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Complex Systems Approaches to Advance Maternal Health Disparities Research and Prevention: Developing a System Dynamics Simulation Model of Severe Maternal Morbidity among Black Women

Complex Systems Approaches to Advance Maternal Health Disparities Research and Prevention: Developing a System Dynamics Simulation Model of Severe Maternal Morbidity among Black Women
促进孕产妇健康差异研究和预防的复杂系统方法:开发黑人妇女严重孕产妇发病率的系统动力学模拟模型
批准号:
10658690
负责人:
Kyrah K Brown
金额:
$36.51万
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-09-26 至 2028-05-31

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PROJECT SUMMARY Non-Hispanic Black women (NHBW) are twice as likely as NH White women to suffer SMM, which in- creases risk for maternal mortality. Although the clinical cause of SMM is multifactorial, the disparity is driven by structural racism. Despite the breadth of knowledge and existing preventive strategies, prolonged SMM dis- parities suggest that current efforts alone are insufficient to achieve equity. Thus, alternate approaches are needed to transform understanding of the causes of SMM disparities and to generate breakthroughs in preven- tion. We argue that SMM disparities are best conceptualized as dynamically complex systems, consisting of tightly coupled elements that continually evolve over time. Thus, to address SMM disparities among NHBW, we will apply complex systems approaches – namely, system dynamics (SD) modeling and system dynamics group model building (SD GMB) – to answer complexity-informed research questions and enable more effica- cious prevention strategies. The overall aim of this project is to apply complex systems approaches to generate a holistic under- standing of the dynamically complex systems underlying SMM outcomes among NHBW, and then translate this understanding into a novel, evidence-based simulation model to be used for evaluating the effectiveness of interventions that can curb SMM outcomes among NHBW. Our specific aims are as follows: 1) to use SD GMB to create a qualitative SD model of the dynamically complex systems that generate SMM outcomes among NHBW; 2) to translate the qualitative SD model into a quantitative SD simulation model; 3) to identify, evaluate, and enhance the effectiveness of existing and plausible interventions that can reduce disparate SMM outcomes among NHBW; and 4) to disseminate the quantitative SD model as a simula- tion-based dashboard for stakeholders and researchers aiming to reduce SMM outcomes among NHBW. The successful completion of this project is expected to transform understanding of the development and perpetuation of SMM disparities by: a) using systems science methods to identify effective solutions to re- duce racial gaps in health; b) disseminating insights to diverse stakeholders to guide broader community- level healthcare and social policy decision-making in the presence of dynamic complexity; and c) providing an initial SD model of maternal health disparities that can spur replication across other contexts. This project will also impact health disparities research more broadly by: a) demonstrating the potential of convening di- verse perspectives in maternal health, complex systems science, and participatory research methods in health disparities research; b) providing transformative evidence of the utility of complex systems approaches in maternal health disparities research and prevention; and c) generating the first SD model of SMM dispari- ties that can be expanded or adapted to other contexts (e.g. as a national model), with anticipated and plau- sible impacts for the broader public and population health fields and related disciplines.
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