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Regionalization of Acute Stroke Care for Rural Populations: A Systems Modeling Approach

Regionalization of Acute Stroke Care for Rural Populations: A Systems Modeling Approach
农村人口急性中风护理的区域化:系统建模方法
批准号:
10567098
负责人:
Mehul D. Patel
金额:
$59.12万
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:
2023-07-07 至 2028-01-31

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中文摘要
翻译
项目总结/摘要 中风是导致死亡和严重长期残疾的主要原因,对农村人口的破坏性尤其大。 社区.在美国,农村地区的中风死亡率估计比农村地区高30%。 市区对时间敏感的急性中风治疗有限是农村差距的重要原因 中风发病率和死亡率。协调紧急医疗服务的区域中风护理系统 (EMS),急诊室,设施间转移机构和医院可以改善急性 为服务不足的人群提供中风护理。然而,有效和高效的中风系统设计的证据 缺乏战略。通过EMS进行院前卒中筛查并直接发送至卒中中心 专业提供高级护理可以显著缩短治疗时间, 结果。然而,最佳EMS卒中分诊和转运策略, 病人和有效地使用紧急医疗资源在很大程度上是未知的,并取决于区域和 地方特色。因此,我们的总体目标是开发一个决策分析系统模型, 允许卒中系统规划者比较区域化EMS分诊和运输策略的潜在影响 农村卒中结局和卫生保健资源利用。决策分析建模是一个严格的, 采用灵活的方法整合信息来源,对系统级战略进行计算机测试, 不同的背景。这一比较证据为决策者提供了宝贵和及时的信息, 使干预措施适合实际执行和评价。使用现有的真实世界数据源, 公布的证据,和关键利益相关者的投入,我们将建立一个计算机模拟模型, 北卡罗来纳州70个乡村县的中风护理。我们的具体目标是:(1)确定EMS卒中分诊 和运输策略,优化农村中风患者的功能结果;(2)估计潜在的 农村EMS分诊和运输对卫生保健资源利用的全系统影响;(3)了解 农村人口和卫生保健系统特征对优化EMS卒中分诊的影响, 运输战略。作为对NOT-MD-20-025的回应,本项目旨在了解和解决卒中 通过改善服务不足的农村人口及时获得紧急护理的机会,实现了不平等。一旦成功 完成后,我们将贡献一个新的决策支持框架,以了解和改善区域 中风护理系统在不同的设置。我们未来的研究将实施完善的EMS中风分诊 和运输策略,并前瞻性地评估长期患者结局, 医疗费用。这一研究领域具有很高的潜力,可以解决重大的发病率和死亡率, 由急性中风和其他时间和资源依赖的医疗紧急情况引起的健康差异(例如, 心肌梗塞、败血症和创伤)。
英文摘要
Project Summary/Abstract Stroke is a leading cause of death and serious long-term disability and particularly devastating to rural communities. In the United States, rural areas have an estimated 30% greater stroke mortality compared to urban areas. Limited access to time-sensitive acute stroke therapies is an important cause of rural disparities in stroke morbidity and mortality. Regional stroke systems of care that coordinate emergency medical services (EMS), emergency departments, inter-facility transfer agencies, and hospitals can improve access to acute stroke care for underserved populations. However, evidence on effective and efficient stroke system designs and strategies is lacking. Prehospital stroke screening by EMS and routing directly to a stroke center specialized in providing advanced care can significantly reduce time to treatment and improve patient outcomes. However, optimal EMS stroke triage and transport strategies that maximize benefit to stroke patients and efficiently use emergency medical resources are largely unknown and depend on regional and local characteristics. Therefore, our overall objective is to develop a decision-analytic systems model that allows stroke system planners to compare potential effects of regionalized EMS triage and transport strategies on rural stroke outcomes and health care resource utilization. Decision-analytic modeling is a rigorous and flexible approach for integrating information sources to conduct in silico testing of system-level strategies under varying contexts. This comparative evidence provides valuable and timely information to decision makers to tailor interventions for real-world implementation and evaluation. Using existing real-world data sources, published evidence, and key stakeholder input, we will build a computer simulation model of regionalized stroke care for 70 rural counties in North Carolina. Our specific aims are to: (1) determine EMS stroke triage and transport strategies that optimize functional outcomes in rural stroke patients; (2) estimate the potential system-wide effects of rural EMS triage and transport on health care resource utilization; and (3) understand the influence of rural population and health care system characteristics on optimizing EMS stroke triage and transport strategies. In response to NOT-MD-20-025, this project aims to understand and address stroke disparities by improving access to timely acute care for underserved rural populations. Upon successful completion, we will have contributed a novel decision support framework to understand and improve regional stroke systems of care across various settings. Our future research will implement refined EMS stroke triage and transport strategies into rural systems and prospectively evaluate long-term patient outcomes and healthcare costs. This line of research has high potential to address significant morbidity and mortality and health disparities caused by acute stroke and other time- and resource-dependent medical emergencies (e.g., myocardial infarction, sepsis, and trauma).
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