Implicit Bias among Physicians and its Prediction of Thrombolysis Decisions for Black and White Patients
Studies documenting racial/ethnic disparities in health care frequently implicate physicians’ unconscious biases. No study to date has measured physicians’ unconscious racial bias to test whether this predicts physicians’ clinical decisions.
To test whether physicians show implicit race bias and whether the magnitude of such bias predicts thrombolysis recommendations for black and white patients with acute coronary syndromes.
Design, Setting, and Participants
An internet-based tool comprising a clinical vignette of a patient presenting to the emergency department with an acute coronary syndrome, followed by a questionnaire and three Implicit Association Tests (IATs). Study invitations were e-mailed to all internal medicine and emergency medicine residents at four academic medical centers in Atlanta and Boston; 287 completed the study, met inclusion criteria, and were randomized to either a black or white vignette patient.
Main Outcome Measures
IAT scores (normal continuous variable) measuring physicians’ implicit race preference and perceptions of cooperativeness. Physicians’ attribution of symptoms to coronary artery disease for vignette patients with randomly assigned race, and their decisions about thrombolysis. Assessment of physicians’ explicit racial biases by questionnaire.
Physicians reported no explicit preference for white versus black patients or differences in perceived cooperativeness. In contrast, IATs revealed implicit preference favoring white Americans (mean IAT score = 0.36, P < .001, one-sample t test) and implicit stereotypes of black Americans as less cooperative with medical procedures (mean IAT score 0.22, P < .001), and less cooperative generally (mean IAT score 0.30, P < .001). As physicians’ prowhite implicit bias increased, so did their likelihood of treating white patients and not treating black patients with thrombolysis (P = .009).
This study represents the first evidence of unconscious (implicit) race bias among physicians, its dissociation from conscious (explicit) bias, and its predictive validity. Results suggest that physicians’ unconscious biases may contribute to racial/ethnic disparities in use of medical procedures such as thrombolysis for myocardial infarction.
- Smedley BD, Stith AY, Nelson, AR, eds. Unequal Treatment: Confronting Racial and Ethnic Disparities in Healthcare. Washington, DC: Institute of Medicine; 2003.
- Kressin, NR, Petersen, LA (2001) Racial differences in the use of invasive cardiovascular procedures: review of the literature and prescription for future research. Ann Intern Med 135: pp. 352-366
- Petersen, LA, Wright, SM, Peterson, ED, Daley, J (2002) Impact of race on cardiac care and outcomes in veterans with acute myocardial infarction. Med Care 40: pp. I86-I96
- Allison, JJ, Kiefe, CI, Centor, RM, Box, JB, Farmer, RM (1996) Racial differences in the medical treatment of elderly Medicare patients with acute myocardial infarction. J Gen Intern Med 11: pp. 736-743 CrossRef
- Canto, JG, Allison, JJ, Kiefe, CI (2000) Relation of race and sex to the use of reperfusion therapy in medicare beneficiaries with acute myocardial infarction. N Engl J Med 342: pp. 1094-1100 CrossRef
- Weitzman, S, Cooper, L, Chambless, L, Rosamond, W, Clegg, L (1997) Gender, racial, and geographic differences in the performance of cardiac diagnostic and therapeutic procedures for hospitalized acute myocardial infarction in four states. Am J Cardiol 79: pp. 722-726 CrossRef
- Taylor, JHA, Canto, JG, Sanderson, B, Rogers, WJ, Hilbe, J (1998) Management and outcomes for black patients with acute myocardial infarction in the reperfusion era. Am J Cardiol 82: pp. 1019-1023 CrossRef
- Physicians for Human Rights. The right to equal treatment. Available at http://www.phrusa.org/research/domestic/race/race_report/index.html. Cited 12 Nov 2005.
- Weisse, CS, Sorum, PC, Sanders, KN, Syat, BL (2001) Do gender and race affect decisions about pain management?. J Gen Intern Med 16: pp. 211-217 CrossRef
- Fincher, C, Williams, JE, MacLean, V, Allison, JJ, Kiefe, CI, Canto, JG (2004) Racial disparities in coronary heart disease: a sociological view of the medical literature on physician bias. Ethn Dis 14: pp. 360-371
- Ayanian, JZ, Cleary, PD, Weissman, JS, Epstein, AM (1999) The effect of patients’ preferences on racial differences in access to renal transplantation. N Engl J Med 341: pp. 1661-1669 CrossRef
- Bogart, LM, Catz, SL, Kelly, JA, Benotsch, EG (2001) Factors influencing physicians’ judgments of adherence and treatment decisions for patients with HIV disease. Med Decis Making 21: pp. 28-36
- Ryn, M (2002) Research on the provider contribution to race/ethnicity disparities in medical care. Med Care 40: pp. I140-I151
- Ryn, M, Burke, J (2000) The effect of patient race and socio-economic status on physicians’ perceptions of patients. Soc Sci Med 50: pp. 813-828 CrossRef
- Schulman, KA, Berlin, JA, Harless, W (1999) The effect of race and sex on physicians’ recommendations for cardiac catheterization. N Engl J Med 340: pp. 618-626 CrossRef
- Devine, PG (1989) Stereotypes and prejudice: their automatic and controlled components. J Pers Soc Psychol 56: pp. 5-18 CrossRef
- Ryn, M, Fu, SS (2003) Paved with good intentions: do public health and human service providers contribute to racial/ethnic disparities in health?. Am J Public Health 93: pp. 248-255 CrossRef
- Einbinder, LC, Schulman, KA (2000) The effect of race on the referral process for invasive cardiac procedures. Med Care Res Rev 57: pp. 162-180 CrossRef
- Greenwald, AG, McGhee, DE, Schwartz, JL (1998) Measuring individual differences in implicit social cognition: the implicit association test. Am J Public Health 74: pp. 1464-1480
- Fazio, RH, Jackson, JR, Dunton, BC, Williams, C (1995) Variability in automatic activation as an unobtrusive measure of racial attitudes: a bona fide pipeline?. J Pers Soc Psychol 69: pp. 1013-1027 CrossRef
- Greenwald, AG, Nosek, BA, Banaji, MR (2003) Understanding and using the implicit association test: an improved scoring algorithm. J Pers Soc Psychol 85: pp. 197-216 CrossRef
- Greenwald, AG, Banaji, MR (1995) Implicit social cognition: attitudes, self–esteem, and stereotypes. Psychol Rev 102: pp. 4-27 CrossRef
- Banaji, MR Implicit attitudes can be measured. In: Roediger, H, Nairne, J, Neath, I, Surprenant, A eds. (2001) The Nature of Remembering: Essays in Honor of Robert G Crowder. American Psychological Association, Washington, DC, pp. 117-150
- Poehlman TA, Uhlmann E, Greenwald AG, Banaji MR. Understanding and using the Implicit Association Test: III. Meta-analysis of predictive validity.
- Cohen, J (1988) Statistical power analysis for the behavior sciences. Earlbaum, Hillsdale, NJ
- Nosek, BA, Banaji, MR, Greenwald, AG (2002) Harvesting implicit group attitudes and beliefs from a demonstration web site. Group Dyn 6: pp. 101-115 CrossRef
- Betancourt, J (2004) Not me! Doctors, decisions, and disparities in health care. Cardiovas Rev Rep 25: pp. 105-109
- Dovidio, JF, Gaertner, SL, Kawakami, K, Hodson, G (2002) Why can’t we just get along? Interpersonal biases and interracial distrust. Cultur Divers Ethnic Minor Psychol 8: pp. 88-102 CrossRef
- Implicit Bias among Physicians and its Prediction of Thrombolysis Decisions for Black and White Patients
- Open Access
- Available under Open Access This content is freely available online to anyone, anywhere at any time.
Journal of General Internal Medicine
Volume 22, Issue 9 , pp 1231-1238
- Cover Date
- Print ISSN
- Online ISSN
- Additional Links
- unconscious bias
- clinical decisions
- Industry Sectors
- Author Affiliations
- 1. The Disparities Solutions Center, Massachusetts General Hospital, Harvard Medical School, 50 Staniford Street, Suite 901, Boston, MA, 02114, USA
- 2. Department of Psychology, Harvard University, Boston, MA, USA
- 3. Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- 4. Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
- 5. University of North Carolina–Chapel Hill, Chapel Hill, NC, USA