.
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Purpose: Cross-sectional studies have demonstrated gender differences in salaries within academic medicine. No research has assessed longitudinal compensation patterns. This study sought to assess longitudinal patterns by gender in compensation, and to understand factors associated with these differences in a longitudinal cohort. Method: A 17-year longitudinal follow-up of the National Faculty Survey was conducted with a random sample of faculty from 24 U.S. medical schools. Participants employed full-time at initial and follow-up time periods completed the survey. Annual pretax compensation during academic year 2012-2013 was compared by gender. Covariates assessed included race/ethnicity; years since first academic appointment; retention in academic career; academic rank; departmental affiliation; percent effort distribution across clinical, teaching, administrative, and research duties; marital and parental status; and any leave or part-time status in the years between surveys. Results: In unadjusted analyses, women earned a mean of $20,520 less than men (P = .03); women made 90 cents for every dollar earned by their male counterparts. This difference was reduced to $16,982 (P = .04) after adjusting for covariates. The mean difference of $15,159 was no longer significant (P = .06) when adjusting covariates and for those who had ever taken a leave or worked part-time. Conclusions: The continued gender gap in compensation cannot be accounted for by metrics used to calculate salary. Institutional actions to address these disparities include both initial appointment and annual salary equity reviews, training of senior faculty and administrators to understand implicit bias, and training of women faculty in negotiating skills.
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Purpose: Despite sincere commitment to egalitarian, meritocratic principles, subtle gender bias persists, constraining women's opportunities for academic advancement. The authors implemented a pair-matched, single-blind, cluster randomized, controlled study of a gender-bias-habit-changing intervention at a large public university. Method: Participants were faculty in 92 departments or divisions at the University of Wisconsin-Madison. Between September 2010 and March 2012, experimental departments were offered a gender-bias-habit-changing intervention as a 2.5-hour workshop. Surveys measured gender bias awareness; motivation, self-efficacy, and outcome expectations to reduce bias; and gender equity action. A timed word categorization task measured implicit gender/leadership bias. Faculty completed a work-life survey before and after all experimental departments received the intervention. Control departments were offered workshops after data were collected. Results: Linear mixed-effects models showed significantly greater changes post intervention for faculty in experimental versus control departments on several outcome measures, including self-efficacy to engage in gender-equity-promoting behaviors (P = .013). When ≥ 25% of a department's faculty attended the workshop (26 of 46 departments), significant increases in self-reported action to promote gender equity occurred at three months (P = .007). Post intervention, faculty in experimental departments expressed greater perceptions of fit (P = .024), valuing of their research (P = .019), and comfort in raising personal and professional conflicts (P = .025). Conclusions: An intervention that facilitates intentional behavioral change can help faculty break the gender bias habit and change department climate in ways that should support the career advancement of women in academic medicine, science, and engineering.
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Purpose: To assess the medical oncology (MO) physician workforce diversity by race, Hispanic ethnicity, and sex, with attention to trainees. Methods: Public registries were used to assess 2010 differences among MO practicing physicians, academic faculty, and fellows; internal medicine (IM) residents; and the US population, using binomial tests with P < .001 significance adjusting for multiple comparisons. Significant changes in fellow representation from 1986 to 2011 were assessed. Results: Female representation as MO fellows (45.0%) was significantly increased compared with faculty (22.4%) and practicing physicians (27.4%); was no different than IM residents (44.7%, P = .853); and increased significantly, by 1.0% per year. Women were significantly underrepresented as practicing physicians, faculty, and fellows compared with the US population (50.8%). Traditionally underrepresented minorities in medicine (URM) were significantly underrepresented as practicing physicians (7.8%), faculty (5.7%), and fellows (10.9%), versus US population (30.0%). Hispanic MO fellows (7.5%) were increased compared with faculty (3.9%) and practicing physicians (4.1%); Black fellows (3.1%) were no different than faculty (1.8%, P = .0283) or practicing physicians (3.5%, P = .443). When comparing MO fellows versus IM residents, there were no differences for American Indians/Alaska Natives/Native Hawaiians/Pacific Islanders (0.3%, 0.6%, respectively, P = .137) and Hispanics (7.5%, 8.7%, P = .139), unlike Blacks (3.1%, 5.6%, P < .001). There has been no significant change in URM representation, with negligible changes every 5 years for American Indians/Alaska Natives/Native Hawaiians/Pacific Islanders (-0.1%), Blacks (-0.3%), and Hispanics (0.3%). Conclusions: Female fellow representation increased 1% per year over the quarter century indicating historical gains, whereas URM diversity remains unchanged. For Blacks alone, representation as MO fellows is decreased compared with IM residents, suggesting greater disparity in MO training.
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Despite efforts to recruit and retain more women, a stark gender disparity persists within academic science. Abundant research has demonstrated gender bias in many demographic groups, but has yet to experimentally investigate whether science faculty exhibit a bias against female students that could contribute to the gender disparity in academic science. In a randomized double-blind study (n = 127), science faculty from research-intensive universities rated the application materials of a student—who was randomly assigned either a male or female name—for a laboratory manager position. Faculty participants rated the male applicant as significantly more competent and hireable than the (identical) female applicant. These participants also selected a higher starting salary and offered more career mentoring to the male applicant. The gender of the faculty participants did not affect responses, such that female and male faculty were equally likely to exhibit bias against the female student. Mediation analyses indicated that the female student was less likely to be hired because she was viewed as less competent. We also assessed faculty participants’ preexisting subtle bias against women using a standard instrument and found that preexisting subtle bias against women played a moderating role, such that subtle bias against women was associated with less support for the female student, but was unrelated to reactions to the male student. These results suggest that interventions addressing faculty gender bias might advance the goal of increasing the participation of women in science.
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Objective Greater numbers of women in medicine have not resulted in more women achieving senior positions. Programs supporting the recruitment, promotion, and retention of women in academic medicine could help to achieve greater advancement of more women to leadership positions. Qualitative research was conducted to understand such programs at 23 institutions and, using the social ecological model, examine how they operate at the individual, interpersonal, institutional, academic community, and policy levels. Methods Telephone interviews were conducted with faculty representatives (n = 44) of the Group on Women in Medicine and Science, Diversity and Inclusion, or senior leaders with knowledge on gender climate in 24 medical schools. Four trained interviewers conducted semistructured interviews that addressed faculty perceptions of gender equity and advancement, which were audiotaped and transcribed. The data were categorized into three content areas—recruitment, promotion, and retention—and coded a priori for each area based on their social ecological level of operation. Findings Participants from nearly 40% of the institutions reported no special programs for recruiting, promoting, or retaining women, largely describing such programming as unnecessary. Existing programs primarily targeted the individual and interpersonal levels simultaneously, via training, mentoring, and networking, or the institutional level, via search committee trainings, child and elder care, and spousal hiring programs. Lesser effort at the academic community and policy levels were described. Conclusions Our findings demonstrate that many U.S. medical schools have no programs supporting gender equity among medical faculty. Existing programs primarily target the individual or interpersonal level of the social ecological interaction. The academic community and broader policy environment require greater focus as levels with little attention to advancing women's careers. Universal multilevel efforts are needed to more effectively advance the careers of medical women faculty and support gender equity.
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England’s health secretary, Jeremy Hunt, is commissioning a report on how to reduce and eliminate the gap in pay between the sexes in the medical profession.1 Here are five facts about the gender pay gap 1. In 2004 male doctors earned 21% more than their female colleagues in the United Kingdom, and by 2013 …
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Background: In Japan, gender inequality between males and females in the medical profession still exists. We examined gender gaps in surgeons' incomes. Methods: Among 8,316 surgeons who participated in a 2012 survey by the Japan Surgical Society, 546 women and 1,092 men within the same postgraduation year were selected randomly with a female-to-male sampling ratio of 1:2 (mean age, 36 years; mean time since graduation, 10.6 years). Results: Average annual income was 9.2 million JPY for women and 11.3 million JPY for men (P < .0001). A general linear regression model showed that the average income of men remained 1.5 million JPY greater after adjusting for gender, age, marital status, number of children, number of beds, current position, and working hours (Model 1). In Model 2, in which 2 statistical interaction terms between annual income and gender with marital status and number of children were added together with variables in Model 1, both interactions became significant, and the gender effect became nonsignificant. For men, average annual income increased by 1.1 million JPY (P < .0001) when they were married and by 0.36 million JPY per child (P = .0014). In contrast, for women, annual income decreased by 0.73 million JPY per child (P = .0005). Conclusions: Male surgeons earn more than female surgeons, even after adjusting for other factors that influenced a surgeon's salary. In addition, married men earn more than unmarried men, but no such trend is observed for women. Furthermore, as the number of children increases, annual income increases for men but decreases for women.
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Background: Women have been entering academic medicine in numbers at least equal to their male colleagues for several decades. Most studies have found that women do not advance in academic rank as fast as men and that their salaries are not as great. These studies, however, have typically not had the data to examine equity, that is, do women receive similar rewards for similar achievement? Objective: To examine equity in promotion and salary for female versus male medical school faculty nationally. Design: Mailed survey questionnaire. Setting: 24 randomly selected medical schools in the contiguous United States. Participants: 1814 full-time U.S. medical school faculty in 199-1996, stratified by sex, specialty, and graduation cohort. Measurements: Promotion and compensation of academic medical faculty. Results: Among the 1814 faculty respondents (response rate, 60%), female faculty were less likely to be full professors than were men with similar professional roles and achievement. For example, 66% of men but only 47% of women (P < 0.01) with 15 to 19 years of seniority were full professors. Large deficits in rank for senior faculty women were confirmed in logistic models that accounted for a wide range of other professional characteristics and achievements, including total career publications, years of seniority, hours worked per week, department type, minority status, medical versus nonmedical final degree, and school. Similar multivariable modeling also confirmed gender inequity in compensation. Although base salaries of nonphysician faculty are gender comparable, female physician faculty have a noticeable deficit (-$11 691; P= 0.01). Furthermore, both physician and nonphysician women with greater seniority have larger salary deficits (-$485 per year of seniority; P = 0.01). Limitations: This is a cross-sectional study of a longitudinal phenomenon. No data are available for faculty who are no longer working full-time in academic medicine, and all data are self-reported. Conclusions: Female medical school faculty neither advance as rapidly nor are compensated as well as professionally similar male colleagues. Deficits for female physicians are greater than those for nonphysician female faculty, and for both physicians and non-physicians, women's deficits are greater for faculty with more seniority.