Does Diversity Matter for Health? Experimental Evidence from Oakland
Open accessAbstract
We study the effect of physician workforce diversity on the demand for preventive care among African-American men.In an experiment in Oakland, California, we randomize black men to black or non-black male medical doctors.We use a two-stage design, measuring decisions before (pre-consultation) and after (post-consultation) meeting their assigned doctor.Subjects select a similar number of preventives in the preconsultation stage, but are much more likely to select every preventive service, particularly invasive services, once meeting with a racially concordant doctor.Our findings suggest black doctors could reduce the black-white male gap in cardiovascular mortality by 19%.
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Racial Concordance and the Quality of Medical Care: Evidence from the Military
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The Importance of Concordance Between Patients and Their Subspecialists
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Community Paramedicine Supporting Community Needs: A Scoping Review
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Evaluating situational judgment test use and diversity in admissions at a southern US medical school
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Why Do We Discriminate? Directional Beliefs and Biased Information Processing
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Everyone Must Address Anti-Black Racism in Health Care
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The Race Between Tax Enforcement and Tax Planning: Evidence From a Natural Experiment in ChilePreprint
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Addressing Racial Biases in Medicine: A Review of the Literature, Critique, and Recommendations
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The Supreme Court and the Importance of Diversity in Medicine
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Hospital Allocation and Racial Disparities in Health Care
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Gender Differences in Medical Evaluations: Evidence from Randomly Assigned Doctors
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#Diversity: Conversations on Twitter about Women and Black Men in Medicine
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Racial and ethnic disparities in excess mortality among U.S. veterans during the COVID ‐19 pandemic
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Building an ethnically and racially diverse neurology workforce
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Food Insecurity Among Students in Six Health Professions’ Training Programs
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Debt-Free Medical Education—A Tool for Health Care Workforce Diversity
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Doctor Decision Making and Patient Outcomes
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Expanding the Boundaries of Representative Bureaucracy
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Ensuring psychedelic treatments and research do not leave anyone behind
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The Great Unequalizer: Initial Health Effects of COVID-19 in the United States
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Self-citationRacial and Ethnic Disparities in Cardiovascular Care
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Prejudice in the Health Care System: Remediation Strategies
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Physician Health Management Skills and Patient Outcomes
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Early Career Setbacks and Women’s Career-Family Trade-Off
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Adaptive Correspondence Experiments
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The Importance of a Helping Hand in Education and in Life
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Fallow Lengths and the Structure of Property Rights
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Association Between Utilization of Digital Prenatal Services and Vaginal Birth After Cesarean
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Healthcare Disparities in Cardiovascular Medicine
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Response to “Should Clinicians Be Activists?”
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Acting Against Racism in Departments of Psychiatry
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- Authors
- Alsan, M., Garrick, O., & Graziani, G.
- Affiliations
- National Bureau of Economic Research (US)
- ORCID
- Alsan, Marcella
- Venue
- National Bureau of Economic Research
- Publisher
- National Bureau of Economic Research
- Published
- 2018-06
- OpenAlex
- W3123508566
- Cited by
- 160
- References
- 52
- Citations by year
- 2026: 4 · 2025: 6 · 2024: 17 · 2023: 26 · 2022: 24 · 2021: 25 · 2020: 31 · 2019: 23 · 2018: 2 · 2017: 1 · 2016: 1
- Type
- report
- Language
- en
- Open access
- green
- doi.org
- Locations
- National Bureau of Economic Research (publishedVersion)
- Topics
- Social Sciences › Safety Research › Experimental Behavioral Economics Studies
- Social Sciences › Health › Health disparities and outcomes
- Health Sciences › Health Professions › General Health Professions › Patient-Provider Communication in Healthcare
- Keywords
- physician workforce diversity, racial concordance, preventive medicine, African American men, racial disparities in health, cardiovascular mortality, health care demand, physician-patient interaction
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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