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

农村各县获得围产期保健服务的机会一直在下降， （围产期）结果在蒙大拿州等农村地区也较差。妇女获得更多的 全面的围产期服务改善了结果。该项目的主要目标是补救 缺乏关于如何在资源有限的农村地区改善围产期服务的知识， 环境，以改善健康公平。本项目将阐明 蒙大拿州围产期健康结果和围产期护理的可及性。通过绘制完整的 围产期综合服务系统（即，产科护理、精神卫生服务和药物滥用 这项研究将产生新的信息，说明哪里存在不平等现象，并对全系统如何进行建模。 可以进行改进。将采用社区参与的方法， 与社区合作伙伴，以确定问题，开发模型，设计研究方法， 最后公布调查结果。研究小组将成立一个行业咨询委员会， 州政府机构代表、临床医生和农村分娩妇女。该团队将 从全国可用的可靠的二级数据源中整合蒙大拿州的数据，包括 关于社会人口统计学、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果的预测模型。这一目标的两个主要目标是：1） 估计目前对综合围产期保健的需求，2）预测未来对 全面的围产期护理。围产期服务需求人口分布图（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）将得到发展。目标2将制定规范性规划模型，为以下方面的决策提供信息： 提高蒙大拿州围产期护理系统的有效性。这一目标的两个主要目标是：1） 开发一种数据驱动的方法，用于评估附近地区的供应和需求之间的一致程度 为农村母亲提供全面的围产期服务，2）制定规定性的地点规划模式 其目标是最大限度地提高母亲和婴儿的平等和获得机会。Aim 3将设计一个交互式Web- 一个基于地图的应用程序，通过新的数据可视化， 蒙大拿州的围产期健康差异。决策者可以使用这一绘图应用程序， 研究人员作为一种工具，提供了一个基于证据的框架，重新设计围产期保健 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.