Evidence Based Implicit Bias Implications for Physicians and Healthcare Professionals
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HEALTHCARE RESEARCH What does this have to do with health- care? In addition to a provider’s conscious adherence to high ethical standards and a commitment to quality care, they are also subject to implicit bias, like the rest of the population. Fitzgerald and Hurst examined 42 peer-reviewed articles (Fitz- Gerald & Hurst, 2017). The evidence in - dicated that healthcare professionals exhibit the same level of implicit bias as the wider population. A couple decades earlier, Shulman and his colleagues pub- lished research that many view as a ma- jor stimulus for further research regarding implicit bias and healthcare (Schulman et al., 1999). They presented 720 physi- cians with videos of patients (actors) who were similar in physical appearance and medical history, differing only by race and sex. All were candidates for cardiac cath- eterization. After the physicians saw the videos of the patients and reviewed their history, the researchers found that wom- en and African Americans were less likely to be referred for cardiac catheterization than men and Whites. It appeared that, in spite of the conscious commitment to equitable care, unconscious bias was an influence in referral decision making. The national interest in implicit bias in healthcare intensified when the Institute of Medicine delivered its report, Unequal Treatment , in 2003 (Smedly et al., 2003). It concluded that implicit bias against so- cial groups, including racial and ethnic groups, can impact the clinical encoun- ter. Much of the research supporting this report utilized the online Implicit Asso- ciation Test (IAT). The IAT measures the strength of associations between con-
cepts such as African American or White, old or young, good or bad, desirable or undesirable, and dangerous or friendly. The reaction time (association) to various pairs of words or photographs is a mea- sure of the strength of the association. Millions of people used this website (op - erated by Harvard University) to take the IAT or one of the other tests. The racial disparity in the judgment of pain has been studied as an example of implicit bias in healthcare. In research by Mende-Siedlecki and colleagues, White providers demonstrated more stringent thresholds in perceiving pain on Afri- can American faces versus White faces, and those with more stringent thresh- olds for African American patients pre- scribed fewer non-narcotic pain relievers (Mende-Siedlecki et al., 2019). This was not true for Asian faces, suggesting that other-face dynamics were not at play. This research did not investigate wheth- er gaps in empathy or perspective taking skills might be a partial explanation for the disparity. Implicit bias has also been shown to impact the quality of the clinical encoun- ter, particularly communication. In an early study, primary care physicians took the IAT and had their clinical encounters recorded (Cooper et al., 2012). Provider race bias on the IAT was associated with lower quality communication with African American patients, such as more provider verbal dominance, lower patient positive affect, poorer patient ratings of interper- sonal care, lower perceptions of respect from clinicians, and lower likelihood of recommending the clinician.
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