In a recent webinar, titled “Increasing Diversity in Clinical Trials,” panelists were asked what role structural racism plays in the healthcare system in the lack of clinical trial diversity. They also were asked if employing a more diverse clinical staff is more likely to increase enrollment of a more diverse patient population.

When discussing these topics, the panel is not accusing individuals of being racist, noted Clyde W. Yancy, MD, MSc, vice dean of diversity and inclusion for medicine, professor of medical social sciences, and chief of the division of cardiology at Northwestern University Feinberg School of Medicine. “We are saying that the construct of systems is such that it advantages one group and disadvantages another group.”

For example, when a clinical trial is set up, who is trained to be a trial coordinator? Who is trained to obtain informed consent forms? Who reviews the protocol? Trial participants might be more comfortable with clinical staff who resemble them.

“All of these things reflect a structure, a process,” Yancy said. “The way an IRB functions, the way protocols are disseminated, the way studies are funded, the way investigators are rewarded, particularly with academic credit, all of this is within a fairly strict system. That system, by design, whether it was overt or not, excludes certain important constituencies. When we talk about structural racism, we’re saying that there’s something inherent in the design of our systems whereby the execution of that process unfortunately leaves some people out of the equation. We shouldn’t fear the phrase ‘structural racism.’ We should recognize it as an invitation to re-evaluate our processes and [ask], ‘Have we developed processes that are more inclusive?’”

Structural racism is a powerful construct that may influence participation in clinical research studies, said panelist Jonathan Jackson, PhD, assistant professor of neurology at Harvard Medical School and director of the CARE Research Center at Massachusetts General Hospital. “It may impact behavior and it may impact trust. It also may impact other aspects of clinical trial design that are much more familiar to trialists and scientists.” For example, not only could a measurement be miscalibrated for certain populations, but a measurement tool, such as one for pain management, may be inappropriate in certain contexts.

Jackson referenced Paris B. Adkins-Jackson, PhD, MPH, a research fellow at the CARE Research Center who has written about this topic. In a recent paper, Adkins-Jackson and colleagues discussed how to measure racism in academic health centers (AHCs).1 First, it is important to “identify and assess” racism operating at three levels: the individual level, the intraorganizational level, and the extraorganizational level, they wrote.

On the individual level, literature has shown implicit bias can be expressed during clinical encounters. This bias can be expressed through “limited time given by clinicians to patients of color, inequity in how that time is spent, inequity in conversational pace and tone, dismissive clinician body language, inequity in information-sharing, inequity in resource use, and inequity in decision-sharing.” The authors proposed measuring these variables, along with patient assessment of level of trust and communication, and comparing them across racial groups.

On the intraorganizational level, structural racism can be experienced through a lack of consequences for clinician bias, the lack of efficient reporting mechanisms, and the lack of culturally responsive training for health professionals. The authors recommend using the Implicit Association Test to capture intraorganization institutional racism.

On the extraorganizational level, AHCs work with federal and government institutions to determine the policies and allocation of resources that can disproportionally affect people of color. The authors suggested using an index of factors that look at these resources to reveal how they may have contributed to structural racism.

Scores from the measurements of these three levels can be combined to yield a composite score to inform “antiracist strategic planning and decision-making” over time, they wrote. “We suggest incorporating qualitative components at each level (e.g., randomized patient interviews at the individual level; observations and evaluations of AHC operations from preclinical health students and community health workers at the intraorganizational level; and local, state, and federal policy analysis at the extraorganizational level). In combination, this mixed-data formative assessment could ensure that a range of voices is solicited, recorded, and drawn upon to eliminate health inequity.”1

Systemic racism reinforces already existing social inequities, Jackson said. “I think the most egregious problem of all is that it’s going to flatten all of these things into the name of some sort of essentialized biological disparity.” Problems will not be attributed to an incorrect measurement or tool, or even to a process that has been incorrectly implemented. “We’re going to say that the problem is you. Because you’ve got more melanin in your skin, you don’t feel pain. Because you have more melanin in your skin, you have a different relationship between this biomarker and this disease. It is simply not the case. The impact and the role of systemic discrimination, systemic racism more specifically, can’t be overstated. It touches every aspect of our research workflow.”

REFERENCE

  1. Adkins-Jackson PB, Legha, RK, Jones KA. How to measure racism in academic health centers. AMA J Ethics 2021;23:E140-E145.