Implicit Bias among Physicians and its Prediction of Thrombolysis Decisions for Black and White Patients

By A. Green, D. Carney, D. Pallin, L. Ngo, Kristal L. Raymond, L. Iezzoni, Mahzarin R. Banaji. Journal of general internal medicine, 2007

1,338 citations recorded by the source corpus.

ContextStudies 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.ObjectiveTo 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 ParticipantsAn 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 MeasuresIAT 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.ResultsPhysicians 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).ConclusionsThis 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.

Subfields: Gender Studies, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/dbff4e95b1b122bdbb827838c6828da664e35600

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Citations in the corpus

Physicians and Implicit Bias: How Doctors May Unwittingly Perpetuate Health Care Disparities (2013, background): “provides an example of how simply increasing physicians’ awareness of their susceptibility to implicit bias changes behavior.(7) A subset of participants who were aware that bias was a focus of the investigation were significantly more likely to recommend thrombolysis for Black patients, even if the”
Responsibility for implicit bias (2012, background): “Implicit racial biases have been found in studies that examine biases in healthcare contexts (Green et al., 2007), housing (Kang, 2014; Turner & Ross, 2007), the criminal justice system (Eberhardt, Goff, Purdie, & Davies, 2004), financial decisions (Tetlock, Kristel, Elson, Green, & Lerner, 2000,…”
Racial Disparities in Health Status and Access to Healthcare: The Continuation of Inequality in the United States Due to Structural Racism (2018, background): “More recently, a study found that physicians subconsciously favor Caucasian patients over African American patients (Green et al. 2007: 1234 (Table 1), 1235–1236).”
Selection Problems in the Presence of Implicit Bias (2018, background): “Research on implicit bias argues that unconscious attitudes toward members of different demographic groups — for example, defined by gender, race, ethnicity, national origin, sexual orientation, and other characteristics — can have a non-trivial impact on the way in which we evaluate members of thes”
Implicit Racial/Ethnic Bias Among Health Care Professionals and Its Influence on Health Care Outcomes: A Systematic Review. (2015, methodology): “When treatment recommendation was used as an outcome, Green et al.33 found that physicians demonstrating pro-White bias were less likely to recommend thrombolysis to Black patients and more likely to recommend this treatment of White patients.”
Racial bias in pain assessment and treatment recommendations, and false beliefs about biological differences between blacks and whites (2016, result): “this research has also shown that racial attitudes, measured both implicitly and explicitly, do not predict racial bias in pain perception or treatment (11, 15, 18), with the exception of one study showing that implicit pro-white attitudes predicted physicians’ likelihood of recommending thrombolysi”
Field Experiments on Discrimination (2016, background): “In Atlanta and Boston, doctors with stronger anti-black implicit attitudes were less likely to prescribe thrombolysis for myocardial infarction to African-American patients, compared to white patients (Green et al., 2007).”
The existence of implicit bias is beyond reasonable doubt: A refutation of ideological and methodological objections and executive summary of ten studies that no manager should ignore (2009, neutral): “To address this practical question, Green et al. (2007) conducted a landmark study involving 220 medical doctors completing their residencies at several hospitals in Atlanta and Boston.”
12. Formation, change, and contextualization of mental associations: determinants and principles of variations in implicit measures (2010, background): “…cations have been found to be predictable by re~ sponse latency differences in the range of millisec~ onds obtained by indirect procedures (e.g., Galdi, Arcuri, & Gawronski, 2008; Green et al., 2007; von Hippel, Brener, & von Hippel, 2008; see also Bodenhausen & Todd, Chapter 15, this volume).”
Bias in the Air: A Nationwide Exploration of Teachers’ Implicit Racial Attitudes, Aggregate Bias, and Student Outcomes (2020, background): “Numerous studies have shown IAT performance correlates with racially biased behaviors in individual-level and geographically aggregated data (Green et al., 2007; Greenwald et al., 2009; Hehman 937240 EDRXXX10.”
A multidisciplinary survey on discrimination analysis (2013, methodology): “Finally, Green et al. (2007) use implicit association tests to measure the implicit bias of physicians in treating thrombolysis in black vs. white patients.”
Aversive Racism and Contemporary Bias (2016, background): “Physicians’ implicit biases predict medical recommendations, such as lower quality of coronary care for Black patients (Green et al., 2007), in ways independent of explicit racial bias.”