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: UNIVERSITY OF TEXAS ARLINGTON
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-26 至 2028-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10658690
• 关键词: Address; Area; Calibration; Childbirth; Clinical; Communities; Complex; Coupled; Data; Data Set; Decision Making; Development; Discipline; Disparity; Distal; Economics; Effectiveness; Effectiveness of Interventions; Elements; Equity; Feedback; Fostering; Health; Health Disparities Research; Health Status; Healthcare; Individual; Intervention; Knowledge; Learning; Life Cycle Stages; Literature; Maternal Health; Maternal Mortality; Methodology; Methods; Modeling; Municipalities; Not Hispanic or Latino; Outcome; Participant; Pathway interactions; Prevention; Prevention strategy; Process; Public Health; Race; Research; Research Methodology; Research Personnel; Risk Factors; Science; Shapes; Social Policies; Societies; Structural Racism; System; Testing; Texas; Time; Translating; United States; Validation; Woman; black women; dashboard; disparities in morbidity; disparity reduction; dynamic system; economic determinant; effectiveness evaluation; evidence base; health determinants; health disparity; insight; maternal risk; metropolitan; model building; models and simulation; novel; population health; racial discrimination; severe maternal morbidity; simulation; social; social determinants; tool; web site

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.

项目总结 非西班牙裔黑人女性(NHBW)患SMM的可能性是NH白人女性的两倍，在- 增加产妇死亡的风险。尽管SMM的临床原因是多因素的，但这种差异是由驱动因素造成的 结构性种族主义。尽管有广泛的知识和现有的预防战略，但长期的SMM疾病仍在继续。 平价表明，仅靠目前的努力不足以实现公平。因此，替代方法有 需要改变对SMM差异原因的理解，并在预防和预防方面取得突破 提顿。我们认为，SMM差异最好被概念化为动态复杂的系统，包括 随着时间的推移不断演变的紧密耦合的元素。因此，为了解决NHBW之间的SMM差距， 我们将应用复杂系统方法，即系统动力学(SD)建模和系统动力学 小组模型构建(SD GMB)-回答复杂信息的研究问题并实现更高的效率- 重要的预防策略。 该项目的总体目标是应用复杂的系统方法，在以下方面产生一个整体的- NHBW中SMM结果背后的动态复杂系统的立场，然后 将这种理解转化为一种新的、基于证据的模拟模型，用于评估 干预措施的有效性，可以遏制全国妇幼保健工作者的SMM成果。我们的具体目标是 1)使用SD GMB创建动态复杂系统的定性SD模型 NHBW的SMM结果；2)将定性SD模型转换为定量SD模拟 模式；3)确定、评估和加强现有和可信的干预措施的有效性，这些干预措施可以 减少NHBW之间不同的SMM结果；以及4)将量化SD模型作为模拟- 为利益相关者和研究人员提供基于TION的仪表板，旨在减少NHBW的SMM成果。 该项目的成功完成预计将改变人们对开发和 通过：a)使用系统科学方法，找出有效的解决办法，以重新确定工作和管理方面的差距； 消除健康方面的种族差距；b)向不同的利益攸关方传播见解，以指导更广泛的社区- 在存在动态复杂性的情况下进行医疗保健和社会政策决策；以及c)提供 孕产妇健康差异的初始SD模型，可以刺激跨其他背景的复制。这个项目 还将通过以下方式更广泛地影响健康差距研究：a)展示召集 关于产妇健康、复杂系统科学和参与式研究方法的观点 健康差距研究；b)提供复杂系统方法效用的变革性证据 在孕产妇健康差异研究和预防方面；以及c)生成首个SMM不同的SD模型- 可根据其他情况扩大或调整的关系(例如，作为国家模式)，预期的和可持续的-- 对更广泛的公共和人口健康领域及相关学科可能产生的影响。