I-Corps: Translation Potential of a Centralized Platform for Health Services Research

I-Corps：卫生服务研究集中平台的翻译潜力

• 批准号: 2409580
• 负责人: Ferhat Zengul
• 金额: $ 5万
• 依托单位: University of Alabama at Birmingham
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-03-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2409580&HistoricalAwards=false
• 关键词: Corps; Translation; Potential; Centralized; Platform

This I-Corps project develops a centralized data management platform for health services researchers and data-resource related decision-makers at academic organizations. The technology provides data management and analytics tools to researchers to expedite their work and allow more time to focus on networking, scientific discovery, and innovation. In addition, the technology provides advanced data cleansing and preprocessing, and may be used with data solutions for the emerging synthetic data industry and generative artificial intelligence (AI) technologies. The platform's streamlined processes are designed to generate evidence-based knowledge that may be leveraged by healthcare administrators, policymakers, and decision-makers to enhance healthcare services. In the future, the platform may not only serve as a research tool but also facilitate data-informed decision-making capabilities for users.This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of the technology. The solution is based on the development of software technology that addresses the challenges health services researchers face with data aggregation, cleansing, integration, and maintenance from public and private sources. The technology uses a centralized data warehouse, providing analysis-ready data sets and alleviating researchers from repetitive data tasks. In addition, it refines aspects of data management by improving data acquisition, extraction, preprocessing, and cleansing phases using a mix of traditional statistical tools and advanced artificial intelligence (AI) algorithms. As the platform integrates new data sources and methodologies, it's designed to expand, ensuring scalability. This approach may save researchers time and resources, enabling them to focus on the intellectual pursuits of their research.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.

这个I-Corps项目为卫生服务研究人员和学术组织的数据资源研究人员和数据资源相关的决策者开发了集中的数据管理平台。 该技术为研究人员提供数据管理和分析工具，以加快其工作，并让更多时间专注于网络，科学发现和创新。 此外，该技术还提供了高级数据清理和预处理，可以与新兴合成数据行业和生成人工智能（AI）技术的数据解决方案一起使用。 该平台简化的流程旨在产生基于证据的知识，医疗保健管理人员，政策制定者和决策者可能会利用，以增强医疗保健服务。 将来，该平台不仅可以用作研究工具，而且还可以促进数据知识的决策能力。该I-Corps项目利用体验式学习以及对行业生态系统的第一手研究来评估该技术的翻译潜力。该解决方案是基于软件技术的开发，该软件技术通过数据聚合，清洁，集成和公共和私人来源的数据聚合，清洁，整合和维护面对挑战。 该技术使用集中式数据仓库，提供准备分析的数据集并减轻重复数据任务的研究人员。此外，它通过使用传统统计工具和高级人工智能（AI）算法的混合物来改善数据获取，提取，预处理和清洁阶段来完善数据管理的各个方面。 随着平台集成新的数据源和方法，它旨在扩展并确保可扩展性。 这种方法可以节省研究人员的时间和资源，使他们能够专注于研究的智力追求。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛的影响评估标准通过评估来支持的。