MICA: Health e-Research Centre

健康电子研究中心（HeRC）将把北方英格兰未充分使用的电子健康数据转化为新知识和改善的医疗保健。未充分使用的数据源包括NHS和健康科学数据库。HeRC将开发健康信息学（HI）方法，以清理和连接不同的数据源，从而更全面地了解健康模式以及患者对治疗的反应。除了将数据与数据联系起来，HeRC还将数据、分析方法和专家联系在一起，以便更及时和准确地得出结果。HeRC通过三个工作流将目前的数据、方法和专业知识结合起来，以释放其潜力：1）研究和开发HI方法，使更多的健康数据可用于分析; 2）应用HI和相关方法，如计算统计学，解决以前棘手的健康科学和服务问题; 3）培训一批新的健康信息专家，以推动他们的方法及其对前沿研究的支持。与纯粹为研究而采集的数据相比，在提供保健服务过程中产生的数据不完整、不准确，而且在记录中可能会有变化。HeRC将探索患者和临床医生一起记录健康和医疗保健信息的影响，例如患者可以在线访问他们的GP记录。HeRC还将为来自智能手机等技术的大量患者报告数据做好准备。研究人员在使用健康记录时面临的实际问题将得到解决，例如：哪些数据可用，在哪里？我是否有权使用这些数据？我能从其他使用类似数据的人那里学到什么？将开发软件，提供一个研究环境，嵌入关键方法，使他们可以学习和使用。研究环境还将嵌入数据集，使其可共享，同时保持高标准的信息治理。五个研究项目将最大限度地利用关联的健康数据进行研究：鸡舍（与患者共同制作观察报告）该计划将考虑如何使技术充分“吸引”患者，使其足够频繁地使用它们，以提供常规医疗保健中缺失的重要信号记录MOD（错失机会检测器）将使链接数据能够用于回答以下问题：“对于这些因心脏病发作而入院的患者，是否在系统中的某个地方错过了预防机会，公共卫生，全科医疗或更专业的护理？“这些信息可用于将资源用于社区最需要的地方。SEA-3（过敏、哮喘和男科的可扩展内型）将使用HI和高级统计数据来帮助识别似乎患有不同形式的哮喘等的患者，这些患者需要不同的预防或治疗。DOT（Diabesity Outcome Translator）是关于通过让不同地方的研究人员同时处理不同类型的关联数据来加快重要问题的答案-解决诸如“糖尿病常用药物治疗的癌症风险是多少？".翅片（可行性改进网络）将研究如何更好地规划测试新疗法的临床试验，以便在特定时间段内实际参与的人数与试验开始前使用关联数据进行的估计相匹配。为了实现HeRC，该联盟将整合北方英格兰最顶尖的统计中心（位于兰开斯特）、公共卫生中心（位于利物浦）、计算机科学中心（位于曼彻斯特）、和健康经济学/服务研究在约克。这种整合将扩展到NHS，建立在患者，公众和社区参与可信的健康数据再利用研究的有前途的模型（NHS电子实验室）的基础上。

The Health e-Research Centre (HeRC) will turn under-used electronic health data in Northern England into new knowledge and improved healthcare. The under-used data sources include NHS and health science databases. HeRC will develop Health Informatics (HI) methods to clean up and link up the different data sources in ways that give a bigger picture of patterns of health and how patients respond to treatments. As well as linking data to data, HeRC will link data, analytical methods and experts together in order to make more timely and accurate findings.HeRC seeks to unlock the potential in the current islands of data, methods and expertise by joining them in three streams of work: 1) researching and developing HI methodology to make linked health data more available for analysis; 2) applying HI and related methodology, such as computational statistics, to solve previously intractable health science and service questions; and 3) training a new cadre of health informaticians to drive their methodology and its support of cutting-edge research.In contrast to data captured purely for research, data generated during the provision of healthcare are incomplete, inaccurate and subject to variation in recording. HeRC will explore the effects of patients and clinicians recording health and healthcare information together, for example where patients have on-line access to their GP records. HeRC will also prepare for the deluge of patient reported data from technologies such as smartphones.The practical questions that researchers face when using health records will be addressed, for example: Which data are available and where? Do I have permission to use the data? What can I learn from other who used similar data? Software will be developed to provide a research environment that embeds key methods so that they can be learnt and used. The research environment will also embed datasets, making them discoverable, whilst maintaining high standards of information governance.Five research programmes will maximise the value of using linked health data for research: The CoOP (Co-producing Observations with Patients) programme will consider how technologies can be made sufficiently 'engaging' for patients to use them frequently enough to provide important signals that are missing from usual healthcare records. The MOD (Missed Opportunities Detector) will enable linked data to be used to answer questions such as "for these patients who were admitted to hospital with a heart attack, was a prevention opportunity missed somewhere in the system, in public health, general practice or more specialist care?" Such information can be used to target resources to where a community needs them most. The SEA-3 (Scalable Endotypes of Allergies, Asthma and Andrology) will use HI and advanced statistics to help identify patients who appear to have a different form of asthma etc. where different kinds of prevention or treatment are needed. The DOT (Diabesity Outcome Translator) is about speeding up the answering of important questions by getting researchers in different places to work on different kinds of linked data together at the same time - tackling questions such as "what is the cancer risk of common drug treatments for diabetes?". The FIN (Feasibility Improvement Network) will look at how clinical trials for testing new treatments can be better planned so that the numbers of people who actually take part over a particular time period match the estimates that are made using linked data before the trial starts.To deliver HeRC, the consortium will integrate Northern England's top centres for statistics at Lancaster, public health at Liverpool, computer science at Manchester, and health economics/services research at York. This integration will extend to the NHS, building on a promising model (NHS e-lab) of patient, public and community involvement in the trustworthy reuse of health data for research.