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J Gen Intern Med ; 38(9): 2045-2051, 2023 07.
Artigo em Inglês | MEDLINE | ID: mdl-36811702

RESUMO

BACKGROUND: Clinical algorithms that incorporate race as a modifying factor to guide clinical decision-making have recently been criticized for propagating racial bias in medicine. Equations used to calculate lung or kidney function are examples of clinical algorithms that have different diagnostic parameters depending on an individual's race. While these clinical measures have multiple implications for clinical care, patients' awareness of and their perspectives on the application of such algorithms are unknown. OBJECTIVE: To examine patients' perspectives on race and the use of race-based algorithms in clinical decision-making. DESIGN: Qualitative study using semi-structured interviews. PARTICIPANTS: Twenty-three adult patients recruited at a safety-net hospital in Boston, MA. APPROACH: Interviews were analyzed using thematic content analysis and modified grounded theory. KEY RESULTS: Among the 23 study participants, 11 were women and 15 self-identified as Black or African American. Three categories of themes emerged: The first theme described definitions and the individual meanings participants ascribed to the term race. The second theme described perspectives on the role and consideration of race in clinical decision-making. Most study participants were unaware that race has been used as a modifying factor in clinical equations and rejected the incorporation of race in these equations. The third theme related to exposure to and experience of racism in healthcare settings. Experiences described by non-White participants ranged from microaggressions to overt acts of racism, including perceived racist encounters with healthcare providers. In addition, patients alluded to a deep mistrust in the healthcare system as a major barrier to equitable care. CONCLUSIONS: Our findings suggest that most patients are unaware of how race has been used to make risk assessments and guide clinical care. Further research on patients' perspectives is needed to inform the development of anti-racist policies and regulatory agendas as we move forward to combat systemic racism in medicine.


Assuntos
Algoritmos , Tomada de Decisão Clínica , Disparidades em Assistência à Saúde , Racismo , Medição de Risco , Adulto , Feminino , Humanos , Masculino , Negro ou Afro-Americano , Pesquisa Qualitativa , Fatores Raciais , Confiança , Conscientização
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