Phase 1 COVID-19 Data and Connectivity – National Core Study (Phase 1 D&C-NCS)

第 1 阶段 COVID-19 数据和连接 — 国家核心研究（第 1 阶段 D

• 批准号: MC_PC_20058
• 负责人: Andrew Morris
• 金额: $ 1936.78万
• 依托单位: Health Data Research UK
• 依托单位国家: 英国
• 项目类别: Intramural
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=MC_PC_20058
• 关键词: Phase; COVID; 19; Data; Connectivity

The Data and Connectivity study sits across the other National Core Studies and delivers a national health data research capability to support COVID-19 research questions, ensuring datasets are discoverable and accessible and linkages are established to answer the priority research questions from the other five National Core Studies. Making data available for wider research use will increase the scope of benefits beyond the specific studies above, leading to unexpected benefits and boosting UK research capacity more generally, increasing return on investment for the NCS programme. Data integration and harmonisation of methods and standards will enable rapid research and development of new interventions and technologies across the spectrum of COVID-19, and knowledge and technology transfer to other clinical and public health areas. Collation and linkage between datasets is critical to bringing the core studies together, ensuring that each of them can deliver against their policy priorities e.g. hospital data may not currently be linked with GP data and wider community data (e.g. socioeconomic data or data on housing and the built environment). Access, cleaning, linkage and use of these datasets together is needed to fully understand links between these factors and outcomes.Delivery of the COVID-19 Data and Connectivity Study will involve close interaction with data custodians, the public and patients, and providers of UK-wide national Trusted Research Environments (TREs) to ensure the required data is stored safely and securely, made readily available to approved researchers and is associated with compute, analytical and data services that make it easier to address priority research questions in a transparent and trustworthy way.Phase 1 will:• Continue to respond to emerging COVID-19 research priorities, mapping key datasets required by the National Core Studies, NIHR UPH Studies and SAGE sub-groups to allow research which can inform policy and operational decision making across the UK• Further develop the data infrastructure and services across the UK to allow faster access to high priority health, administrative, molecular, and behavioural data assets for researchers working on the most important COVID-related studies, ensuring priority research questions can be answered efficiently, in a transparent and trustworthy way. • Strengthen and extend the existing national Trusted Research Environments (TRE) and UK Health Data Research Innovation Gateway infrastructure through inclusive four nations approach ensuring the priority datasets for COVID-19 research are findable, accessible, inter-operable and reusable (FAIR) as a single shop window

数据和连通性研究横跨其他国家核心研究，提供国家健康数据研究能力，以支持COVID-19研究问题，确保数据集可共享和可访问，并建立联系，以回答其他五项国家核心研究的优先研究问题。使数据可用于更广泛的研究用途将增加上述具体研究之外的效益范围，从而带来意想不到的效益，并更普遍地提高英国的研究能力，增加NCS计划的投资回报。数据整合以及方法和标准的协调将有助于快速研究和开发新的干预措施和技术，并将知识和技术转移到其他临床和公共卫生领域。数据集之间的整理和联系对于将核心研究集中在一起至关重要，确保每个研究都可以根据其政策优先事项提供，例如医院数据目前可能没有与GP数据和更广泛的社区数据（例如社会经济数据或住房和建筑环境数据）联系起来。为了充分理解这些因素和结果之间的联系，需要访问、清理、链接和使用这些数据集。COVID-19数据和连通性研究的交付将涉及与数据保管人、公众和患者以及英国全国可信研究环境（TREs）提供商的密切互动，以确保安全可靠地存储所需数据，该平台可随时供经批准的研究人员使用，并与计算、分析和数据服务相关联，使其更容易以透明和值得信赖的方式解决优先研究问题。第一阶段将：·继续应对新出现的COVID-19研究优先事项，绘制国家核心研究所需的关键数据集，NIHR UPH研究和SAGE小组，以允许研究，可以为英国各地的政策和运营决策提供信息·进一步发展英国各地的数据基础设施和服务，以允许更快地获得高优先级的健康，行政，分子，为从事最重要的COVID相关研究的研究人员提供行为数据资产，确保以透明和可信的方式有效回答优先研究问题。·通过包容性四国方法加强和扩展现有的国家可信研究环境（TRE）和英国健康数据研究创新网关基础设施，确保COVID-19研究的优先数据集作为单一商店窗口可查找，可访问，可互操作和可重复使用（FAIR）

项目成果

Harmonising electronic health records for reproducible research: challenges, solutions and recommendations from a UK-wide COVID-19 research collaboration.

• DOI: 10.1186/s12911-022-02093-0
• 发表时间: 2023-01-16
• 期刊: BMC MEDICAL INFORMATICS AND DECISION MAKING
• 影响因子: 3.5
• 作者: Abbasizanjani, Hoda;Torabi, Fatemeh;Bedston, Stuart;Bolton, Thomas;Davies, Gareth;Denaxas, Spiros;Griffiths, Rowena;Herbert, Laura;Hollings, Sam;Keene, Spencer;Khunti, Kamlesh;Lowthian, Emily;Lyons, Jane;Mizani, Mehrdad A.;Nolan, John;Sudlow, Cathie;Walker, Venexia;Whiteley, William;Wood, Angela;Akbari, Ashley
• 通讯作者: Akbari, Ashley

Towards mitigating health inequity via machine learning: a nationwide cohort study to develop and validate ethnicity-specific models for prediction of cardiovascular disease risk in COVID-19 patients

通过机器学习减轻健康不平等：一项全国性队列研究，旨在开发和验证用于预测 COVID-19 患者心血管疾病风险的特定种族模型

• DOI: 10.1101/2023.09.13.23295489
• 发表时间: 2023
• 作者: Allery F

Harmonising electronic health records for reproducible research: challenges, solutions and recommendations from a UK-wide COVID-19 research collaboration

协调电子健康记录以进行可重复的研究：英国范围内的 COVID-19 研究合作面临的挑战、解决方案和建议

• DOI: 10.21203/rs.3.rs-2109276/v1
• 发表时间: 2022
• 作者: Abbasizanjani H

Ethnic inequalities in positive SARS-CoV-2 tests, infection prognosis, COVID-19 hospitalisations and deaths: analysis of 2 years of a record linked national cohort study in Scotland.

• DOI: 10.1136/jech-2023-220501
• 发表时间: 2023-10
• 期刊: JOURNAL OF EPIDEMIOLOGY AND COMMUNITY HEALTH
• 影响因子: 6.3
• 作者: Amele, Sarah;Kibuchi, Eliud;McCabe, Ronan;Pearce, Anna;Henery, Paul;Hainey, Kirsten;Fagbamigbe, Adeniyi Francis;Kurdi, Amanj;McCowan, Colin;Simpson, Colin R.;Dibben, Chris;Buchanan, Duncan;Demou, Evangelia;Almaghrabi, Fatima;Anghelescu, Gina;Taylor, Harry;Tibble, Holly;Rudan, Igor;Nazroo, James;Becares, Laia;Daines, Luke;Irizar, Patricia;Jayacodi, Sandra;Pattaro, Serena;Sheikh, Aziz;Katikireddi, Srinivasa Vittal
• 通讯作者: Katikireddi, Srinivasa Vittal

COVID-19 hospital admissions and deaths after BNT162b2 and ChAdOx1 nCoV-19 vaccinations in 2·57 million people in Scotland (EAVE II): a prospective cohort study.

• DOI: 10.1016/s2213-2600(21)00380-5
• 发表时间: 2021-12
• 期刊: The Lancet. Respiratory medicine
• 作者: Agrawal U;Katikireddi SV;McCowan C;Mulholland RH;Azcoaga-Lorenzo A;Amele S;Fagbamigbe AF;Vasileiou E;Grange Z;Shi T;Kerr S;Moore E;Murray JLK;Shah SA;Ritchie L;O'Reilly D;Stock SJ;Beggs J;Chuter A;Torabi F;Akbari A;Bedston S;McMenamin J;Wood R;Tang RSM;de Lusignan S;Hobbs FDR;Woolhouse M;Simpson CR;Robertson C;Sheikh A
• 通讯作者: Sheikh A