Racial disparities in coronary heart disease: a sociological view of the medical literature on physician bias.

Abstract

PURPOSE: To interpret, within a sociological context, evidence of physician bias in the management and outcomes of coronary heart disease (CHD) treatment for African Americans vs Whites. DATA IDENTIFICATION: Articles addressing race and ethnic disparities in CHD, and gender as an additional risk factor, published since 1980, were searched and reviewed. Source material was identified using the electronic search engines for MEDLINE and Sociological STUDY SELECTION: Articles were included in the review of race or ethnic disparities in heart disease when they provided direct or indirect evidence of potential sources of physician bias and/or differential treatment for CHD. Three types of studies suggest the presence of physician bias, and include those demonstrating: 1) patterned disparities in treatments and interventions; 2) practitioner perceptual bias/stereotyping of patients; and 3) patient perceptions of bias in treatment. RESULTS: A growing body of research supports the presence of physician bias in differential treatment practices for CHD based on patient race/ethnicity, and sometimes patient gender and socioeconomic status, which manifests as additional risk factors in the quality of care, pharmacological therapy, and use of invasive procedures. Access to care and patient preferences/behaviors do not fully account for racial disparities in CHD treatment. CONCLUSION: Socioeconomics, individual racism, and institutional racism represent 3 predominant pathways to differential treatment for CHD that are mediated by the patient-provider relationship. Racial biases are shown to be a part of the social structure of medical practices at both the macro and micro levels. Individual healthcare providers can potentially reduce disparities in Black-White CHD treatment and outcomes by examining the patient-provider relationship for bias. Future studies will require addressing more direct ways of measuring, monitoring, and reducing subtle bias in the healthcare system.

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