This cross-sectional study examines the association of demographic factors and educational experiences with students’ intention to practice in underserved areas among a national cohort of graduating medical students.
Key Points
Question
What demographic and experiential factors are associated with medical students’ intention to pursue surgery and practice in medically underserved areas?
Findings
In this cross-sectional study of 48 096 graduating medical students interested in pursuing surgery, students who were female, Black, Hispanic, Indian/Pakistani, multiracial Black and White, or had global health or health disparity experiences were more likely to report an intention to practice in underserved areas.
Meaning
These findings highlight the importance of medical schools’ and residency training programs’ social and clinical mission to diversify the surgical workforce and improve the supply of surgeons who are motivated to practice in underserved areas.
Abstract
Importance
The surgical workforce shortage is a threat to promoting health equity in medically underserved areas. Although the Health Resources and Services Administration and the American College of Surgeons have called to increase the surgical pipeline for trainees to mitigate this shortage, the demographic factors associated with students’ intention to practice in underserved areas is unknown.
Objective
To evaluate the association between students’ demographics and medical school experiences with intention to pursue surgery and practice in underserved areas.
Design, Setting, and Participants
This cross-sectional study surveyed graduating US allopathic medical students who matriculated between 2007-2008 and 2011-2012. Analysis began June 2020 and ended December 2020.
Main Outcomes and Measures
Intention to pursue surgery and practice in underserved areas were retrieved from the Association of American Medical Colleges graduation questionnaire. Logistic regression models were constructed to evaluate (1) the association between demographic factors and medical students’ intention to pursue surgical specialties vs medical specialties and (2) the association between demographic factors and medical school electives with intention to practice in underserved areas.
Results
Among 57 307 students who completed the graduation questionnaire, 48 096 (83.9%) had complete demographic data and were included in the study cohort. The mean (SD) age at matriculation was 23.4 (2.5) years. Compared with students who reported intent to pursue nonsurgical careers, a lower proportion of students who reported intent to pursue a surgical specialty identified as female (3264 [32.4%] vs 19 731 [51.9%]; χ2 P < .001). Multiracial Black and White students (adjusted odds ratio [aOR], 1.72; 95% CI, 1.11-2.65) were more likely to report an intent for surgery compared with White students. Among students who reported an intention to pursue surgery, Black/African American students (aOR, 3.24; 95% CI, 2.49-4.22), Hispanic students (aOR, 2.00; 95% CI, 1.61-2.47), multiracial Black and White students (aOR, 2.27; 95% CI, 1.03-5.01), and Indian/Pakistani students (aOR, 1.31; 95% CI, 1.02-1.69) were more likely than White students to report an intent to practice in underserved areas. Students who reported participating in community health (aOR, 1.61; 95% CI, 1.42-1.83) or global health (aOR, 1.83; 95% CI, 1.61-2.07) experiences were more likely to report an intention to practice in underserved areas.
Conclusions and Relevance
This study suggests that diversifying the surgical training pipeline and incorporating health disparity and community health in undergraduate or graduate medical education may promote students’ motivation to practice in underserved areas.
Introduction
Geographical maldistribution of health care professionals across the United States is a major indicator of poor population health.1 The US Health Resources and Services Administration defines a medically underserved area as a geographic area with a shortage of physicians,2 which leads to geographical health disparity that disproportionately affects residents in these areas, including low-income residents and veterans.3,4,5 The Health Resources and Services Administration estimates that the US will reach a critical shortage of surgeons by 2025.6 Surgeons are uniquely trained to provide necessary and lifesaving procedures; therefore, efforts to increase the number of surgeons in underserved areas is critical to address health disparity in the US.
One critical initiative to generate a surgical workforce is to invest in the pipeline of trainees who are interested in practicing in underserved areas. A trainee’s intention to practice in underserved areas is associated with their demographics; female students and students from minoritized race and ethnic groups are more likely to express an intention to practice in underserved areas compared with their peers.7 Therefore, for more than 30 years, there has been a concerted effort to increase medical school admission of underrepresented students.8 Physicians who are underrepresented in medicine (URiM) are more likely to care for more patients insured by Medicaid compared with physicians who are not URiM.9 Despite the many benefits of diversifying the surgical workforce, there is a breadth of data spanning decades demonstrating a dismal lack of both race and ethnic and gender diversity across all surgical specialties.10,11,12,13 Diversification of the surgical workforce to reflect the heterogeneity of the United States’ population will lead to more equitable access and quality of surgical care.14,15,16,17,18
The Health Resources and Services Administration and American College of Surgeons have anticipated a shortage of surgeons that will disproportionately affect underserved areas and have called for the implementation of programs to address the growing dilemma.19,20 The majority of previous research on medical students’ intention to practice in underserved areas has focused on the general medical student population or preferentially focused on students interested in primary care.7,21,22 It is not yet clear how demographic and medical training experiences are associated with the intention of trainees interested in surgery to practice in underserved areas. In this study, we examined the association of demographic factors and educational experiences with students’ intention to practice in underserved areas among a national cohort of graduating medical students. We hypothesized that minoritized backgrounds and community-based experiences were associated with students’ intention to practice in underserved areas. Understanding the characteristics of students interested in pursuing surgical careers and practicing in underserved areas may aid in efforts to enhance access to surgical care in medically underserved areas as they have in primary care.23,24
Methods
Individual-level data were provided by the Association of American Medical Colleges (AAMC) student record system25 and the National Board of Medical Examiners for a national cohort study of 92 012 US medical matriculants from 2007-2008 to 2011-2012. A total of 88 059 students (95.70%) graduated by 2017, when the data were collected from the AAMC. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline.26 The AAMC graduation questionnaire is a national annual survey of graduating medical students.27 Between 2012 and 2017, AAMC graduation questionnaire response rates were between 79.0% and 82.4%. Deidentified records were obtained from the graduation questionnaire databank and merged across survey years prior to analysis. The study’s data include the following categories from the AAMC and National Board of Medical Examiners: sex, race and ethnicity, age at matriculation, parental educational level, degree program at graduation, United States Medical Licensing Examination (USMLE) Step 1 score, planned practice specialty, intention to practice in an underserved area, total student debt on medical school graduation, scholarship awarded during medical school, and participation in electives during medical school. All data were confidential and anonymous. The study was approved by the Albany Medical College Institutional Review Board. Students provided written consent to AAMC.
Data were recategorized prior to analysis. Age at matriculation was used to create a binary variable to identify students who were 23 years or older at matriculation. To determine first-generation status, parental educational attainment of an associate’s degree or less for both parents was included in the first-generation classification. If a student listed either parent’s educational status as a bachelor’s degree or higher, the student was placed in the continuing-generation classification. Race and ethnic categorization was determined based on the self-identification of students. Ethnoracial categories included Hispanic, non-Hispanic American Indian/Alaska Native, non-Hispanic Asian, non-Hispanic Black/African American, non-Hispanic Hawaiian Native/other Pacific Islander, non-Hispanic White, and unknown/other. Students who reported more than 1 racial and ethnic category were categorized as multiracial. Ethnoracial categories were further disaggregated into ethnoracial subgroups within Hispanic, non-Hispanic Asian, and multiracial. Non-Hispanic Asian subgroups included Chinese, Indian/Pakistani, Japanese/multiethnic Asian/other Asian, Korean, and Southeast Asian (Vietnamese and Filipino). Hispanic subgroups included Cuban, Mexican, Puerto Rican, and multiethnic Hispanic (more than 1 Hispanic subgroup). Multiracial subgroups included Asian and Black, Asian and White, Black and White, non-Hispanic American Indian/Alaska Native and non-White, non-Hispanic American Indian/Alaska Native and White, and more than 2 race groups. Total student debt at graduation was coded into 5 levels: no debt, less than $100 000, $100 000 to $199 999, $200 000 to $299 999, and $300 000 or more. Planned area of practice included general surgery, colorectal surgery, neurological surgery, orthopedic surgery, ophthalmology, otolaryngology, plastic surgery, vascular surgery, thoracic surgery, and urology. Students who reported any other specialty were classified as nonsurgery. Students’ intention to practice in underserved areas were classified as yes if a student responded yes and as no if the student responded undecided or no.
Descriptive statistics were conducted, and differences in frequencies between students’ intention to pursue a surgical or nonsurgical specialty were assessed using a χ2 test and analysis of variance. Multivariate logistic regression models were conducted to estimate the adjusted odds ratios (aORs) for the associations of covariates with intention to practice in a surgical specialty and intention to practice in underserved areas. For each outcome, 2 regression models were performed: model 1 was performed with aggregated race and ethnicity (8 race and ethnic categories) and model 2 was performed with disaggregated race and ethnicity (21 race and ethnic categories). Statistics are reported as aORs with 95% CIs from model 1 unless otherwise noted. All statistical analyses were performed using Stata version 16.1 (StataCorp). Two-sided P values were significant at less than .05. Analysis began June 2020 and ended December 2020.
Results
Among 88 059 medical students who graduated, 57 307 (65.09%) completed the graduation questionnaire and indicated a specialty of interest. Compared with nonrespondents, AAMC graduation questionnaire respondents were similarly distributed by sex (female individuals: 29 742 [51.9%] vs 16 053 [52.2%]; χ2 = .70; P = .40), with a higher proportion of White students (36 333 [63.4%] vs 16 268 [52.9%]; χ2 = 308.7; P < .001) in the respondent cohort. Of those, 48 096 students (75.0%) had complete data on demographic and academic characteristics and were included in the study (eFigure in the Supplement). Among 48 096 students in the study cohort, 10 078 (20.9%) reported an intention to pursue a surgical career. Students with a plan for a surgical career had higher mean USMLE Step 1 scores (mean [SE]; 237.6 [16.9] vs 227.8 [20.6]; analysis of variance P < .001; Table 1). Compared with their peers, a higher proportion of male students (6814 [67.6%] vs 18 287 [48.1%]; χ2 = 1215.4; P < .001) and a lower proportion of Black/African American students (333 [3.3%] vs 1691 [4.4%]; χ2 = 25.8; P < .001) reported an intention to pursue a surgical specialty. A higher proportion of students who reported an intention to pursue a surgical field worked on a research project (8787 [87.2%] vs 25 514 [67.1%]; χ2 = 1570.6; P < .001; Table 1) compared with students not interested in a surgical specialty.
Table 1. Characteristics of Graduation Questionnaire Participants From US Allopathic Medical Schools From 2007-2008 to 2011-2012.
| Characteristic | No. (%) | P value | ||
|---|---|---|---|---|
| Total | Intended specialty of practice | |||
| Nonsurgery | Surgerya | |||
| No. | 48 096 | 38 018 (79.0) | 10 078 (21.0) | NA |
| Intention to practice in underserved areas | ||||
| Yes | 12 534 (26.1) | 10 809 (28.4) | 1725 (17.1) | <.001 |
| No or undecided | 35 334 (73.5) | 27 022 (71.1) | 8312 (82.5) | |
| No response | 228 (0.5) | 187 (0.5) | 41 (0.4) | |
| USMLE Step 1 score, mean (SE)b | 229.9 (20.3) | 227.8 (20.6) | 237.6 (17.0) | <.001 |
| Sex | ||||
| Female | 22 995 (47.8) | 19 731 (51.9) | 3264 (32.4) | <.001 |
| Male | 25 101 (52.2) | 18 287 (48.1) | 6814 (67.6) | |
| Age at matriculation, y | ||||
| <23 | 26 500 (55.1) | 21 045 (55.4) | 5455 (54.1) | .03 |
| ≥23 | 21 596 (44.9) | 16 973 (44.6) | 4623 (45.9) | |
| Generation status | ||||
| First-generation college graduate | 5427 (11.3) | 4398 (11.6) | 1029 (10.2) | <.001 |
| Continuing-generation student | 42 669 (88.7) | 33 620 (88.4) | 9049 (89.8) | |
| Race and ethnicity | ||||
| Hawaiian Native/other Pacific Islander | 73 (0.2) | 60 (0.2) | 11 (0.1) | <.001 |
| Non-Hispanic American Indian/Alaska Native | 90 (0.2) | 73 (0.2) | 18 (0.2) | |
| Non-Hispanic Black/African American | 2024 (4.2) | 1691 (4.5) | 333 (3.3) | |
| Non-Hispanic White | 31 510 (65.5) | 24 673 (64.0) | 6837 (67.8) | |
| Non-Hispanic multiracial | 1344 (2.8) | 1055 (2.8) | 290 (2.9) | |
| Asian and Black | 28 (0.06) | 21 (0.06) | 7 (0.1) | |
| Asian and White | 889 (1.9) | 698 (1.8) | 191 (1.9) | |
| Black and White | 128 (0.3) | 96 (0.3) | 32 (0.3) | |
| Non-Hispanic American Indian/Alaska Native and non-White | 29 (0.06) | 22 (0.06) | 7 (0.1) | |
| Non-Hispanic American Indian/Alaska Native and White | 183 (0.4) | 145 (0.4) | 38 (0.4) | |
| >2 Races | 87 (0.2) | 72 (0.2) | 15 (0.1) | |
| Hispanic | 3238 (6.7) | 2633 (6.9) | 605 (6.0) | |
| Cuban | 326 (0.7) | 265 (0.7) | 61 (0.6) | |
| Hispanic (multiethnic) | 161 (0.3) | 135 (0.4) | 26 (0.2) | |
| Hispanic other | 1117 (2.3) | 900 (2.4) | 217 (2.1) | |
| Mexican | 915 (1.9) | 743 (2.0) | 172 (1.7) | |
| Puerto Rican | 726 (1.5) | 595 (1.6) | 131 (1.3) | |
| Non-Hispanic Asian | 8690 (18.1) | 6935 (18.2) | 1755 (17.4) | |
| Chinese | 2533 (5.3) | 1999 (5.3) | 534 (5.3) | |
| Indian/Pakistani | 3282 (6.8) | 2651 (7.0) | 631 (6.2) | |
| Japanese/multiethnic Asian/other Asian | 1146 (2.4) | 926 (2.4) | 220 (2.2) | |
| Korean | 961 (2.0) | 735 (1.9) | 226 (2.2) | |
| Southeast Asian (Vietnamese and Filipino) | 768 (1.6) | 624 (1.6) | 144 (1.4) | |
| Unknown/other | 1129 (2.4) | 900 (2.4) | 229 (2.3) | |
| Degree program | ||||
| Bachelor’s degree and MD | 1000 (2.1) | 780 (2.1) | 220 (2.2) | <.001 |
| MD | 44 355 (92.2) | 34 967 (92.0) | 9388 (93.1) | |
| MD/PhD | 1395 (2.9) | 1186 (3.1) | 209 (2.1) | |
| Other dual degrees | 1346 (2.8) | 1085 (2.9) | 261 (2.6) | |
| Total debt, $ | ||||
| No debt | 6702 (13.9) | 5254 (13.8) | 1448 (14.4) | .01 |
| <100 000 | 7155 (14.9) | 5662 (14.9) | 1493 (14.8) | |
| 100 000-199 999 | 13 056 (27.2) | 10 443 (27.5) | 2613 (25.9) | |
| 200 000-299 999 | 11 654 (24.2) | 9173 (24.1) | 2481 (24.6) | |
| ≥300 000 | 3514 (7.1) | 2731 (7.2) | 783 (7.8) | |
| No response | 6015 (12.5) | 4755 (12.5) | 1260 (12.5) | |
| Acquired a scholarship | ||||
| No | 18 641 (38.8) | 14 797 (38.9) | 3844 (38.1) | .13 |
| Yes | 29 225 (60.8) | 23 030 (60.6) | 6195 (61.5) | |
| No response | 230 (0.5) | 191 (0.5) | 39 (0.4) | |
| Experience in providing health education in the community | ||||
| No | 28 965 (60.2) | 22 950 (60.4) | 6015 (59.7) | .21 |
| Yes | 19 131 (39.8) | 15 068 (39.6) | 4063 (40.3) | |
| Participated in a community-based research project | ||||
| No | 35 007 (72.8) | 27 572 (72.5) | 7435 (73.8) | .01 |
| Yes | 13 089 (27.2) | 10 446 (27.5) | 2643 (26.2) | |
| Experience related to cultural awareness and cultural competency | ||||
| No | 14 898 (31.0) | 11 665 (30.7) | 3233 (32.1) | .007 |
| Yes | 33 198 (69.0) | 26 353 (69.3) | 6845 (67.9) | |
| Participated in educating students about careers in health care professions or biological sciences | ||||
| No | 26 303 (54.7) | 20 988 (55.2) | 5315 (52.7) | <.001 |
| Yes | 21 799 (45.3) | 17 036 (44.8) | 4763 (47.3) | |
| Experience with a free clinic for the underserved population | ||||
| No | 12 496 (26.0) | 9856 (25.9) | 2640 (26.2) | .58 |
| Yes | 35 600 (74.0) | 28 162 (74.1) | 7438 (73.8) | |
| Experience related to health disparities | ||||
| No | 15 022 (31.2) | 11 734 (30.9) | 3288 (32.6) | <.001 |
| Yes | 33 074 (68.8) | 26 284 (69.1) | 6790 (67.4) | |
| Global health experience | ||||
| No | 33 536 (69.7) | 26 278 (69.1) | 7258 (72.0) | <.001 |
| Yes | 14 560 (30.3) | 11 740 (30.9) | 2820 (28.0) | |
| Learned the proper use of the interpreter when needed | ||||
| No | 12 287 (25.6) | 9654 (25.4) | 2633 (26.1) | .13 |
| Yes | 35 809 (74.5) | 28 364 (74.6) | 7445 (73.9) | |
| Learned another language to improve communication with patients | ||||
| No | 36 385 (75.7) | 28 674 (75.4) | 7711 (76.5) | .02 |
| Yes | 11 711 (24.4) | 9344 (24.6) | 2367 (23.5) | |
| Worked on a research project | ||||
| No | 13 795 (28.7) | 12 504 (32.9) | 1291 (12.8) | <.001 |
| Yes | 34 301 (71.3) | 25 514 (67.1) | 8787 (87.2) | |
Abbreviations: NA, not applicable; USMLE, United States Medical Licensing Examination.
Includes general surgery, colorectal surgery, neurosurgery, orthopedic, ophthalmology, otolaryngology, plastic surgery, vascular surgery, thoracic surgery, and urology.
First-attempt USMLE Step 1 score.
Intention for a Surgical Specialty
Students with a higher first-attempt USMLE Step 1 score (aOR, 1.02; 95% CI, 1.02-1.02) and who identified as male (aOR, 1.96; 95% CI, 1.86-2.07) were more likely to report an intent for a surgical career (Table 2). Students with debt were also more likely to report an intent to pursue a surgical field (Table 2). Among ethnoracial groups, multiracial Black and White students (aOR, 1.72; 95% CI, 1.11-2.65) were more likely than non-Hispanic White students to report an intention to pursue surgical specialties. Compared with MD students, MD-PhD (aOR, 0.47; 95% CI, 0.40-0.55) and other dual-degree students (aOR, 0.79; 95% CI, 0.68-0.92) were less likely to report an intent to pursue a surgical residency. No significant association was found for students’ parental education attainment, age at matriculation, or medical school scholarship awards (Table 2).
Table 2. Intention to Pursue Surgery Among Graduation Questionnaire Participants Who Matriculated Between 2007-2008 and 2011-2012.
| Predictors | Adjusted odds ratio (95% CI) | |
|---|---|---|
| Model 1a | Model 2b | |
| USMLE Step 1 scorec | 1.02 (1.02-1.02) | 1.02 (1.02-1.02) |
| Sex | ||
| Female | 1 [Reference] | 1 [Reference] |
| Male | 1.96 (1.86-2.06) | 1.96 (1.86-2.07) |
| Age at matriculation, y | ||
| <23 | 1 [Reference] | 1 [Reference] |
| ≥23 | 1.00 (0.95-1.06) | 1.01 (0.96-1.07) |
| Generation status | ||
| Continuing-generation college graduate | 1 [Reference] | 1 [Reference] |
| First-generation college graduate | 0.99 (0.91-1.07) | 0.98 (0.91-1.07) |
| Race and ethnicity | ||
| Hispanic | 1.03 (0.93-1.15) | NA |
| Cuban | NA | 0.89 (0.65-1.23) |
| Hispanic (multiethnic) | NA | 0.90 (0.56-1.45) |
| Hispanic other | NA | 1.04 (0.88-1.23) |
| Mexican | NA | 1.02 (0.84-1.23) |
| Puerto Rican | NA | 1.15 (0.92-1.43) |
| Non-Hispanic American Indian/Alaska Native | 1.30 (0.73-2.32) | 1.24 (0.71-2.17) |
| Non-Hispanic Asian | 0.94 (0.88-1.00) | NA |
| Chinese | NA | 0.99 (0.89-1.11) |
| Indian/Pakistani | NA | 0.82 (0.74-0.91) |
| Japanese/multiethnic Asian/other Asian | NA | 0.92 (0.78-1.09) |
| Korean | NA | 1.16 (0.98-1.38) |
| Southeast Asian (Vietnamese and Filipino) | NA | 0.98 (0.8-1.2) |
| Non-Hispanic Black/African American | 1.11 (0.97-1.28) | 1.11 (0.97-1.28) |
| Non-Hispanic Hawaiian Native/other Pacific Islander | 1.02 (0.53-1.96) | 0.95 (0.46-1.94) |
| Non-Hispanic White | 1 [Reference] | 1 [Reference] |
| Non-Hispanic multiracial | 1.07 (0.92-1.24) | NA |
| Asian and Black | NA | 1.77 (0.70-4.49) |
| Asian and White | NA | 1.01 (0.84-1.21) |
| Black and White | NA | 1.72 (1.11-2.65) |
| Non-Hispanic American Indian/Alaska Native and non-White | NA | 1.3 (0.48-3.49) |
| Non-Hispanic American Indian/Alaska Native and White | NA | 0.99 (0.66-1.48) |
| >2 Races | NA | 0.88 (0.47-1.64) |
| Unknown/other | 0.90 (0.76-1.05) | 0.89 (0.76-1.05) |
| Degree program | ||
| Bachelor’s degree and MD | 1.14 (0.96-1.35) | 1.17 (0.99-1.39) |
| MD | 1 [Reference] | 1 [Reference] |
| MD/PhD | 0.47 (0.40-0.55) | 0.47 (0.40-0.55) |
| Other dual degrees | 0.79 (0.68-0.92) | 0.79 (0.68-0.92) |
| Total debt, $ | ||
| No debt | 1 [Reference] | 1 [Reference] |
| <100 000 | 0.95 (0.87-1.03) | 0.94 (0.86-1.03) |
| 100 000-199 999 | 0.93 (0.86-1.00) | 0.92 (0.85-0.99) |
| 200 000-299 999 | 1.04 (0.96-1.13) | 1.03 (0.96-1.12) |
| ≥300 000 | 1.19 (1.07-1.33) | 1.18 (1.06-1.32) |
| Acquired a scholarship | ||
| No | 1 [Reference] | 1 [Reference] |
| Yes | 0.96 (0.91-1.01) | 0.96 (0.91-1.01) |
| Experience in providing health education in the community | ||
| No | 1 [Reference] | 1 [Reference] |
| Yes | 1.10 (1.04-1.16) | 1.10 (1.04-1.16) |
| Participated in a community-based research project | ||
| No | 1 [Reference] | 1 [Reference] |
| Yes | 0.95 (0.90-1.01) | 0.95 (0.90-1.01) |
| Experience related to cultural awareness and cultural competency | ||
| No | 1 [Reference] | 1 [Reference] |
| Yes | 0.99 (0.93-1.07) | 0.99 (0.93-1.07) |
| Participated in educating students about careers in health care professions or biological sciences | ||
| No | 1 [Reference] | 1 [Reference] |
| Yes | 1.18 (1.12-1.24) | 1.18 (1.12-1.24) |
| Experience with a free clinic for the underserved population | ||
| No | 1 [Reference] | 1 [Reference] |
| Yes | 1.01 (0.95-1.07) | 1.01 (0.95-1.07) |
| Experience related to health disparities | ||
| No | 1 [Reference] | 1 [Reference] |
| Yes | 0.89 (0.83-0.95) | 0.89 (0.83-0.95) |
| Global health experience | ||
| No | 1 [Reference] | 1 [Reference] |
| Yes | 0.99 (0.93-1.04) | 0.99 (0.93-1.05) |
| Learned the proper use of the interpreter when needed | ||
| No | 1 [Reference] | 1 [Reference] |
| Yes | 0.88 (0.83-0.95) | 0.89 (0.83-0.94) |
| Learned another language to improve communication with patients | ||
| No | 1 [Reference] | 1 [Reference] |
| Yes | 0.97 (0.92-1.04) | 0.97 (0.92-1.03) |
| Worked on a research project | ||
| No | 1 [Reference] | 1 [Reference] |
| Yes | 3.05 (2.84-3.27) | 3.05 (2.84-3.27) |
Abbreviations: NA, not applicable; USMLE, United States Medical Licensing Examination.
Model 1 uses 8 race and ethnic categories (aggregated).
Model 2 uses 21 race and ethnic categories (disaggregated).
First-attempt USMLE Step 1 score.
Intention to Practice in Underserved Areas
Among 10 078 students who report an intention to pursue a surgical field, 1725 (17.1%) indicated that they intended to practice in underserved areas after graduation. Students who attained a higher first-attempt USMLE Step 1 score were less likely to report an intent to practice in underserved areas (aOR, 0.98; 95% CI, 0.98-0.99; Table 3). Compared with female students interested in surgery, male students were less likely to report an intention to practice in underserved areas (aOR, 0.73; 95% CI, 0.64-0.82). Students who matriculated at age older than 23 years were less likely to report an intention to practice in underserved areas (aOR, 0.81; 95% CI, 0.72-0.92). Students who had debt and received a scholarship during medical school were more likely to report an intent to practice in underserved areas (Table 3). Among ethnoracial groups, non-Hispanic Black/African American students (aOR, 3.24; 95% CI, 2.49-4.22) and Hispanic students (aOR, 2.00; 95% CI, 1.61-2.47) were more likely than non-Hispanic White students to report an intent to practice in underserved areas. Disaggregation of ethnoracial groups in model 2 demonstrated that all Hispanic subgroups, multiracial Black and White students (aOR, 2.27; 95% CI, 1.03-5.01), and Indian/Pakistani students (aOR, 1.31; 95% CI, 1.02-1.69) were more likely to report an intent to practice in underserved area compared with non-Hispanic White students.
Table 3. Intention to Practice in Underserved Areas Among Graduation Questionnaire Participants Interested in Surgery.
| Predictors (n = 8812) | Adjusted odds ratio (95% CI) | |
|---|---|---|
| Model 1a | Model 2b | |
| USMLE Step 1 scorec | 0.98 (0.98-0.99) | 0.98 (0.98-0.99) |
| Sex | ||
| Female | 1 [Reference] | 1 [Reference] |
| Male | 0.73 (0.64-0.82) | 0.72 (0.63-0.81) |
| Age at matriculation, y | ||
| <23 | 1 [Reference] | 1 [Reference] |
| ≥23 | 0.81 (0.72-0.92) | 0.80 (0.70-0.9) |
| Generation status | ||
| Continuing-generation college graduate | 1 [Reference] | 1 [Reference] |
| First-generation college graduate | 1.1 (0.92-1.32) | 1.1 (0.92-1.32) |
| Race and ethnicity | ||
| Hispanic | 2.00 (1.61-2.47) | NA |
| Cuban | NA | 2.06 (1.08-3.96) |
| Hispanic (multiethnic) | NA | 3.64 (1.46-9.03) |
| Hispanic other | NA | 1.59 (1.12-2.25) |
| Mexican | NA | 2.33 (1.61-3.37) |
| Puerto Rican | NA | 2.07 (1.34-3.18) |
| Non-Hispanic American Indian/Alaska Native | 2.44 (0.86-6.95) | 2.43 (0.85-6.94) |
| Non-Hispanic Asian | 1.00 (0.85-1.18) | NA |
| Chinese | NA | 0.75 (0.56-1.02) |
| Indian/Pakistani | NA | 1.31 (1.02-1.69) |
| Japanese/multiethnic Asian/other Asian | NA | 1.19 (0.81-1.76) |
| Korean | NA | 0.88 (0.59-1.31) |
| Southeast Asian (Vietnamese and Filipino) | NA | 0.83 (0.50-1.37) |
| Non-Hispanic Black/African American | 3.24 (2.49-4.22) | 3.24 (2.49-4.22) |
| Non-Hispanic Hawaiian Native/other Pacific Islander | 2.27 (0.55-9.39) | 2.29 (0.55-9.48) |
| Non-Hispanic White | 1 [Reference] | 1 [Reference] |
| Non-Hispanic multiracial | 1.33 (0.97-1.83) | NA |
| Asian and Black | NA | 1.82 (0.37-8.89) |
| Asian and White | NA | 1.26 (0.84-1.90) |
| Black and White | NA | 2.27 (1.03-5.01) |
| Non-Hispanic American Indian/Alaska Native and non-White | NA | 1.93 (0.33-11.15) |
| Non-Hispanic American Indian/Alaska Native and White | NA | 0.69 (0.25-1.89) |
| >2 Races | NA | 1.45 (0.41-5.07) |
| Unknown/other | 1.03 (0.68-1.55) | 1.03 (0.68-1.55) |
| Degree program | ||
| Bachelor’s degree and MD | 0.90 (0.58-1.40) | 0.85 (0.55-1.32) |
| MD | 1 [Reference] | 1 [Reference] |
| MD/PhD | 0.35 (0.19-0.66) | 0.35 (0.19-0.66) |
| Other dual degrees | 1.23 (0.89-1.69) | 1.22 (0.88-1.68) |
| Total debt, $ | ||
| No debt | 1 [Reference] | 1 [Reference] |
| <100 000 | 1.23 (0.98-1.54) | 1.24 (0.99-1.56) |
| 100 000-199 999 | 1.26 (1.03-1.54) | 1.27 (1.04-1.56) |
| 200 000-299 999 | 1.39 (1.14-1.7) | 1.40 (1.14-1.72) |
| ≥300 000 | 1.53 (1.19-1.97) | 1.54 (1.20-1.98) |
| Acquired a scholarship | ||
| No | 1 [Reference] | 1 [Reference] |
| Yes | 1.26 (1.1-1.43) | 1.26 (1.11-1.44) |
| Experience in providing health education in the community | ||
| No | 1 [Reference] | 1 [Reference] |
| Yes | 1.22 (1.07-1.38) | 1.22 (1.07-1.38) |
| Participated in a community-based research project | ||
| No | 1 [Reference] | 1 [Reference] |
| Yes | 1.61 (1.42-1.83) | 1.62 (1.42-1.84) |
| Experience related to cultural awareness and cultural competency | ||
| No | 1 [Reference] | 1 [Reference] |
| Yes | 1.12 (0.94-1.34) | 1.11 (0.93-1.33) |
| Participated in educating students about careers in health care professions or biological sciences | ||
| No | 1 [Reference] | 1 [Reference] |
| Yes | 0.94 (0.83-1.07) | 0.94 (0.83-1.06) |
| Experience with a free clinic for the underserved population | ||
| No | 1 [Reference] | 1 [Reference] |
| Yes | 1.08 (0.92-1.26) | 1.08 (0.92-1.26) |
| Experience related to health disparities | ||
| No | 1 [Reference] | 1 [Reference] |
| Yes | 1.25 (1.05-1.49) | 1.25 (1.05-1.50) |
| Global health experience | ||
| No | 1 [Reference] | 1 [Reference] |
| Yes | 1.83 (1.61-2.07) | 1.84 (1.62-2.08) |
| Learned the proper use of the interpreter when needed | ||
| No | 1 [Reference] | 1 [Reference] |
| Yes | 0.77 (0.66-0.90) | 0.77 (0.66-0.90) |
| Learned another language to improve communication with patients | ||
| No | 1 [Reference] | 1 [Reference] |
| Yes | 1.25 (1.09-1.44) | 1.25 (1.09-1.44) |
| Worked on a research project | ||
| No | 1 [Reference] | 1 [Reference] |
| Yes | 0.67 (0.57 − 0.79) | 0.67 (0.56-0.79) |
Abbreviations: NA, not applicable; USMLE, United States Medical Licensing Examination.
Model 1 uses 8 race and ethnic categories (aggregated).
Model 2 uses 21 race and ethnic categories (disaggregated).
First-attempt USMLE Step 1 score.
Experiences during medical school can be associated with students’ intention to practice in underserved areas.21 Students who reported participating in a community-based research project (aOR, 1.61; 95% CI, 1.42-1.83; Table 3), community health education experience (aOR, 1.22; 95% CI, 1.07-1.38), health disparity–related experience (aOR, 1.25; 95% CI, 1.05-1.49), or global health experience (aOR, 1.83; 95% CI, 1.61-2.07) were more likely to report an intention to practice in underserved areas. These data suggest that among students who were interested in surgery, demographic and medical school experiences were associated with their intention to practice in underserved areas.
Intention to Practice in Underserved Areas Across Surgical Specialty
Compared with students who reported an intention to pursue general surgery, students who reported an intention to match into neurological surgery (aOR, 0.40; 95% CI, 0.29-0.54), orthopedic surgery (aOR, 0.49; 95% CI, 0.41-0.58), otolaryngology (aOR, 0.51; 95% CI, 0.41-0.65), plastic surgery (aOR, 0.52; 95% CI, 0.38-0.71), thoracic surgery (aOR, 0.33; 95% CI, 0.19-0.56), and urology (aOR, 0.46; 95% CI, 0.36-0.59) were less likely to report an intention to practice in underserved areas (Table 4). Across all surgical specialties, non-Hispanic Black/African American students have the highest predictive probability of reporting an intention to practice in underserved areas (Figure, A). To understand whether the demographics of students within a specialty were correlated with prevalence of intent to practice in underserved areas, Pearson correlations were performed between percentage of male students, older students, debt, and students who are URiM (non-Hispanic Black/African American, Hispanic, American Indian/Alaska Native/Hawaiian Native/other Pacific Islander, multiracial) with the frequency of reporting intention to practice in underserved areas within each specialty. There was a significant negative correlation between prevalence of intention to practice in underserved areas and percentage of male students (Pearson R2 = 0.482; P = .02) (Figure, D) and no significant correlation with percentage of student debt, URiM, or age at matriculation (Figure, B-E). These data show that prevalence of intention to practice in underserved areas varied across surgical specialties and was significantly correlated with sex diversity.
Table 4. Prevalence of Intention to Practice in Underserved Areas by Surgical Specialty.
| Surgical specialty | Intention to practice in underserved area, No. (%) | Adjusted odds ratio (95% CI)a | |
|---|---|---|---|
| No or undecided | Yes | ||
| Total | 8312 (82.8) | 1725 (17.2) | NA |
| General surgery | 2221 (74.0) | 779 (26.0) | 1 [Reference] |
| Colorectal surgery | 24 (85.7) | 4 (14.3) | 0.45 (0.13-1.41) |
| Ophthalmology | 1051 (80.7) | 251 (19.3) | 0.84 (0.70-1.01) |
| Otolaryngology | 918 (87.5) | 131 (12.5) | 0.51 (0.41-0.65) |
| Orthopedic surgery | 2193 (87.6) | 310 (12.4) | 0.49 (0.41-0.58) |
| Plastic surgery | 385 (87.3) | 56 (12.7) | 0.52 (0.38-0.71) |
| Urology | 776 (88.3) | 103 (11.7) | 0.46 (0.36-0.59) |
| Neurological surgery | 538 (88.9) | 67 (11.1) | 0.40 (0.29-0.54) |
| Vascular surgery | 44 (86.3) | 7 (13.7) | 0.56 (0.25-1.29) |
| Thoracic surgery | 162 (90.5) | 17 (9.5) | 0.33 (0.19-0.56) |
Abbreviation: NA, not applicable.
Adjusting for United States Medical Licensing Examination Step 1 scores, demographics (parental education background, ethnoracial identity, sex, and age at matriculation), degree program, debt, and scholarship.
Figure. Intention to Practice in Underserved Areas Across Surgical Specialty.
IPUA indicates intention to practice in underserved areas; URiM, underrepresented in medicine.
Discussion
This study identified demographic and educational factors associated with graduating medical students’ intention to pursue surgical careers and practice in underserved areas. While previous literature has explored the characteristics of students who intend to match into a surgical postgraduate residency training program, to our knowledge, this is the first study to investigate the intention of graduating medical students interested in surgical careers to practice in underserved areas. We showed that individual characteristics, experiences during medical school, academics, and finances were associated with students’ intention to practice in underserved areas. Among graduating students interested in surgery, female, Black/African American, Hispanic, multiracial Black and White, and Indian/Pakistani students were more likely to have an intention to practice in underserved areas. In addition, those who were younger, received scholarships, or graduated with a significant debt burden were also more likely to intend to practice in underserved areas.
Thirty years ago, the National Health Service Corps was established to generate a physician workforce for rural and urban underserved areas.28 Thirty years later, we are no closer to providing the physician workforce that rural and urban underserved communities deserve.29 The continued shortage of physicians has been attributed, in part, to the lack of progress with accepting a diverse class of medical trainees.8 Although the absolute number of matriculants who are URiM have increased, the relative representation of minoritized race and ethnic groups in relation to the US population remain unchanged.30 Across all surgical specialties, underrepresented students, specifically Black/African American students, had the highest predictive likelihood of practicing in underserved areas. Students who are URiM are significantly underrepresented in all stages of surgical training, although the present study demonstrates that underrepresented students were equally or more likely to be interested in surgery compared with their White colleagues. However, despite their high interest in surgical fields during medical school, students from minoritized race and ethnic groups are significantly underrepresented in surgical residencies.31 From 2004 to 2018, Black representation in the surgical workforce was found to have decreased at a rate of 0.1% per year, which parallels a similar decrease in Black representation in nonsurgical specialties.32 This constant decrease suggests that the diversity leakage occurs early in medical training and identifies medical school admissions as a critical body that can have major roles in diversifying the surgical workforce. Medical school and residency admissions, especially in surgical specialties, traditionally define competitive applicants as those with cognitive abilities to succeed in standardized academic milestones like USMLE Step 1.23,33,34 Existing ethnoracial, sex, and socioeconomic disparity in standardized examination performances and medical student honors, such as Alpha Omega Alpha, suggests that these academic measures may also be an indicator of privilege.35,36,37 Freeman et al33 argued that by prioritizing academic measures such as USMLE Step 1, residency training programs are selecting for a medical trainee cohort that are uninterested in caring for underserved populations. Indeed, we found that among students who were interested in surgery, those who performed well on USMLE Step 1, and were interested in more academically competitive surgical specialties, like orthopedic surgery, were less likely to report an intention to practice in underserved areas. In addition to USMLE Step 1 transitioning being graded on a pass/fail scale in 2022,38 some medical schools have developed targeted admissions policies to meet their social mission of producing community-focused physicians and physician leaders.34 To produce a physician workforce that meets the needs of underserved rural and urban areas, more medical schools and residency programs should adapt the social perspective to redefine the characteristics of a competitive applicant to include selecting applicants that will make a positive impact on the health of society.
In addition to identifying students’ characteristics that promote interest in practicing in underserved areas, it may be possible to increase the attractiveness of surgical specialties for students with interest in practicing in underserved areas. A high prevalence of intention to practice in underserved areas was found to be significantly correlated with sex diversity within specialty. This indicates that surgical specialties that attract more female students, such as general surgery, tend to have a higher percentage of students who report an intention to practice in underserved areas. Women are underrepresented in academic and leadership roles in surgical departments, with greater disparity in surgical subspecialties compared with general surgery.39 Sex-concordance mentorship is an important factor for female medical students interested in surgery.40 Therefore, lack of female representation in surgical leadership positions can directly be associated with female medical students’ choice in surgical specialty.39
In addition to demographic factors, students’ histories and demonstrated commitment in working to benefit society is an important factor in selecting a medical workforce to mitigate the surgeon shortage in underserved areas. Increased personal exposure to medically underserved settings is associated with an intention to practice in those areas.22 Data on geographic retention showed that residents tend to practice where they trained,41,42 suggesting that providing more training infrastructure and increasing residency spots at hospitals located in underserved areas may reduce physician shortage in these areas. In addition, students who attended a medical school with a higher social mission focus were more likely to report intention to practice in underserved areas.21 Among surgical patients, cultural competence is rated as an important factor in quality care.43 These findings suggest that training programs that expose students and residents to community health, rural health, and culturally competent care may be an effective strategy to reduce shortage in the surgical workforce. In the current study, students who participated in a community or global health experience during medical school were more likely to report an intention to practice in underserved areas. Prior studies have also demonstrated that surgery residents who participated in rural rotations are more likely to practice in rural areas.42,44 These experiences offer students and residents the opportunity to build networks and find mentors who may ultimately motivate their interest to practice in underserved areas.
Limitations
The present study has several limitations. The data are based on graduating medical students’ self-reported intention to pursue a surgical career. Therefore, this does not account for whether respondents committed to this career pathway or if they attempted to match into another specialty. This also does not account for physicians who decided to change residencies after graduation. Additionally, a higher proportion of graduation questionnaire respondents identified as White compared with graduation questionnaire nonrespondents. A review of AAMC graduation questionnaire from all schools summary reports indicate that this trend is persistent across graduation questionnaire administration years,27 suggesting that there should be increased efforts to promote graduation questionnaire completion among graduates who are not White across all medical schools. Furthermore, we did not collect data on residency attrition, final area of practice, or include graduates from osteopathic medical schools. Lastly, because these survey responses are self-reported, variability exists in the interpretation of many survey questions. Because the AAMC survey did not distinguish a specific definition of underserved, there may be variability in respondents’ perception and understanding of an underserved area.
Conclusions
The present study suggests that for medical schools and residency programs to produce a surgical workforce that will meet the anticipated demand for surgeons in underserved areas, they must carefully consider the selection of students and trainees to medical school and residency, as well as curricular exposure to culturally diverse experiences during training. Residency programs and surgical societies must go further to diversify their leadership to increase the attractiveness of surgical subspecialties to female students and students who are URiM,45 a cohort of students with high intention to practice in underserved areas. However, it is not clear whether medical school and residency programs should prioritize demographic factors or students’ experiential histories as major contributors to students’ interest in practicing in underserved areas. Future studies should evaluate the relative effectiveness of creating innovative programs to increase students’ exposure to community and global health in addition to redefining selection criteria to produce a graduating cohort with a high service-oriented profile. The accreditation bodies of undergraduate and graduate medical education, the Liaison Committee on Medical Education and Accreditation Council for Graduate Medical Education, currently do not evaluate programs based on their social mission. Because medical schools and residencies are responsible for the future health of the nation, we propose that both be held accountable in accreditation processes for tracking service to underserved populations among their graduates.
eFigure. Study sample size flow chart
References
- 1.Kohrs FP, Mainous AG III. The relationship of health professional shortage areas to health status: implications for health manpower policy. Arch Fam Med. 1995;4(8):681-685. doi: 10.1001/archfami.4.8.681 [DOI] [PubMed] [Google Scholar]
- 2.Health Resources & Services Administration . Definitions & explanations. Published 2020. Accessed October 30, 2020. https://www.hrsa.gov/grants/definitions.html
- 3.Boscarino JJ, Figley CR, Adams RE, Urosevich TG, Kirchner HL, Boscarino JA. Mental health status in veterans residing in rural versus non-rural areas: results from the veterans’ health study. Mil Med Res. 2020;7(1):44. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.United States Census Bureau. Nearly One-quarter of veterans live in rural areas, census bureau reports [press release]. Published January 15, 2017. Accessed August 31, 2021. https://www.census.gov/newsroom/press-releases/2017/cb17-15.html
- 5.US Department of Veterans Affairs . Rural veteran health care challenges. Accessed January 10, 2021. https://www.ruralhealth.va.gov/aboutus/ruralvets.asp
- 6.US Department of Health and Human Services . National and Regional Projections of Supply and Demand for Surgical Specialty Practitioners: 2013-2025. Published December 2016. Accessed August 31, 2021. https://bhw.hrsa.gov/sites/default/files/bureau-health-workforce/data-research/surgical-specialty-report.pdf
- 7.Garcia AN, Kuo T, Arangua L, Pérez-Stable EJ. Factors associated with medical school graduates’ intention to work with underserved populations: policy implications for advancing workforce diversity. Acad Med. 2018;93(1):82-89. doi: 10.1097/ACM.0000000000001917 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Nickens HW, Ready TP, Petersdorf RG. Project 3000 by 2000: racial and ethnic diversity in U.S. medical schools. N Engl J Med. 1994;331(7):472-476. doi: 10.1056/NEJM199408183310712 [DOI] [PubMed] [Google Scholar]
- 9.Komaromy M, Grumbach K, Drake M, et al. The role of black and Hispanic physicians in providing health care for underserved populations. N Engl J Med. 1996;334(20):1305-1310. doi: 10.1056/NEJM199605163342006 [DOI] [PubMed] [Google Scholar]
- 10.Butler PD, Longaker MT, Britt LD. Major deficit in the number of underrepresented minority academic surgeons persists. Ann Surg. 2008;248(5):704-711. doi: 10.1097/SLA.0b013e31817f2c30 [DOI] [PubMed] [Google Scholar]
- 11.Stain SC, Higgins RSD. Is increasing the number of faculty as role models the solution to increasing the number of underrepresented physicians? Ann Surg. 2008;248(5):712-713. doi: 10.1097/SLA.0b013e31818bb574 [DOI] [PubMed] [Google Scholar]
- 12.Smith BT, Egro FM, Murphy CP, Stavros AG, Nguyen VT. An evaluation of race disparities in academic plastic surgery. Plast Reconstr Surg. 2020;145(1):268-277. doi: 10.1097/PRS.0000000000006376 [DOI] [PubMed] [Google Scholar]
- 13.Daniels EW, French K, Murphy LA, Grant RE. Has diversity increased in orthopaedic residency programs since 1995? Clin Orthop Relat Res. 2012;470(8):2319-2324. doi: 10.1007/s11999-012-2259-x [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Saha S. Taking diversity seriously: the merits of increasing minority representation in medicine. JAMA Intern Med. 2014;174(2):291-292. doi: 10.1001/jamainternmed.2013.12736 [DOI] [PubMed] [Google Scholar]
- 15.Linos E, Wintroub B, Shinkai K. Diversity in the dermatology workforce: 2017 status update. Cutis. 2017;100(6):352-353. [PMC free article] [PubMed] [Google Scholar]
- 16.Kuczewski MG, Brubaker L. Medical education for “Dreamers”: barriers and opportunities for undocumented immigrants. Acad Med. 2014;89(12):1593-1598. doi: 10.1097/ACM.0000000000000399 [DOI] [PubMed] [Google Scholar]
- 17.Laveist TA, Nuru-Jeter A. Is doctor-patient race concordance associated with greater satisfaction with care? J Health Soc Behav. 2002;43(3):296-306. doi: 10.2307/3090205 [DOI] [PubMed] [Google Scholar]
- 18.Harrington MA, Rankin EA, Ladd AL, Mason BS. The orthopaedic workforce is not as diverse as the population it serves: where are the minorities and the women?: AOA critical issues symposium. J Bone Joint Surg Am. 2019;101(8):e31. doi: 10.2106/JBJS.18.01010 [DOI] [PubMed] [Google Scholar]
- 19.Health Resources & Services Administration . What is a medically underserved area/population (MUA/P)? Accessed August 31, 2021. https://bhw.hrsa.gov/workforce-shortage-areas/shortage-designation#mups
- 20.American College of Surgeons . Ensuring an Adequate Surgical Workforce in Underserved Areas. Leadership & Advocacy Summit 2019: American College of Surgeons; 2019. [Google Scholar]
- 21.Boscardin CK, Grbic D, Grumbach K, O’Sullivan P. Educational and individual factors associated with positive change in and reaffirmation of medical students’ intention to practice in underserved areas. Acad Med. 2014;89(11):1490-1496. doi: 10.1097/ACM.0000000000000474 [DOI] [PubMed] [Google Scholar]
- 22.O’Connell TF, Ham SA, Hart TG, Curlin FA, Yoon JD. A National longitudinal survey of medical students’ intentions to practice among the underserved. Acad Med. 2018;93(1):90-97. doi: 10.1097/ACM.0000000000001816 [DOI] [PubMed] [Google Scholar]
- 23.Larkins S, Michielsen K, Iputo J, et al. Impact of selection strategies on representation of underserved populations and intention to practise: international findings. Med Educ. 2015;49(1):60-72. doi: 10.1111/medu.12518 [DOI] [PubMed] [Google Scholar]
- 24.Grumbach K, Hart LG, Mertz E, Coffman J, Palazzo L. Who is caring for the underserved? a comparison of primary care physicians and nonphysician clinicians in California and Washington. Ann Fam Med. 2003;1(2):97-104. doi: 10.1370/afm.49 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Association of American Medical Colleges . Student records system (SRS). Accessed August 31, 2021. https://www.aamc.org/data-reports/students-residents/report/student-records-system-srs
- 26.von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP; STROBE Initiative . The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Ann Intern Med. 2007;147(8):573-577. doi: 10.7326/0003-4819-147-8-200710160-00010 [DOI] [PubMed] [Google Scholar]
- 27.Association of American Medical Colleges . Graduation questionnaire (GQ). Accessed August 31, 2021. https://www.aamc.org/data-reports/students-residents/report/graduation-questionnaire-gq
- 28.Heisler EJ. The National Health Service Corps. Congressional Research Service. Published April 26, 2018. Accessed August 31, 2021. https://sgp.fas.org/crs/misc/R44970.pdf
- 29.Association of American Medical Colleges . The complexities of physician supply and demand: projections from 2018 to 2033. Published June 2020. Accessed August 31, 2021. https://www.aamc.org/system/files/2020-06/stratcomm-aamc-physician-workforce-projections-june-2020.pdf
- 30.Lett LA, Murdock HM, Orji WU, Aysola J, Sebro R. Trends in racial/ethnic representation among US medical students. JAMA Netw Open. 2019;2(9):e1910490-e1910490. doi: 10.1001/jamanetworkopen.2019.10490 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Nieblas-Bedolla E, Williams JR, Christophers B, Kweon CY, Williams EJ, Jimenez N. Trends in race/ethnicity among applicants and matriculants to US surgical specialties, 2010-2018. JAMA Netw Open. 2020;3(11):e2023509-e2023509. doi: 10.1001/jamanetworkopen.2020.23509 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Bingmer K, Ofshteyn A, Bliggenstorfer JT, Steinhagen E, Stein SL. Where is the leak in the surgeon pipeline? Am J Surg. 2020;220(5):1174-1178. doi: 10.1016/j.amjsurg.2020.06.048 [DOI] [PubMed] [Google Scholar]
- 33.Freeman J, Ferrer RL, Greiner KA. Viewpoint: developing a physician workforce for America’s disadvantaged. Acad Med. 2007;82(2):133-138. doi: 10.1097/ACM.0b013e31802d8d242 [DOI] [PubMed] [Google Scholar]
- 34.Evans DV, Jopson AD, Andrilla CHA, Longenecker RL, Patterson DG. Targeted medical school admissions: a strategic process for meeting our social mission. Fam Med. 2020;52(7):474-482. doi: 10.22454/FamMed.2020.470334 [DOI] [PubMed] [Google Scholar]
- 35.Boatright D, Ross D, O’Connor P, Moore E, Nunez-Smith M. Racial disparities in medical student membership in the Alpha Omega Alpha honor society. JAMA Intern Med. 2017;177(5):659-665. doi: 10.1001/jamainternmed.2016.9623 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Williams M, Kim EJ, Pappas K, et al. The impact of United States Medical Licensing Exam (USMLE) step 1 cutoff scores on recruitment of underrepresented minorities in medicine: a retrospective cross-sectional study. Health Sci Rep. 2020;3(2):e2161. doi: 10.1002/hsr2.161 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Nguyen M, Mason HRC, O’Connor PG, et al. Association of socioeconomic status with Alpha Omega Alpha honor society membership among medical students. JAMA Netw Open. 2021;4(6):e2110730-e2110730. doi: 10.1001/jamanetworkopen.2021.10730 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.United States Medical Licensing Examination. Change to pass/fail score reporting for Step 1. Published 2021. Accessed August 31, 2021. https://www.usmle.org/incus/
- 39.Peel JK, Schlachta CM, Alkhamesi NA. A systematic review of the factors affecting choice of surgery as a career. Can J Surg. 2018;61(1):58-67. doi: 10.1503/cjs.008217 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Faucett EA, McCrary HC, Milinic T, Hassanzadeh T, Roward SG, Neumayer LA. The role of same-sex mentorship and organizational support in encouraging women to pursue surgery. Am J Surg. 2017;214(4):640-644. doi: 10.1016/j.amjsurg.2017.07.005 [DOI] [PubMed] [Google Scholar]
- 41.Association of American Medical Colleges . Report on residents: Table C6: physician retention in state of residency training, by state. Published 2020. Accessed July 24, 2021. https://www.aamc.org/data-reports/students-residents/interactive-data/table-c6-physician-retention-state-residency-training-state
- 42.Deveney K, Deatherage M, Oehling D, Hunter J. Association between dedicated rural training year and the likelihood of becoming a general surgeon in a small town. JAMA Surg. 2013;148(9):817-821. doi: 10.1001/jamasurg.2013.2681 [DOI] [PubMed] [Google Scholar]
- 43.Zhao C, Dowzicky P, Colbert L, Roberts S, Kelz RR. Race, gender, and language concordance in the care of surgical patients: a systematic review. Surgery. 2019;166(5):785-792. doi: 10.1016/j.surg.2019.06.012 [DOI] [PubMed] [Google Scholar]
- 44.Deveney K, Hunter J. Education for rural surgical practice: the Oregon Health & Science University model. Surg Clin North Am. 2009;89(6):1303-1308, viii. doi: 10.1016/j.suc.2009.07.007 [DOI] [PubMed] [Google Scholar]
- 45.Satiani B, Vaccaro PS, Go MR. Diversity in membership and leadership positions in a regional vascular society. J Vasc Surg. 2010;51(4)(suppl):47S-52S. doi: 10.1016/j.jvs.2009.09.063 [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
eFigure. Study sample size flow chart
