Cross-cutting theme 1: Big Data and Computing innovation

新的数字技术的出现使得大量关于健康暴露和结果的信息能够使用先进的统计技术进行捕获、存储和分析。“大数据”将为开展研究提供新的方法，并有可能大幅提高临床研究的规模和效率。PHRU的这一开创性工作计划旨在利用大数据方法促进大规模流行病学研究，并通过识别有效开展随机试验的障碍来提高随机试验的效率。这项工作得到了一个计算团队的支持，该团队生产和维护旨在满足我们新的和正在进行的研究的具体要求的系统，并确保它们具有足够的适应性，为未来的工作提供平台。我们的系统专注于研究质量的关键方面：招募大量合格参与者;数据收集和研究开展;研究管理，协调和监督;实验室管理，包括分析和储存;结果的确定，确认和分类;以及分析，报告和传播。

The emergence of new digital technologies is allowing huge quantities of information on health exposures and outcomes to be captured, stored, and analysed using advanced statistical techniques. ‘Big Data’ will provide new ways to conduct research and offers the potential of a dramatic increase in the scale and efficiency of clinical studies. This pioneering programme of work within PHRU aims to harness Big Data methodology to facilitate large-scale epidemiological studies and improve the efficiency of randomised trials by identifying barriers to their efficient conduct. This work is supported by a computing team that produces and maintains systems designed to meet the specific requirements of our new and on-going studies, and to ensure that they are sufficiently adaptable to provide a platform for future work. Our systems focus on aspects that are key to study quality: recruitment of large numbers of eligible participants; data collection and study conduct; study management, coordination and oversight; laboratory management including analysis and storage; ascertainment, confirmation and classification of outcome; and analysis, reporting and dissemination.