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).

Abstract

Objective

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.

Background

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.

Methods

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.

Results

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.

Conclusions

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.

Department

Description

Provenance

Citation

Published Version (Please cite this version)

10.1097/as9.0000000000000337

Publication Info

Bhavsar, Nrupen A, Rachel E Patzer, David J Taber, Katie Ross-Driscoll, Rhiannon Deierhoi Reed, Juan C Caicedo-Ramirez, Elisa J Gordon, Roland A Matsouaka, et al. (2023). 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). Annals of surgery open : perspectives of surgical history, education, and clinical approaches, 4(3). p. e337. 10.1097/as9.0000000000000337 Retrieved from https://hdl.handle.net/10161/29664.

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Scholars@Duke

Matsouaka

Roland Albert Matsouaka

Associate Professor of Biostatistics & Bioinformatics
Kirk

Allan Douglas Kirk

David C. Sabiston, Jr. Distinguished Professor of Surgery

I am a surgeon with interest in immune management of transplant recipients. I am particularly interested in therapies that influence T cell costimulation pathways and adjuvant therapies that facilitate costimulation blockade to prevent the rejection of transplanted organs without undue suppression of protective immunity. I am also interested in understanding how injury, such as that occurring during trauma or in elective surgery, influences immune responses and subsequent healing following injury.

McElroy

Lisa M McElroy

Assistant Professor of Surgery

I am an abdominal transplant surgeon with a health services research lab focused on understanding how complex health care processes and large multidisciplinary teams affect outcomes of high cost, high acuity patients.  I have a master's degree in health services and outcomes research methodology with supplemental training in health disparities research methods, engineering methods for healthcare system and process assessment, organizational behavior theory and change management, and implementation science.

As my research has progressed, an emerging theme has been the interplay between biologic and social risk, which each contribute to a patient’s ultimate success but receive disproportionate consideration in anticipation of and in response to subpar outcomes. I am currently involved in several efforts that build on this concept and employ an approach to health equity research that accounts for center and organizational-level characteristics when examining differences in care based on social determinants of health. 


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