PDF(Pubmed)
Abstract：
COVID-19 data have been generated across the United Kingdom as a by-product of clinical care and public health provision, as well as numerous bespoke and repurposed research endeavors. Analysis of these data has underpinned the United Kingdom\'s response to the pandemic, and informed public health policies and clinical guidelines. However, these data are held by different organizations, and this fragmented landscape has presented challenges for public health agencies and researchers as they struggle to find relevant data to access and interrogate the data they need to inform the pandemic response at pace.
We aimed to transform UK COVID-19 diagnostic data sets to be findable, accessible, interoperable, and reusable (FAIR).
A federated infrastructure model (COVID - Curated and Open Analysis and Research Platform [CO-CONNECT]) was rapidly built to enable the automated and reproducible mapping of health data partners\' pseudonymized data to the Observational Medical Outcomes Partnership Common Data Model without the need for any data to leave the data controllers\' secure environments, and to support federated cohort discovery queries and meta-analysis.
A total of 56 data sets from 19 organizations are being connected to the federated network. The data include research cohorts and COVID-19 data collected through routine health care provision linked to longitudinal health care records and demographics. The infrastructure is live, supporting aggregate-level querying of data across the United Kingdom.
CO-CONNECT was developed by a multidisciplinary team. It enables rapid COVID-19 data discovery and instantaneous meta-analysis across data sources, and it is researching streamlined data extraction for use in a Trusted Research Environment for research and public health analysis. CO-CONNECT has the potential to make UK health data more interconnected and better able to answer national-level research questions while maintaining patient confidentiality and local governance procedures.
We aimed to transform UK COVID-19 diagnostic data sets to be findable, accessible, interoperable, and reusable (FAIR).
A federated infrastructure model (COVID - Curated and Open Analysis and Research Platform [CO-CONNECT]) was rapidly built to enable the automated and reproducible mapping of health data partners\' pseudonymized data to the Observational Medical Outcomes Partnership Common Data Model without the need for any data to leave the data controllers\' secure environments, and to support federated cohort discovery queries and meta-analysis.
A total of 56 data sets from 19 organizations are being connected to the federated network. The data include research cohorts and COVID-19 data collected through routine health care provision linked to longitudinal health care records and demographics. The infrastructure is live, supporting aggregate-level querying of data across the United Kingdom.
CO-CONNECT was developed by a multidisciplinary team. It enables rapid COVID-19 data discovery and instantaneous meta-analysis across data sources, and it is researching streamlined data extraction for use in a Trusted Research Environment for research and public health analysis. CO-CONNECT has the potential to make UK health data more interconnected and better able to answer national-level research questions while maintaining patient confidentiality and local governance procedures.
摘要：
背景：COVID-19数据已作为临床护理和公共卫生提供的副产品在英国各地产生，以及许多定制和重新利用的研究努力。对这些数据的分析支持了英国对这一流行病的反应，以及知情的公共卫生政策和临床指南。然而,这些数据由不同的组织持有，这种支离破碎的景观给公共卫生机构和研究人员带来了挑战，因为他们努力寻找相关数据来访问和询问他们需要的数据，以便及时为大流行应对措施提供信息。
目标：我们的目标是将英国COVID-19诊断数据集转变为可查找的，可访问,可互操作，和可重复使用（FAIR）。
方法：快速构建了一个联合基础设施模型（COVID-策划和开放的分析和研究平台[CO-CONNECT]），以实现将健康数据合作伙伴的假名数据自动映射到观察医疗结果合作伙伴共同数据模型，而无需任何数据离开数据控制器的安全环境，并支持联合队列发现查询和荟萃分析。
结果：共有来自19个组织的56个数据集连接到联合网络。数据包括研究队列和通过与纵向医疗保健记录和人口统计相关的常规医疗保健提供收集的COVID-19数据。基础设施是活的，支持对整个英国的数据进行聚合级查询。
结论：CO-CONNECT是由一个多学科团队开发的。它支持跨数据源的快速COVID-19数据发现和即时荟萃分析，它正在研究简化的数据提取，以便在可信的研究环境中进行研究和公共卫生分析。CO-CONNECT有可能使英国的健康数据更加相互联系，并能够更好地回答国家一级的研究问题，同时保持患者的机密性和地方治理程序。
目标：我们的目标是将英国COVID-19诊断数据集转变为可查找的，可访问,可互操作，和可重复使用（FAIR）。
方法：快速构建了一个联合基础设施模型（COVID-策划和开放的分析和研究平台[CO-CONNECT]），以实现将健康数据合作伙伴的假名数据自动映射到观察医疗结果合作伙伴共同数据模型，而无需任何数据离开数据控制器的安全环境，并支持联合队列发现查询和荟萃分析。
结果：共有来自19个组织的56个数据集连接到联合网络。数据包括研究队列和通过与纵向医疗保健记录和人口统计相关的常规医疗保健提供收集的COVID-19数据。基础设施是活的，支持对整个英国的数据进行聚合级查询。
结论：CO-CONNECT是由一个多学科团队开发的。它支持跨数据源的快速COVID-19数据发现和即时荟萃分析，它正在研究简化的数据提取，以便在可信的研究环境中进行研究和公共卫生分析。CO-CONNECT有可能使英国的健康数据更加相互联系，并能够更好地回答国家一级的研究问题，同时保持患者的机密性和地方治理程序。
