Increasing Healthcare Access to At-Risk Populations: Research-based Policies for Mobile Health Clinics

增加高危人群的医疗保健可及性：基于研究的移动医疗诊所政策

• 批准号: 1637347
• 负责人: Rigoberto Delgado
• 金额: $ 24.93万
• 依托单位: The University of Texas Health Science Center at Houston
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-01 至 2018-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1637347&HistoricalAwards=false
• 关键词: Increasing; Healthcare; Access; Risk; Populations

IIS-1637347 Increasing Healthcare Access to At-Risk Populations:Research-based Policies for Mobile Health Clinics Project Description Mobile clinics play an important role in providing healthcare to at-risk populations in both urban and rural areas. Currently, over 1500 mobile clinics operate in the US and handle over 5 million visits per year providing essential healthcare services. These programs, however, have grown organically over time and it is important to establish evidence-based approaches to encourage a systematic expansion of this essential healthcare delivery model. This proposal addresses this issue through the use of epidemiological and economic GIS data, combined with proprietary routing software, to implement a program for optimal delivery of mobile clinic healthcare services in the Houston, Texas, region. The project involves eight different providers and includes designing systematic strategies for meeting future healthcare needs of low-income communities. The aim is also to develop models and techniques that can be implemented by mobile clinic programs throughout the country. Early estimates indicate that this project can result in 20% increase in mobile health clinic capacity, which could translate into significant savings in healthcare costs, and considerable improvements in quality of life for the poor. These results are in line with the NSF mission goal of promoting the advancement of health.The overall goal of this project is to optimize and implement a data-based program for coordinated deployment of mobile clinic programs. We will initially identify optimal expansion strategies for the eight current mobile clinics programs to meet the fast-growing demand for healthcare services in underserved communities. The project will then measure the potential of the developed models and techniques and apply them to mobile clinic programs in other regions of Texas and other states in the nation. To achieve the above goals, the team will first apply data mining and forecasting techniques to estimate present and future demand of healthcare services in selected communities. We will combine these approaches with advance GIS mapping tools and stochastic measures to identify target population clusters. We will also conduct survey and economic analysis to measure the operational cost and identify operational constraints in the present mobile clinic programs, and develop new optimization models for the deployment of the mobile clinic service. Then, we will develop new effective techniques to solve the developed optimization models to estimate the maximum capacity of the current mobile health clinic programs in the Houston region, and identify expansion strategies to meet the future service demand while minimizing cost. Lastly, we will estimate overall healthcare cost savings and quality of life impact at the community level at baseline and post-intervention.

IIS-1637347增加高危人群的医疗服务：基于研究的移动的健康诊所政策项目描述移动的诊所在为城市和农村地区的高危人群提供医疗服务方面发挥着重要作用。目前，超过1500家移动的诊所在美国运营，每年处理超过500万次访问，提供基本的医疗保健服务。然而，这些计划随着时间的推移而有机地发展，重要的是要建立以证据为基础的方法，以鼓励系统地扩展这种基本的医疗保健提供模式。该提案通过使用流行病学和经济地理信息系统数据，结合专有路由软件，解决了这个问题，以实施一项计划，在得克萨斯州休斯顿地区的移动的诊所医疗保健服务的最佳交付。该项目涉及八个不同的提供者，包括设计系统的战略，以满足低收入社区未来的医疗保健需求。其目的还在于开发可由全国各地的移动的诊所项目实施的模型和技术。初步估计表明，该项目可使移动的保健诊所的能力增加20%，从而可大大节省保健费用，并大大改善穷人的生活质量。这些结果符合NSF促进健康进步的使命目标。本项目的总体目标是优化和实施基于数据的程序，以协调部署移动的诊所程序。我们将初步确定目前八个移动的诊所项目的最佳扩张策略，以满足服务不足社区对医疗服务快速增长的需求。然后，该项目将衡量开发的模型和技术的潜力，并将其应用于德克萨斯州其他地区和美国其他州的移动的诊所项目。为达致上述目标，研究小组将首先应用数据挖掘及预测技术，估计选定社区现时及未来的医疗服务需求。我们将联合收割机将这些方法与先进的GIS制图工具和随机措施相结合，以确定目标人口集群。我们亦会进行调查及经济分析，以衡量目前移动的诊所计划的营运成本及找出营运上的限制，并为部署移动的诊所服务开发新的优化模式。然后，我们将开发新的有效的技术来解决开发的优化模型，以估计在休斯敦地区目前的移动的健康诊所计划的最大容量，并确定扩展策略，以满足未来的服务需求，同时最大限度地降低成本。最后，我们将估计基线和干预后社区层面的整体医疗保健成本节约和生活质量影响。