Electronic Health Record Epidemiology & Risk Stratification
Electronic health records collected as part of standard clinical care, national biobanks and targeted cohorts contain detailed information about a patient’s clinical history. Analysis of these on a large-scale enables us to identify the individuals with the highest risk of disease, or those likely to respond positively to specific treatments. This research requires a range of expertise such as the ability to ethically and securely collect, store and curate the data, link it with other datasets and analyse it using advanced statistical or machine learning methods. This needs to be combined with on-the-ground clinical knowledge, both in primary and secondary care, to direct the research questions and to evaluate how best to implement the findings for patient benefit.
Examples of the unique resources Oxford cancer researchers support include very large cohort datasets (e.g. The Million Women Study, Our Future Health), major biobanks (UK Biobank and China Kadoorie) and groups drawing together electronic health data (NCIMI, QResearch, Oxford-Royal College of General Practitioners Research & Surveillance Centre, CORECT-R, NIHR Health Informatics Collaborative, Clinical Trial Service Unit & Cancer Epidemiology Unit, the Turing Institute, Health Data Research UK and NHS Digital.)