Women have a higher rate of missed myocardial infarction. Black patients wait longer to receive care in the emergency department for chest pain. Transgender patients get asked questions about their orientation that have nothing to do with their clinical condition. A Latina woman does not get adequate pain medication because she is being “dramatic.” A female physician’s opinion is dismissed by her male colleagues. An older physician views residents as being “lazy” because they get to limit their work hours. Male physicians get paid more and achieve leadership positions more frequently than female physicians. You’ve heard this before and seen the research behind these disparities. None of this is intentional, yet somehow these things continue to happen and are a part of our daily lives. While the causes for these disparities are multifactorial, unconscious bias plays a big role.
Explore This IssueACEP Now: Vol 36 – No 04 – April 2017
Bias is a tendency or an inclination that results in judgment without question. In its most extreme, negative form, it is a prejudice against someone who is not like you that results in some harm to the “other.” It can also be positive. In reality, bias serves two purposes. It helps us to function on a daily basis, and most important, it serves to protect us from harm. Think about it. You are walking down the street at night in an unfamiliar area. Just ahead, you see the shadow of a figure walking toward you and see a glint of light off of a long pointy object in what looks like that figure’s hand. What do most of us instinctively do? We quickly move away from the figure. Why? Because most of us have developed a strong bias against strange and unknown figures holding presumably sharp objects that may cause us harm. While the figure may not be a true threat, our bias causes us to instantaneously perform certain protective actions. It is unlikely that we would approach the figure, do a careful and detailed assessment, review a long list of potential actions, and choose our option—we may not be alive if we did so.
Each of us is a unique individual who has our own individual experiences and education (both formal and informal). These can be described as our “book of rules.” Our “schema” organizes these rules. Together, these form the background, our “lens,” through which we view the world. We are constantly experiencing rules and reshaping our schema and background on a minute-by-minute basis. Background is context, and context is the lens through which we view the world. We cannot help having biases; it is a part of who we are.
No explicit preference for white or black patients or perceived cooperativeness was found. However, the IATs demonstrated implicit preference for white patients and implicit stereotypes of black patients as less cooperative with medical procedures and less cooperative in general.
In 1998, Anthony Greenwald, Debbie McGhee, and Jordan Schwarz created an implicit association test (IAT).1 This tool is the most recognized and commonly used test to measure unconscious bias and measures the strength of automatic associations between concepts (eg, black people, gay people) and evaluations (eg, good and bad). The IAT score is based on how long it takes a person, on average, to associate certain evaluative words with the concept being tested. Thus, if one quickly associates “good” words with “white” and “bad” words with “black,” there may be a preference of white over black. (A more detailed description can be found in the “Education” section at Implicit.Harvard.edu.) Currently, there are 13 tests on the Project Implicit website: Native American, Gender-Science, Asian American, Race (Black-White), Age, Disability, Weight, Presidents, Arab-Muslim, Skin-Tone, Sexuality, Weapons, and Gender-Career.2
Does unconscious bias affect patient care? A study by Green et al using the IAT tested 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 (ACS). Using vignettes of a patient presenting to the emergency department with ACS followed by a questionnaire and three IATs, 287 internal medicine and emergency medicine residents at four academic medical centers in Atlanta and Boston were studied. No explicit preference for white or black patients or perceived cooperativeness was found. However, the IATs demonstrated implicit preference for white patients and implicit stereotypes of black patients as less cooperative with medical procedures and less cooperative in general. As the physicians’ pro-white implicit bias increased so did their likelihood of treating white patients and not treating black patients with thrombolysis. The authors conclude that unconscious bias may contribute to racial/ethnic disparities in the use of medical procedures. While the study is a bit dated (percutaneous coronary intervention is the standard for myocardial infarction), it is the one study linking IAT results to treatment choices. A number of other studies have demonstrated the existence of implicit biases of physicians in race, obesity, gender, and age.4–6
One question that comes up with the IAT is, does it measure prejudice? Research to date has not clarified the answer. The IAT may simply be measuring the association of positive evaluations with the “in,” or majority, group and negative evaluations with the “out,” or minority, group and may not be related to a specific attribute. A study was done in which two versions of an IAT were studied. In the first, the in group was “French and me” and the out group was “North African,” and an IAT effect was found. In the second version, the two categories were “French” and “North African and me.” The IAT effect disappeared. The investigators concluded that in-group/out-group membership, and not nationality, was the important factor.7 What is the importance of the IAT? In my opinion, it is a tool that can be used to stimulate thought about one’s unconscious biases but should not be used to measure one’s prejudices. Preference for a certain group does not equal prejudice against another. Awareness of a preference allows you to consider how your bias may affect your decisions related to the other group. Remember, also, that it is a two-way street. Your patients also have their own implicit biases, and this, too, has the potential to affect decisions regarding compliance with your decisions.
The lives of our patients are affected by bias. It plays a role in how we interpret important clues in the history and physical examination of patients, how we interpret tests, and how we convey information. If your unconscious bias is such that you downplay or discount certain facts or findings, this has the potential to negatively affect patient care (eg, missed myocardial infarction, reduced analgesic treatment, longer wait times, etc.).
What can we do? First, recognize and accept that we have biases. They help us to function and serve to protect us. It is a necessary part of who we are as humans. Reflect on our biases, developing the capacity to shine the light on ourselves. Research has demonstrated that bias blind spots (the ability to “rationally” explain away our biases) are greater in those with higher cognitive ability (eg, physicians). Realize that this is not easy to deal with. Explore the awkwardness and discomfort that comes along with examining our biases and how it affects our daily interactions. Engage with people who we consider “others” and learn and gain experience from them. Finally, get feedback. Ask a trusted person, “How did I do?” This is how we learned our profession. We became educated, sought guidance and feedback, and practiced it over and over.
Dr. Lopez is professor and vice chair in the department of emergency medicine at Thomas Jefferson University Hospital, associate provost for diversity and inclusion at Thomas Jefferson University, and associate dean for diversity and community engagement at Sidney Kimmel Medical College of Thomas Jefferson University, all in Philadelphia.
- Greenwald AG, McGhee DE, Schwartz JL. Measuring individual differences in implicit cognition: the implicit association test. J Pers Soc Psychol. 1998;74(6):1464-1480.
- About the IAT. Project Implicit website. Accessed March 13, 2017.
- Green AR, Carney DR, Palin DJ, et al. Implicit bias among physicians and its prediction of thrombolysis decisions for black and white patients. J Gen Intern Med. 2007;22(9):1231-1238.
- Cooper LA, Roter DL, Carson KA, et al. The associations of clinicians’ implicit bias attitudes about race with medical visit communication and patient ratings of interpersonal care. Am J Public Health. 2012;102(5):979-987.
- Schwartz MB, Chambliss HO, Brownell KD, et al. Weight bias among health professionals specializing in obesity. Obes Res. 2003;11(9):1033-1039.
- Uncapher H, Arean PA. Physicians are less willing to treat suicidal ideation in older patients. J Am Geriatr Soc. 2000;48(2)188-192.
- Popa-Roch M, Delmas F. Prejudice Implicit Association Test effects – the role of self-related heuristics. J Psychol. 2010;218(1):44-50.