Deconstructing Unconscious Bias in the Health Care Workforce: An Iterative Mixed Methods Approach

Abstract

The prevalence of unconscious bias within the healthcare workforce is not well understood. Likewise, not much is known about the potential impacts of unconscious bias training interventions on the healthcare workforce as they have not been included in studies evaluating effectiveness. This constrains any ability to evaluate the potential for unconscious bias training as a means to reduce patient healthcare disparities. This dissertation uses an iterative mixed methods approach to examine the prevalence of unconscious bias, factors associated with individual mitigation activities, and the impact on the healthcare workforce. Results demonstrate that the unconscious biases of healthcare workers differ significantly from those of the general population and are highly variable across geographic regions and provider types. Likewise, there is some evidence to indicate that factors beyond that of the individual (i.e. type of practice and community) may potentially influence physicians’ decisions to participate in unconscious bias mitigation activities. Lastly, physicians have many reasons for wanting to address unconscious bias, such as for their own personal and/or professional development. However, there is a consensus that greater accountability on the part of organizations is needed to address the upstream systemic issues that contribute to the formation and or maintenance of unconscious bias.