Maternal Health Data Innovation and Coordination Hub

孕产妇健康数据创新与协调中心

• 批准号: 10748737
• 负责人: Andreea Alina Creanga
• 金额: $ 200万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-15 至 2030-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10748737
• 关键词: Area; Artificial Intelligence; Award; Bioethics; Centers of Research Excellence; Clinical; Collaborations; Common Data Element; Communication; Communities; Data; Data Analyses; Data Collection; Data Science; Data Set; Data Storage and Retrieval; Development; Documentation; Equity; Evaluation; FAIR principles; Family; Fostering; Funding; Generations; Goals; Human; Informatics; Infrastructure; Ingestion; Knowledge; Machine Learning; Maternal Health; Medical; Mentorship; Methods; Observational Study; Ontology; Outcome; Patients; Peer Review; Population Heterogeneity; Pregnancy Outcome; Preparation; Process; Public Health Schools; Recommendation; Registries; Reporting; Reproducibility; Research; Research Project Grants; Research Support; Resources; Scholarship; Secure; Security; Site; Specialist; Standardization; Statistical Data Interpretation; Techniques; Terminology; Training; United States National Institutes of Health; Universities; Vision; career development; cloud based; data hub; data integration; data modeling; data repository; data reuse; data sharing; experience; health data; health disparity; health economics; health equity; implementation science; improved; innovation; interest; medical schools; multidisciplinary; open source; patient safety; precision medicine; programs; quality assurance; repository; skills; symposium; tool; web site

Project Summary The Johns Hopkins University (JHU) seeks to strengthen the coordination of innovative research and practice efforts in maternal health through collaboration with the National Institutes of Health (NIH) and their Implementing a Maternal Health and Pregnancy Outcomes Vision for Everyone (IMPROVE) initiative grantees. The overarching goals of this project are to establish and maintain a Maternal Health Data Innovation and Coordination Hub to support Maternal Health Research Centers of Excellence, and to facilitate the reuse of the data they generate. The project will be implemented by a multidisciplinary team of maternal health experts and biostatisticians at JHU’s Bloomberg School of Public Health, and informatics and data science specialists at JHU’s School of Medicine, with support from an Experts’ Bureau comprised of subject matter experts in health equity, bioethics, health economics, patient safety, patient and family engagement in research. Key project activities are to establish and maintain a secure, cloud-based coordination platform with controlled access, and a public-facing Data Hub website; develop common data elements using a modified Delphi approach; support the use of a common data model; provide data collection and analysis tools with integrated quality assurance workflows; provide support for statistical analyses using traditional and artificial intelligence/machine learning techniques; prepare and share data with NIH repositories; provide technical assistance and skills coaching, training, and professional development opportunities to Research Centers/IMPROVE grantees. Our proposal has technical and conceptual areas of innovation. Most notably, the proposed integration of the Data Hub with an existing research coordination platform with demonstrated feasibility -- JHU’s Precision Medicine Analytics Platform (PMAP). It utilizes the Observational Health Data Science and Informatics (OHDSI) open-source community and the Observational Medical Outcomes Partnership (OMOP), employed by large NIH-funded research. OMOP is based upon standard clinical terminologies; enables extraction, ingestion, collation of variables of interest into an observational research registry; and has the capability for data storage, security, analysis, and transfer among participating sites. Also innovative are the proposed training and career development opportunities, including tuition scholarships, data challenge awards, and a mentorship program. We anticipate that these activities will lead to short-term and intermediate outcomes (e.g. improved data science capabilities; generation of findable, accessible, interoperable, and reusable data), which, over the long-term, will advance research to improve maternal health outcomes and promote equity. Process and outcomes evaluations will ascertain the extent to which our project is successfully supporting Research Centers. Data science methods and findings from research projects will be disseminated on the Data Hub website, through reports, peer-reviewed articles, and scientific presentations.

项目摘要 约翰·霍普金斯大学（JHU）试图加强创新研究和实践的协调 通过与美国国立卫生研究院（NIH）和 他们实施孕妇健康和怀孕成果为每个人（改进）启动的愿景 大家。该项目的总体目标是建立和维护孕产妇健康数据创新 和协调枢纽，以支持孕产妇健康研究中心，并促进再利用 它们生成的数据。该项目将由Mater Health的多学科团队实施 JHU彭博公共卫生学院的专家和生物统计学家以及信息与数据科学 JHU医学院的专家，在专家局的支持下，包括主题 健康公平，生物伦理学，健康经济学，患者安全，患者和家庭参与方面的专家 研究。关键项目活动是建立和维护一个安全的，基于云的协调平台 受控访问和面向公共的数据集线器网站；使用修改后开发常见的数据元素 Delphi方法；支持使用常见数据模型；提供数据收集和分析工具 综合质量保证工作流；使用传统和人工来提供统计分析的支持 智能/机器学习技术；与NIH存储库准备并共享数据；提供技术 协助和技能教练，培训和专业发展机会 中心/改善盛大。我们的建议具有创新的技术和概念领域。最值得注意的是 提议将数据中心与现有研究协调平台的整合与已证明 可行性-JHU的Precision Medicine Analytics平台（PMAP）。它利用观察性健康数据 科学与信息学（OHDSI）开源社区以及观察性医学成果 合作伙伴关系（OMOP），由大型NIH资助的研究进行。 OMOP基于标准临床 术语；可以提取，摄入，将兴趣变量整理到考试中 注册表；并具有数据存储，安全性，分析和参与站点之间的转移功能。还 创新是拟议的培训和职业发展机会，包括学费科学，数据 挑战奖和心态计划。我们预计这些活动将导致短期和 中级结果（例如，提高数据科学能力；可访问，可访问的生成， 可互操作和可重复使用的数据），从长远来看，该数据将提高研究以改善母校健康 结果并促进公平。流程和结果评估将确定我们的项目的程度 成功支持研究中心。研究项目的数据科学方法和发现将是 通过报告，同行评审的文章和科学演示在数据中心网站上传播。