Defining the Need for Causal Inference to Understand the Impact of Social Determinants of Health: A Primer on Behalf of the Consortium for the Holistic Assessment of Risk in Transplantation (CHART).
Defining the Need for Causal Inference to Understand the Impact of Social Determinants of Health: A Primer on Behalf of the Consortium for the Holistic Assessment of Risk in Transplantation (CHART).
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DOI：
10.1097/as9.0000000000000337
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发表时间：
2023-12
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这项研究旨在介绍一些关键的概念和方法，这些概念和方法为研究设计提供了依据，这些研究试图量化健康的社会决定因素(SDOH)对获得器官移植的机会和结果的因果影响。SDOH和移植结果之间的因果关系还知之甚少。这在一定程度上是由于对患者之间的复杂互动、他们的邻里环境、三级护理系统以及影响机会和结果的结构性因素的非标准化和不完整的捕捉。要设计研究来量化这些因素对移植机会和结果的因果影响，需要理解因果推断的基本概念。我们概述了因果推理中的基本概念，包括潜在结果框架和有向无环图。我们讨论了如何在因果框架中概念化SDOH，并提供了应用实例来说明如何引入偏差。需要直接测量SDOH，增加对潜在变量和中介变量的测量，并建立多层次的研究框架，审查多个卫生系统的健康不平等现象，以推广结果。我们说明，社会经济地位、种族/民族以及患者和临床医生之间的语言不一致可能会产生偏见。要实现公平的移植系统，需要在心理社会风险因素、途径和结果之间建立因果关系。这是以准确和精确地量化社会风险为前提的，最好的办法是改进卫生系统数据的组织，并作出多中心努力，以与专科和服务线相关的方式收集和学习这些数据。这篇文章旨在介绍一些关键概念，这些概念有助于设计量化健康的社会决定因素(SDOH)对获得器官移植的途径和结果的因果影响的研究。为了在器官移植的SDOH和临床结果的交汇点上快速推进研究，研究人员必须在研究设计时考虑由于社会经济地位、种族/民族以及患者和临床医生之间的语言不一致而产生的偏见。移植是一个范例模型，但所回顾的方法可广泛应用于其他外科和非外科领域。
This study aims to introduce key concepts and methods that inform the design of studies that seek to quantify the causal effect of social determinants of health (SDOH) on access to and outcomes following organ transplant. The causal pathways between SDOH and transplant outcomes are poorly understood. This is partially due to the unstandardized and incomplete capture of the complex interactions between patients, their neighborhood environments, the tertiary care system, and structural factors that impact access and outcomes. Designing studies to quantify the causal impact of these factors on transplant access and outcomes requires an understanding of the fundamental concepts of causal inference. We present an overview of fundamental concepts in causal inference, including the potential outcomes framework and direct acyclic graphs. We discuss how to conceptualize SDOH in a causal framework and provide applied examples to illustrate how bias is introduced. There is a need for direct measures of SDOH, increased measurement of latent and mediating variables, and multi-level frameworks for research that examine health inequities across multiple health systems to generalize results. We illustrate that biases can arise due to socioeconomic status, race/ethnicity, and incongruencies in language between the patient and clinician. Progress towards an equitable transplant system requires establishing causal pathways between psychosocial risk factors, access, and outcomes. This is predicated on accurate and precise quantification of social risk, best facilitated by improved organization of health system data and multicenter efforts to collect and learn from it in ways relevant to specialties and service lines. Mini abstract This article aims to introduce key concepts that inform the design of studies to quantify the causal effect of social determinants of health (SDOH) in access to and outcomes after organ transplant. To rapidly advance research at the intersection of SDOH and clinical outcomes in organ transplant, investigators must consider biases arising from socioeconomic status, race/ethnicity, and incongruencies in language between the patient and clinician at the time of study design. Transplant is an exemplar model, but the approaches reviewed can broadly be applied to other surgical and nonsurgical fields.