The Health e-Research Centre (HeRC) will stitch together millions of under-used NHS and health science records from across Northern England to reveal hidden patterns in disease and treatment. The problem is that data generated during routine healthcare—GP visits, hospital admissions, prescriptions—is messy, scattered across incompatible databases, and often locked away from researchers. Current methods cannot easily clean, link, and analyse these fragmented records, so valuable insights into what actually works for patients are lost. HeRC will develop new software and statistical tools to make these datasets usable, while also training a new generation of health informaticians to apply them. If successful, the centre will allow researchers to answer questions that are currently intractable: whether a heart attack patient missed a prevention opportunity somewhere in the system, what the cancer risk is from common diabetes drugs, or how to identify patients with distinct forms of asthma who need different treatments. The work will also build a secure research environment where datasets are discoverable and methods are embedded, making large-scale health data analysis faster, more accurate, and more routine for the NHS.
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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 Page 3 of 19 Date Saved: 28/02/2012 12:49:22 Date Printed: 28/02/2012 12:56:18 Technical Summary Academic Beneficiaries Describe who will benefit from the research 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,
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