Diversity has been embraced as a core value and fundamental priority across medical education in recent years. The benefits of diverse and inclusive medical schools are increasingly understood by senior administrators, faculty, and students.1,2 Medical school deans are incorporating diversity and inclusion into their institution-wide assessments and strategic planning. One resource that has supported institutions in this effort is the AAMC’s Diversity 3.0 Framework.3 The framework was developed to provide a conceptual guide for “innovative, high-performing organizations in promoting a culture of inclusion and a full appreciation of different perspectives.”3 This data-driven approach to diversity and inclusion transformation has resulted in the growth of inclusive policies, programs, and practices at medical schools and teaching hospitals.4-7

Continued progress in understanding the multiple dimensions of diversity and inclusion will need to rely on improving data collection and analysis. One such avenue is the utilization of disaggregated race and ethnicity data. New perspectives on how racial and ethnic minorities choose to self-identify are increasing our understanding of diversity. Broad categories of “Asian” or “Black” may not correlate to an individual’s perceptions of personal group identity.8,9 The rich—and often conflicting—histories and experiences of subpopulations and subgroups are not captured by these broader categories. Recent changes in data collection strategies can now allow AAMC race and ethnicity data to be disaggregated by specific subpopulation. Such enhanced data analysis may better capture distinctions and nuances among members of the same racial and ethnic groups.8-10 Medical education can also use data to take a more intersectional approach to improve understanding of how multiple crosscutting identities (e.g., race and ethnicity, gender, sexual orientation, socioeconomic status, and/or disability) create unique challenges and barriers to success in medical school and academic medicine.11-13 Recent exploration into the trending decline of Black males matriculating to medical school and too few women of color among the faculty highlights how an intersectional analysis of race and gender can aid the field in developing targeted initiatives to address areas of concern.14, 11

The disaggregation of racial and ethnic minority subpopulations is pivotal to grasping a full view of barriers and challenges in professional and graduate education. Asians have often been treated as a “model minority” monolith in medical education. Historically, Native Hawaiians and Other Pacific Islanders have been aggregated with Asians for data collection purposes because of their small sample sizes.15 This data collection strategy fails to account for the social, historical, and economic barriers that Native Hawaiians and Other Pacific Islanders face in accessing educational and professional opportunities.15 Disaggregating often culturally dissimilar racial and ethnic subgroups can allow for a more accurate and nuanced analysis.8,9 When Asian medical school applicants are disaggregated (Figure 5), the majority of applicants identify as belonging to East Asian or South Asian subgroups. Southeast Asian subgroup applicants—those who are Vietnamese, Cambodian, Indonesian, and Laotian, for example—represent only 5% of all applicants. Southeast Asians apply to medical schools at lower rates than Blacks or African Americans and Hispanics or Latinos. Finally, non-U.S. citizens and non-permanent residents experience challenges different from those of U.S. racial and ethnic minority groups. Data collection practices should maintain clear distinctions between foreign and domestic people of color and not conflate their experiences. A nuanced diversity and inclusion data collection and analysis strategy will allow for a more accurate understanding of underrepresented groups in medicine.

 

 

Medical schools have gradually become more diverse, and in recent years, medical students have become more receptive to the benefits of having culturally competent curricula and diverse classmates and faculty.2 Multifaceted approaches to diversity and inclusion in medical education, such as the Diversity 3.0 Framework, consider compositional diversity as part of a larger analysis that incorporates faculty, student, and staff perspectives about climate and culture.10,3 Institutions that engage in robust climate and culture assessments as part of their missions and strategic plans are in a position to overcome barriers to diversity and inclusion and act on opportunities.3,16 Institutions that recognize the value of new approaches to diversity and inclusion data can create meaningfully inclusive communities with responsive and targeted programs and policies, such as recruitment and mentorship. Medical schools can leverage these data to improve policies and programs around recruitment, retention, mentorship, and resources.10 Enhanced structural improvements to better support underserved faculty, students, and staff can prompt overall changes in institutional climate and culture as individuals feel increasingly valued by their medical school and/or teaching hospital.1

Medical schools and teaching hospitals should strive to consider diversity from the emerging frames of subpopulation and intersectionality. This data disaggregation strategy will allow for a fresh approach to understand how climate and culture affect racial and ethnic subgroups and intersectional groups, such as women of color, in medical education. Future research could expand the current value of intersectional work on gender and race/ethnicity with other types of intersectional data collection to better capture lesbian, gay, bisexual, transgender, and queer (LGBTQ), disability, and socioeconomic status by race and ethnicity. New approaches to diversity and inclusion data collection and analysis are essential as medical schools strive to make data-driven institutional changes to reduce disparities in health care and increase equity in medical education.

References

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  2. Mujawar I, Sabatino M, Mitchell SR, et al. A 12-year comparison of students’ perspectives on diversity at a Jesuit medical school. Med Ed Online. 2014. http://www.med-ed-online.net/index.php/meo/article/view/23401.
  3. Diversity 3.0 Learning Series: assessing institutional culture and climate [webcast]. Washington, DC: Association of American Medical Colleges (AAMC); 2013. https://www.aamc.org/initiatives/diversity/learningseries/335954/cultureclimatewebcast.html.
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