Appointments with a medical provider typically entail more than just interaction with the doctor. There are check-ins with reception, a pre-screening with a nurse, and then a follow-up with the office’s front desk after speaking with the doctor. While researchers have studied how physicians’ racial biases affect the experience of minority patients, little attention has been paid to how healthcare staff’s biases might affect patients. In an effort to explore that open question, Gabriel S. Tajeu, assistant professor of health services administration and policy, conducted research that found healthcare staff showed greater pro-white bias than doctors and registered nurses.
The findings, published in October in the Journal of the National Medical Association, are based on research conducted in Alabama while Tajeu was a doctoral candidate at the University of Alabama-Birmingham.
In the study, participants—doctors, registered nurses, and staff—were asked to take the Implicit Association Test and Modern Racism Scale, tests administered by computer that measure implicit and explicit bias, respectively.
In the implicit bias test, white participants (both MD/RN and staff) exhibited a bias score significantly higher than participants who identified as black or other. In addition, among white study participants, white staff (non-MD/RN) had higher levels of pro-white implicit bias compared to white MD/RN staff. The study found little difference between MD/RN and staff results for the explicit bias test. Due to the small sample size of participants (107, in total), the study was unable to determine a statistically significant difference between MD/RN and staff groups when broken down into more granular, sociodemographic categories.
In recent years, especially since the 2001 publication of a landmark report entitled “Crossing the Quality Chasm,” researchers have increasingly considered how sociocultural factors might affect medical treatment. One 2007 study found that, when physicians were presented with a clinical vignette describing symptoms of heart attack, the greater a physician’s pro-white implicit bias, the less likely they were to recommend administering black patients with an effective, commonly used treatment.
By focusing on other individuals present in medical settings, like receptionists and staff, Tajeu’s work adds to a growing field of research that looks at negative racial attitudes among healthcare professionals. According to Tajeu, his is one of the first studies to look beyond medical providers and examine biases among staff. “The encounter with the front desk staff who is scheduling you may influence various aspects of the rest of the healthcare experience, but that hasn’t been examined yet,” says Tajeu. “The next step would be to examine the potential effects of experiencing racism in the first interaction with a staff member.”
Tajeu says that examining racial bias among medical providers and how bias correlates with treatment outcomes is important because minorities are underrepresented among healthcare providers. While about a quarter of the nation’s population is non-white, only about 6 percent of nurses and 9 percent of doctors are minorities, according to the 2014 Sullivan Commission report. This is a serious problem when attempting to provide culturally competent care, according to Tajeu. He says that, while cultural competency training among nurses and doctors has become an important factor in limiting negative sociocultural factors among a population that does not wholly reflect the population it serves, it is only a start. “In this study we are saying that staff are a population that should not be overlooked when it comes to these trainings,” says Tajeu.
Tajeu and his co-investigators are now in the process of determining the effect of an intervention they implemented among healthcare staff in Alabama to ameliorate the effects of pro-white implicit bias. Tajeu hopes that the intervention may suggest pathways for working with healthcare staff and limiting the effect of racial bias in the long term.
— Tara W. Merrigan