Urgent research and surveillance on Covid-19 using the new OpenSAFELY secure platform across 55 million patients' full linked primary care records

使用新的 OpenSAFELY 安全平台对 5500 万患者的完整链接初级保健记录进行针对 Covid-19 的紧急研究和监测

• 批准号: MR/V015737/1
• 负责人: Ben Goldacre
• 金额: $ 166.49万
• 依托单位: University of Oxford
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=MR%2FV015737%2F1
• 关键词: Urgent; research; surveillance; Covid; 19

We are delivering a platform for analysing healthcare data, currently including 27 million patients' GP records (with identifiable information removed), soon expanding to 55 million. This unprecedented scale is needed for rapid results during Covid-19.OpenSAFELY uses a new model for maximum efficiency and privacy: rather than copying large volumes of information from GP records into another location, which involves security risks, we have instead built a secure analytics platform inside the data centres where GP records already reside, and linked to all relevant Covid-19 outcomes data such as death records and intensive care.We have set this up rapidly and our first analyses are already complete. We now urgently need funds to sustain the platform, and to accelerate and expand our work on the following three workstreams:1) Further research to identify which patients are at higher risk of admission, ventilation and death from Covid-19, to inform management, seclusion advice, service planning, and underlying mechanisms behind these findings (e.g. is there higher risk among BAME groups simply because of previous medical conditions?); and to explore hypotheses on certain drugs helping to protect people against poor outcomes, including ibuprofen, asthma drugs, anticoagulants, and other treatments. 2) Predicting local spread and service need, and evaluating exit strategies from lockdown, by creating models of disease transmission which combine "disease-dynamics" approaches with detailed clinical data on Covid-19 prevalence and the population at risk in every local area.3) Measuring and mitigating the indirect health impacts of Covid-19 on, for example, cancer diagnosis and referrals, cardiovascular management, vaccinations, etc, and identifying urgent necessary actions both nationally and in smaller regions.

我们正在提供一个分析医疗数据的平台，目前包括2700万患者的GP记录（删除了可识别信息），很快将扩展到5500万。这种前所未有的规模是在Covid-19期间快速取得成果所必需的。OpenSAFELY使用了一种新的模式来实现最大的效率和隐私：我们没有将GP记录中的大量信息复制到另一个位置（这涉及安全风险），而是在GP记录已驻留的数据中心内构建了一个安全分析平台，并与所有相关的Covid-19结果数据（如死亡记录和重症监护）相关联。我们已经迅速建立了这一点，我们的第一批分析已经完成。我们现在迫切需要资金来维持这个平台，并加快和扩大我们在以下三个工作流程上的工作：1）进一步研究，以确定哪些患者因新冠肺炎入院、通气和死亡的风险较高，为管理、隔离建议、服务规划以及这些发现背后的潜在机制提供信息（例如，BAME群体中的风险较高是否仅仅是因为以前的医疗状况？）;并探讨某些药物有助于保护人们免受不良后果的假设，包括布洛芬，哮喘药物，抗凝剂和其他治疗方法。2)通过创建疾病传播模型，将联合收割机方法与每个地方的Covid-19患病率和风险人群的详细临床数据相结合，预测当地传播和服务需求，并评估封锁后的退出策略。3）衡量和减轻Covid-19对癌症诊断和转诊、心血管管理、疫苗接种等的间接健康影响，并确定国家和较小区域的紧急必要行动。

项目成果

Overall and cause-specific hospitalisation and death after COVID-19 hospitalisation in England: cohort study in OpenSAFELY using linked primary care, secondary care and death registration data

• DOI: 10.1101/2021.07.16.21260628
• 发表时间: 2021-07
• 作者: K. Bhaskaran;C. Rentsch;G. Hickman;W. Hulme;Anna Schultze;H. Curtis;K. Wing;C. Warren-Gash;L. Tomlinson;C. Bates;R. Mathur;B. Mackenna;V. Mahalingasivam;A. Wong;A. Walker;C. Morton;D. Grint;A. Mehrkar;R. Eggo;P. Inglesby;I. Douglas;H. Mcdonald;J. Cockburn;E. Williamson;D. Evans;J. Parry;F. Hester;S. Harper;S. Evans;S. Bacon;L. Smeeth;B. Goldacre

HIV infection and COVID-19 death: a population-based cohort analysis of UK primary care data and linked national death registrations within the OpenSAFELY platform.

• DOI: 10.1016/s2352-3018(20)30305-2
• 发表时间: 2021-01
• 期刊: The lancet. HIV
• 作者: Bhaskaran K;Rentsch CT;MacKenna B;Schultze A;Mehrkar A;Bates CJ;Eggo RM;Morton CE;Bacon SCJ;Inglesby P;Douglas IJ;Walker AJ;McDonald HI;Cockburn J;Williamson EJ;Evans D;Forbes HJ;Curtis HJ;Hulme WJ;Parry J;Hester F;Harper S;Evans SJW;Smeeth L;Goldacre B
• 通讯作者: Goldacre B

OpenSAFELY: Representativeness of electronic health record platform OpenSAFELY-TPP data compared to the population of England.

• DOI: 10.12688/wellcomeopenres.18010.1
• 发表时间: 2022
• 期刊: Wellcome open research

OpenSAFELY: Representativeness of Electronic Health Record platform OpenSAFELY-TPP data compared to the population of England

OpenSAFELY：电子健康记录平台 OpenSAFELY-TPP 数据与英格兰人口相比的代表性

• DOI: 10.1101/2022.06.23.22276802
• 发表时间: 2022
• 作者: Andrews C

Overall and cause-specific hospitalisation and death after COVID-19 hospitalisation in England: A cohort study using linked primary care, secondary care, and death registration data in the OpenSAFELY platform.

• DOI: 10.1371/journal.pmed.1003871
• 发表时间: 2022-01
• 期刊: PLoS medicine
• 影响因子: 15.8
• 作者: Bhaskaran K;Rentsch CT;Hickman G;Hulme WJ;Schultze A;Curtis HJ;Wing K;Warren-Gash C;Tomlinson L;Bates CJ;Mathur R;MacKenna B;Mahalingasivam V;Wong A;Walker AJ;Morton CE;Grint D;Mehrkar A;Eggo RM;Inglesby P;Douglas IJ;McDonald HI;Cockburn J;Williamson EJ;Evans D;Parry J;Hester F;Harper S;Evans SJ;Bacon S;Smeeth L;Goldacre B
• 通讯作者: Goldacre B