Modeling Rural Perinatal Health Outcomes and Service Systems to Improve Health Equity

农村县获得围产期保健服务的机会一直在下降，孕产妇和婴儿保健 在蒙大拿州等农村地区，(围产期)结局也较差。妇女获得更多机会 全面的围产期服务改善了结局。这个项目的主要目标是弥补 缺乏关于如何在资源有限的农村地区改善获得围产期服务的知识 以改善健康公平的方式改善环境。这个项目将阐明 蒙大拿州的围产期健康结果和围产期护理机会。通过绘制完整的 全面围产期服务系统(即产科护理、精神健康服务和药物滥用 服务)，这项研究将产生关于哪里存在不平等的新信息，并模拟如何在系统范围内 可以进行改进。将采用社区参与的方法，涉及大量参与 与社区合作伙伴一起确定问题、开发模型、设计研究方法，以及 最后公布调查结果。研究小组将成立一个行业咨询委员会，成员包括 州政府机构、临床医生和农村生育妇女的代表。团队将会 从全国可用的强大辅助数据源集成蒙大拿州的数据，包括 关于社会人口、健康结果和服务设施的信息。为了实现其目标， 该项目将使用空间人口统计技术和设施规划优化模型。目标1将创建 蒙大拿州围产期健康结局预测模型。这一目标的两个主要目标是1) 估计目前对全面围产期护理的需求，以及2)预测未来对 全面的围产期护理。围产期服务需求人口图(育龄妇女 及其社会人口学特征)和结局(低出生体重、早产和婴儿 死亡率)将被开发出来。目标2将开发规范性规划模型，为决策提供信息 提高蒙大拿州围产期保健系统的有效性。这一目标的两个主要目标是1) 开发数据驱动的方法来评估附近供需之间的匹配程度 为农村母亲提供全面的围产期服务，以及2)开发指令性的地点规划模式 其目标是最大限度地提高母亲和婴儿的公平和获得机会。AIM 3将设计一种交互式网络- 基于地图应用程序，通过一种新颖的数据可视化转换来自目标1和目标2的结果 蒙大拿州的围产期健康差距。此地图应用程序可供政策制定者和 研究人员作为工具，为重新设计围产期保健提供循证框架 医疗服务不足的农村地区的医疗系统。

Access to perinatal health services in rural counties has been declining, and maternal and infant health (perinatal) outcomes are also poorer in rural areas like Montana. Women with increased access to comprehensive perinatal services have improved outcomes. The main objective of this project is to remedy the lack of knowledge about how access to perinatal services could be improved in a rural, resource-constrained environment in ways that would improve health equity. This project will elucidate the spatial variation in perinatal health outcomes and perinatal care access across the state of Montana. By mapping out the full system of comprehensive perinatal services (i.e., obstetric care, mental health services, and substance abuse services), this research will generate new information about where inequities exist and model how system-wide improvements can be made. A community-engaged approach will be applied involving substantial engagement with community partners in order to identify problems, develop models, design the research approach, and finally disseminate the findings. The research team will form an Industry Advisory Board comprised of representatives of state government agencies, clinicians, and rural women who have given birth. The team will integrate data for Montana from robust secondary data sources that are nationally available, including information on sociodemographics, health outcomes, and service facilities. To achieve its objectives, the project will use spatial demographic techniques and facility planning optimization models. Aim 1 will create predictive models of perinatal health outcomes across Montana. The two main objectives of this aim are 1) to estimate the current demand for comprehensive perinatal care, and 2) to predict the future demand for comprehensive perinatal care. Population maps of demand for perinatal services (women of childbearing age and their sociodemographic characteristics) and outcomes (low birth weight, preterm deliveries, and infant mortality) will be developed. Aim 2 will develop prescriptive planning models to inform decisions about improving the effectiveness of the Montana perinatal care system. The two main objectives of this aim are 1) to develop a data-driven approach for assessing the degree of alignment between supply and demand of nearby comprehensive perinatal services for rural mothers, and 2) to develop prescriptive location planning models with the goal of maximizing equity and access for mothers and infants. Aim 3 will design an interactive Web- based mapping application that translates results from Aims 1 and 2 through a novel data visualization of perinatal health disparities in Montana. This mapping application can be used by policymakers and researchers as a tool that provides an evidence-based framework for redesigning perinatal health care systems in rural, medically underserved areas.