ABSTRACT
Chapter 4 addresses the question of “under what conditions would precision medicine most likely become racialized in the clinic?” We report that physicians understand that genomic data categorized by race and ethnicity is inherently faulty. Yet data is delivered to these healthcare providers in a racialized format, and they are then tasked to utilize this data to make treatment decisions for their patients. For example, data categorized along ethnic and racial lines provides shorthand devices to help patients understand their disease probability. We propose the “relative resources” theoretical model to argue that precision medicine is most likely to become racialized (as opposed to personalized) for individuals and populations that do not have access to adequate resources at the individual and/or systemic level. “Resources” refers not only to financial resources, but also human and computational resources, and legal and infrastructural resources. Lack of relevant resources to receive personalized medical treatment may contribute to further health inequality among already vulnerable populations, which are likely to be ethnic and racial minority groups.
