EAGER: An Open Data Sharing Platform for Substance Use Disorders

EAGER：药物使用障碍的开放数据共享平台

• 批准号: 1945764
• 负责人: Siddhartha Sikdar
• 金额: $ 20万
• 依托单位: George Mason University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-01 至 2022-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1945764&HistoricalAwards=false
• 关键词: EAGER; Open; Data; Sharing; Platform

This project promotes the progress of data science to address the opioid overdose crisis currently ravaging communities across the nation, as well as to address substance use disorders more broadly. Numerous local, state, and federal efforts are underway to collect data relevant to substance use epidemiology, the availability of services, and response strategies. The challenge is that though there is a large volume of diverse and increasingly public data sources (e.g., national epidemiology surveys, mortality records, prescription drug monitoring, housing, health claims), these data sources are often fragmented, siloed in isolated portals, restricted by data-sharing agreements, and are difficult to use as there are no uniform standards for data collection or dissemination. The strategies necessary for linking these data to generate meaningful, actionable knowledge that is easily accessible for different stakeholder communities have not been developed. This project will develop and disseminate an open platform that will extract and integrate relevant data and provide toolkits that will enable stakeholder groups to take timely, appropriate action to manage substance use and other health and social challenges in their communities. To achieve this objective, the project brings together an interdisciplinary team from academia, industry, and government, with expertise in engineering, physical and social science disciplines to accomplish three tasks: 1) The team will create an open data sharing environment based at George Mason University. 2) The team will develop and test a data extraction and integration layer that will aggregate data appropriately to comply with confidentiality constraints from data stewards of proprietary data sets. The data integration will enable multiple disparate datasets to be linked at multiple geographical scales using de-identified profiles. 3) The team will work with domain experts and community stakeholders to develop, deploy, and refine data-driven analytics methods and toolkits for use cases to answer pressing community needs. The project will result in an open data framework with the potential to transform the current status quo of a crisis-driven acute system of care for substance abuse to data-driven pre-emptive, precision-targeted system of care. The open data framework has the potential to enable communities and government agencies to improve policies and practices through improved identification of relevant factors, prediction, targeting and coordination of resources, interventions and evaluation for managing substance use disorders.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该项目促进了数据科学的进步，以解决目前肆虐全国各地社区的阿片类药物过量危机，以及更广泛地解决物质使用障碍。许多地方、州和联邦正在努力收集与物质使用流行病学、服务可用性和应对策略相关的数据。挑战在于，尽管存在大量多样化且日益公开的数据源（例如，这些数据来源往往是零散的，孤立地存在于孤立的门户网站中，受到数据共享协议的限制，而且由于没有统一的数据收集或传播标准而难以使用。尚未制定必要的战略，将这些数据联系起来，以产生有意义的、可采取行动的知识，使不同的利益攸关方群体能够容易地获得这些知识。该项目将开发和传播一个开放平台，提取和整合相关数据，并提供工具包，使利益攸关方群体能够及时采取适当行动，管理其社区的药物使用和其他健康和社会挑战。为了实现这一目标，该项目汇集了来自学术界，工业界和政府的跨学科团队，具有工程，物理和社会科学学科的专业知识，以完成三项任务：1）该团队将在乔治梅森大学创建一个开放的数据共享环境。2)该小组将开发和测试一个数据提取和集成层，该层将适当地聚合数据，以遵守专有数据集数据管理员的保密限制。数据整合将使多个完全不同的数据集能够使用去识别的概况在多个地理尺度上联系起来。3)该团队将与领域专家和社区利益相关者合作，开发、部署和完善数据驱动的分析方法和工具包，以满足迫切的社区需求。该项目将产生一个开放的数据框架，有可能将目前由危机驱动的药物滥用急性护理系统的现状转变为由数据驱动的先发制人、精确定位的护理系统。开放式数据框架有潜力使社区和政府机构能够通过改进相关因素的识别、预测、目标定位和资源协调、干预和评估来改善政策和实践，以管理物质使用障碍。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估来支持。