Chapter 13: Race, Bias & Health Care – Inequality, Racism & Medical Justice

Race, Bias & Health Care – Inequality, Racism & Medical Justice critically examines the pervasive role of race, racial bias, and systemic inequities within modern health care, demonstrating that minority groups frequently experience worse health outcomes than white populations. The text establishes that the traditional notion of race as a system of distinct biological groups is scientifically unfounded; rather, race is a powerful social construction. Nevertheless, the concept must be retained to address the real-world impact of racism, which is defined by the components of inferiorization and antipathy. Racism is morally condemned for violating ethical standards, including the principles of respect for persons and justice. The chapter details massive societal inequalities in wealth, education, and housing that are rooted in historical and contemporary institutional or structural racism—such as historical policies like redlining—which persist even when individual actors harbor no explicit prejudice. These structural failings translate directly into alarming health disparities, notably significantly higher infant mortality rates and lower life expectancies for Black Americans. Research indicates that discrimination and chronic exposure to everyday racism (microaggressions) contribute substantial stress, leading to adverse physiological effects and poorer health. Within the clinical setting, evidence confirms that race influences medical decision-making due to implicit bias—unconscious negative attitudes held by health care providers that result in minority patients receiving fewer procedures and poorer quality care, regardless of the provider's explicit intentions. Finally, the chapter analyzes the controversies surrounding race-based medicine and racial profiling in medicine, where race is used as a proxy in diagnosis or treatment (such as drug prescription). Experts caution that using race as a proxy is flawed, as it ignores vast intra-racial variability, often misattributes differences to genetics instead of socioeconomic status (SES), and risks embedding inequality into standard practices, including clinical algorithms.