The Effect of Race and Sex on Physicians' Recommendations for Cardiac Catheterization
Open accessAbstract
BACKGROUND: Epidemiologic studies have reported differences in the use of cardiovascular procedures according to the race and sex of the patient. Whether the differences stem from differences in the recommendations of physicians remains uncertain. METHODS: We developed a computerized survey instrument to assess physicians' recommendations for managing chest pain. Actors portrayed patients with particular characteristics in scripted interviews about their symptoms. A total of 720 physicians at two national meetings of organizations of primary care physicians participated in the survey. Each physician viewed a recorded interview and was given other data about a hypothetical patient. He or she then made recommendations about that patient's care. We used multivariate logistic-regression analysis to assess the effects of the race and sex of the patients on treatment recommendations, while controlling for the physicians' assessment of the probability of coronary artery disease as well as for the age of the patient, the level of coronary risk, the type of chest pain, and the results of an exercise stress test. RESULTS: The physicians' mean (+/-SD) estimates of the probability of coronary artery disease were lower for women (probability, 64.1+/-19.3 percent, vs. 69.2+/-18.2 percent for men; P<0.001), younger patients (63.8+/-19.5 percent for patients who were 55 years old, vs. 69.5+/-17.9 percent for patients who were 70 years old; P<0.001), and patients with nonanginal pain (58.3+/-19.0 percent, vs. 64.4+/-18.3 percent for patients with possible angina and 77.1+/-14.0 percent for those with definite angina; P=0.001). Logistic-regression analysis indicated that women (odds ratio, 0.60; 95 percent confidence interval, 0.4 to 0.9; P=0.02) and blacks (odds ratio, 0.60; 95 percent confidence interval, 0.4 to 0.9; P=0.02) were less likely to be referred for cardiac catheterization than men and whites, respectively. Analysis of race-sex interactions showed that black women were significantly less likely to be referred for catheterization than white men (odds ratio, 0.4; 95 percent confidence interval, 0.2 to 0.7; P=0.004). CONCLUSIONS: Our findings suggest that the race and sex of a patient independently influence how physicians manage chest pain.
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Promoting awareness of the social and historical context of race, the evidence documenting racial disparities in the quality of health care, and the evidence that provider bias may contribute to those disparities may help nurture internal motivation to reduce bias based on a sense of fairness.
“Promoting awareness of the social and historical context of race, the evidence documenting racial disparities in the quality of health care,2 and the evidence that provider bias may contribute to those disparities15 may also help in nurturing internal motivation to reduce bias, based on a sense of fairness.”
From Reducing Racial Bias Among Health Care Providers: Lessons from Social-Cognitive Psychology (2007) · cites this paper as [15]
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RIDDLE: Race and ethnicity Imputation from Disease history with Deep LEarning
Kim, J.-S., Gao, X., & Rzhetsky, A. (2018) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1006106 · Cited by 31 · see citing works
“As an example, it has been reported that referrals for cardiac catheterization are rarer among African American patients than in White patients [2].”
BackgroundPhysicians’ Implicit and Explicit Attitudes About Race by MD Race, Ethnicity, and Gender
Sabin, J. A., Nosek, B. A., Greenwald, A. G., & Rivara, F. P. (2009) · Journal of Health Care for the Poor and Underserved · doi:10.1353/hpu.0.0185 · Cited by 472 · see citing works
- Authors
- Schulman, K. A., Berlin, J. A., Harless, W., Kerner, J. F., Sistrunk, S., Gersh, B. J., Dubé, R., Taleghani, C. K., Burke, J. E., Williams, S., Eisenberg, J. M., Ayers, W., & Escarce, J. J.
- Affiliations
- Georgetown University Medical Center (US)
- Interactive Drama (United States) (US)
- Georgetown Lombardi Comprehensive Cancer Center (US)
- University of Pennsylvania (US)
- ORCID
- Venue
- New England Journal of Medicine
- Publisher
- Massachusetts Medical Society
- Published
- 1999-02-25
- Volume
- 340
- Issue
- 8
- Pages
- 618-626
- ISSN
- 0028-4793 (ISSN-L)
- 1533-4406
- OpenAlex
- W2001371486
- Cited by
- 1,934
- References
- 37
- Citations by year
- 2026: 18 · 2025: 39 · 2024: 47 · 2023: 62 · 2022: 74 · 2021: 68 · 2020: 79 · 2019: 58 · 2018: 56 · 2017: 40 · 2016: 60 · 2015: 52 · 2014: 60 · 2013: 59 · 2012: 68
- FWCI
- 123.81
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- New England Journal of Medicine (publishedVersion)
- PubMed (publishedVersion)
- University Libraries (University of Maryland) (submittedVersion)
- DigitalGeorgetown (Georgetown University Library) (submittedVersion)
- Digital Repository at the University of Maryland (University of Maryland College Park)
- Funders
- Agency for Healthcare Research and Quality (HS07315)
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Sex and Gender in Healthcare
- Social Sciences › Gender Studies › Diversity and Career in Medicine
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Cardiac Imaging and Diagnostics
- Keywords
- cardiac catheterization, physician referral, racial disparities, sex differences, coronary artery disease, chest pain, Black women, gender bias in medicine, racial bias in medicine, coronary risk assessment, angina pectoris, exercise stress testing, primary care physicians, health care disparities
- MeSH terms
- Age Factors, Aged, Angina Pectoris, Attitude of Health Personnel, Chest Pain, Coronary Disease, Data Collection, Decision Making, Female, Cardiac Catheterization, Humans, Male, Middle Aged, Physicians, Physicians, Family, Primary Health Care, Sex Factors, Logistic Models, Patient Selection, Black People, White People
About these checks
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.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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