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在 COVID-19 大流行期间通过耶鲁医学院创新的 COVID-19 数据探索者和存储库促进协作奖学金:开发和可用性研究。

Promoting Collaborative Scholarship During the COVID-19 Pandemic Through an Innovative COVID-19 Data Explorer and Repository at Yale School of Medicine: Development and Usability Study.

机构信息

Clinical and Translational Research Accelerator, Yale School of Medicine, Yale University, New Haven, CT, United States.

Department of Pediatrics, Yale School of Medicine, Yale University, New Haven, CT, United States.

出版信息

JMIR Form Res. 2024 Sep 3;8:e52120. doi: 10.2196/52120.

Abstract

BACKGROUND

The COVID-19 pandemic sparked a surge of research publications spanning epidemiology, basic science, and clinical science. Thanks to the digital revolution, large data sets are now accessible, which also enables real-time epidemic tracking. However, despite this, academic faculty and their trainees have been struggling to access comprehensive clinical data. To tackle this issue, we have devised a clinical data repository that streamlines research processes and promotes interdisciplinary collaboration.

OBJECTIVE

This study aimed to present an easily accessible up-to-date database that promotes access to local COVID-19 clinical data, thereby increasing efficiency, streamlining, and democratizing the research enterprise. By providing a robust database, a broad range of researchers (faculty and trainees) and clinicians from different areas of medicine are encouraged to explore and collaborate on novel clinically relevant research questions.

METHODS

A research platform, called the Yale Department of Medicine COVID-19 Explorer and Repository (DOM-CovX), was constructed to house cleaned, highly granular, deidentified, and continually updated data from over 18,000 patients hospitalized with COVID-19 from January 2020 to January 2023, across the Yale New Haven Health System. Data across several key domains were extracted including demographics, past medical history, laboratory values during hospitalization, vital signs, medications, imaging, procedures, and outcomes. Given the time-varying nature of several data domains, summary statistics were constructed to limit the computational size of the database and provide a reasonable data file that the broader research community could use for basic statistical analyses. The initiative also included a front-end user interface, the DOM-CovX Explorer, for simple data visualization of aggregate data. The detailed clinical data sets were made available for researchers after a review board process.

RESULTS

As of January 2023, the DOM-CovX Explorer has received 38 requests from different groups of scientists at Yale and the repository has expanded research capability to a diverse group of stakeholders including clinical and research-based faculty and trainees within 15 different surgical and nonsurgical specialties. A dedicated DOM-CovX team guides access and use of the database, which has enhanced interdepartmental collaborations, resulting in the publication of 16 peer-reviewed papers, 2 projects available in preprint servers, and 8 presentations in scientific conferences. Currently, the DOM-CovX Explorer continues to expand and improve its interface. The repository includes up to 3997 variables across 7 different clinical domains, with continued growth in response to researchers' requests and data availability.

CONCLUSIONS

The DOM-CovX Data Explorer and Repository is a user-friendly tool for analyzing data and accessing a consistently updated, standardized, and large-scale database. Its innovative approach fosters collaboration, diversity of scholarly pursuits, and expands medical education. In addition, it can be applied to other diseases beyond COVID-19.

摘要

背景

COVID-19 大流行引发了大量涵盖流行病学、基础科学和临床科学的研究文献。得益于数字革命,现在可以访问大型数据集,这也使得实时疫情追踪成为可能。然而,尽管如此,学术教师及其学员仍在努力获取全面的临床数据。为了解决这个问题,我们设计了一个临床数据存储库,以简化研究流程并促进跨学科合作。

目的

本研究旨在提供一个易于访问的最新数据库,以促进获取本地 COVID-19 临床数据,从而提高效率、简化流程并使研究事业民主化。通过提供一个强大的数据库,鼓励来自不同医学领域的广泛研究人员(教师和学员)和临床医生探索和合作具有临床相关性的新问题。

方法

构建了一个名为 Yale 医学系 COVID-19 探索者和存储库(DOM-CovX)的研究平台,以容纳来自耶鲁纽黑文卫生系统的超过 18000 名 COVID-19 住院患者的清洁、高度细化、去识别和持续更新的数据,这些数据来自 2020 年 1 月至 2023 年 1 月。从多个关键领域提取了数据,包括人口统计学、既往病史、住院期间的实验室值、生命体征、药物、影像学、程序和结果。由于几个数据领域的时变性质,构建了汇总统计信息以限制数据库的计算规模,并提供一个更合理的数据文件,供更广泛的研究社区用于基本统计分析。该倡议还包括前端用户界面 DOM-CovX Explorer,用于聚合数据的简单数据可视化。详细的临床数据集在经过审查委员会审查后可供研究人员使用。

结果

截至 2023 年 1 月,DOM-CovX Explorer 已收到来自耶鲁不同小组的 38 份请求,该存储库已将研究能力扩展到包括临床和研究型教师和学员在内的 15 个不同外科和非外科专业的多元化利益相关者。一个专门的 DOM-CovX 团队指导数据库的访问和使用,这加强了部门间的合作,促成了 16 篇同行评议论文的发表、2 个预印本服务器上的项目以及 8 个科学会议的演讲。目前,DOM-CovX Explorer 仍在不断扩展和改进其界面。该存储库包含来自 7 个不同临床领域的多达 3997 个变量,并且随着研究人员的请求和数据可用性的增加,还在不断增长。

结论

DOM-CovX Data Explorer 和 Repository 是一个用于分析数据和访问一致更新、标准化和大规模数据库的用户友好工具。它的创新方法促进了合作、学术追求的多样性,并扩展了医学教育。此外,它可以应用于 COVID-19 以外的其他疾病。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/780c/11408881/bf1571d2c999/formative_v8i1e52120_fig1.jpg

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