Section of Nephrology, Boston University Chobanian & Avedisian School of Medicine and Boston Medical Center, Evans Biomedical Research Center, 5th Floor, 650 Albany Street, Boston, MA, 02118, USA.
Department of Anthropology, Boston University College of Arts and Sciences, Boston, MA, USA.
J Gen Intern Med. 2023 Jul;38(9):2045-2051. doi: 10.1007/s11606-023-08035-4. Epub 2023 Feb 22.
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.
To examine patients' perspectives on race and the use of race-based algorithms in clinical decision-making.
Qualitative study using semi-structured interviews.
Twenty-three adult patients recruited at a safety-net hospital in Boston, MA.
Interviews were analyzed using thematic content analysis and modified grounded theory.
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.
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.
最近，将种族作为一个修正因素纳入临床决策的临床算法因在医学中传播种族偏见而受到批评。用于计算肺或肾功能的方程就是根据个体种族而具有不同诊断参数的临床算法的例子。虽然这些临床措施对临床护理有多种影响，但患者对这些算法的应用的认识和看法尚不清楚。
探讨患者对种族和种族为基础的算法在临床决策中的应用的看法。
使用半结构化访谈的定性研究。
在马萨诸塞州波士顿的一家保障医疗服务的医院招募了 23 名成年患者。
使用主题内容分析和改良的扎根理论对访谈进行分析。
在 23 名研究参与者中，有 11 名女性，15 名自认为是黑人或非裔美国人。出现了三个主题类别：第一个主题描述了参与者对种族一词的定义和个人含义。第二个主题描述了对种族在临床决策中的作用和考虑的观点。大多数研究参与者都不知道种族已被用作临床方程中的一个修正因素，并反对在这些方程中纳入种族。第三个主题与在医疗保健环境中经历的种族主义有关。非白人参与者描述的经历从微侵犯到公然的种族主义行为不等，包括与医疗保健提供者的种族主义遭遇。此外，患者还提到了对医疗保健系统的深深不信任，这是实现公平护理的主要障碍。
我们的研究结果表明，大多数患者不知道种族是如何被用来进行风险评估和指导临床护理的。需要进一步研究患者的观点，为制定反种族主义政策和监管议程提供信息，因为我们将继续努力打击医学中的系统性种族主义。
