From racial disparities in specific areas of patient care and the repercussions of the COVID-19 pandemic, to the unfair interactions among providers as well as among medical students themselves, 61 articles published over a three-year period between 2018 and 2020 documented the tangible consequences of these biases. While acknowledging the existence of the issues posed by implicit bias is a start, effectively addressing it in the field of healthcare requires actionable and diverse strategies. Emerging research findings from our review underscored the need for intervention methods that combine the best of what we know at the individual level about how to mitigate the impact of implicit racial bias with evidence-based institutional interventions tailored to the diverse population of healthcare providers and trainees. Moreover, it continues to be necessary to develop a deeper understanding of how implicit bias operates at the individual and institutional levels. The healthcare domain’s collective commitment to dismantling these biases is vital, as it enhances the chance of every patient receiving unbiased and compassionate care, while also affording equitable opportunities to those providing services in the healthcare system. If 2020 taught us anything, it is that no country or community can be completely isolated from the healthcare challenges faced by others.
Even though decades of implicit racial bias research have continued to confirm the negative impact of bias in 2018-2020 there remain areas where research conclusions are unsettled, providing new directions for research. Sukhera et al.’s (2018a) review of healthcare education studies that use the IAT found that the IAT is often used in two ways: as a metric to evaluate the success of an educational activity or as a tool to promote awareness while triggering discussion and reflection. The IAT can be used in distinct and complementary ways; curriculum designers and educators must consider the premise for using the test, anticipate potential reactions from learners, and have a plan in place to address such reactions prior to delivering instruction. For example, when the goal of implicit bias intervention is to improve provider communication behaviors, Hagiwara et al., (2019) raised concerns about the limitations of the existing patient provider communication coding systems, such as the Roter Interaction Analysis System (RIAS) and the Four Habits Coding Scheme. They noted that these systems fail to consistently include an assessment of nonverbal or paraverbal behaviors, which are often associated with the manifestation of implicit bias. To address these shortcomings, the authors recommended that more research should be aimed towards identifying specific provider communication behaviors that may reflect provider implicit racial bias, with a special focus of integrating minority patient perspectives. By gathering narratives from minority patients, researchers can identify nonverbal and paraverbal cues that are consistent with implicit racial bias and then develop coding systems to recognize discrete and quantifiable communications for providers to address.
Notably, Maina et al.’s 2018 review indicated that the research on the impact of providers’ implicit bias on patient care and outcomes had mixed results. When it comes to mitigation efforts, their review found only two intervention studies that investigated methods to reduce implicit bias among healthcare providers, with only one study demonstrating a post-intervention reduction in implicit bias. The authors also highlighted several limitations among the reviewed studies, including the use of convenience samples, low response rates, overreliance on vignettes instead of real-world measures, limited ability to infer causality due to cross-sectional study designs, and an excessive focus on physicians’ implicit racial bias rather than that of other types of healthcare providers. While the latter limitation has been addressed by multiple studies in our dataset, the opportunities for both empirical (additional evidence-based findings) and methodological innovations (development of more precise and successful tools to study implicit racial bias) in this line of scholarship remain. We hope these areas for future research will be addressed across many healthcare specialties, reducing disparities and producing better medical outcomes in the years to come.