A National Center for Digital Health Informatics Innovation

项目概要 本地解决方案很少扩展到多机构环境，并且无法实现 CTSA 催化数据的愿景 - 驱动的转化研究。数据、软件和人员在很大程度上是分散且互不关联的 CTSA。 CTSA 拥有大量既不可访问也不可互操作的数据；这阻碍了机会 创新算法和工具。 反过来，工具也会遭受短视焦点或盲目重复的困扰。寻找专家合作伙伴极其困难 无论是对罕见疾病的候选变异进行功能验证、寻找临床队列还是导航 创办公司的知识产权冒险之旅。建立真正的学习型卫生系统面临着挑战，其中 高质量的临床和研究数据可以在临床护理中有效且高效地重复使用。 CD2H 有 利用来自各地临床机构的新冠病毒数据，建立了国家新冠肺炎队列协作组织 (N3C) 国家。 该公开数据资源包括成人和儿科数据，可以解决以下问题 与疫苗有效性、治疗方法和疾病严重程度的预测有关。儿科 COVID-19 DREAM Challenge 将要求社区参与者利用国家数据来预测儿童的严重状况 COVID 队列协作 (N3C) 电子健康记录 (EHR) 数据。对此所期望的结果 面临的挑战是建立训练有素且经过验证的儿科 COVID-19 严重程度预测模型，该模型可以 实施到 EHR 的临床工作流程中，以帮助促进适当的治疗。

Project Summary Local solutions rarely scale to multi-institutional settings, and don’t realize the vision of CTSAs catalyzing data- driven translational research. Data, Software, and People are Largely Decentralized and Unconnected in CTSA. CTSAs hold a wealth of data that is neither accessible nor interoperable; this hinders opportunities to innovate algorithms and tools. Tools in turn, suffer from myopic focus or blind duplication. It is extremely difficult to identify expert partners whether for functionally validating a candidate variant for a rare disease, finding clinical cohorts, or navigating the IP odyssey of starting a company. There are the challenges in building a truly learning health system where high quality clinical and research data can effectively and efficiently be reused in clinical care. The CD2H has developed the National COVID Cohort Collaborative (N3C) with COVID data from clinical institutions across the country. This publicly available data resource includes data on adults and pediatrics and can address the questions related to vaccine effectiveness, treatments and predictions of severity of illness. The Pediatric COVID-19 DREAM Challenge will ask community participants to predict severity status in children, using the National COVID Cohort Collaborative (N3C) Electronic Health Record (EHR) data. The desired outcome for this challenge is to produce trained and validated pediatric COVID-19 severity prediction models that can be implemented into a clinical workflow in an EHR to help facilitate appropriate treatment.