HDR UK National Text Analytics Implementation Project
We will apply NLP methods to generate a more comprehensive picture of patients and their health.
We will establish a national, natural language processing (NLP) research community that will address the complexity of clinical text through the development of shared tools and standards, supporting joint working across industry, academia, and the NHS. The community will be open and inclusive. and develop capabilities for UK-wide NLP research at scale. The community will share exemplar projects, material and datasets for training and implementation, and integrate with other health data analytics.
Building on existing successful partner-led programmes, and drawing the wider community together, this project will enable a major shift in the UK’s ability for research-ready, actionable, real-time and large-scale EHRs. Shared tools will be made available across the NHS, creating richer, more useful clinical information to improve healthcare. The integration of NLP derived phenotypes (digital descriptions of health characteristics) from EHRs with other rich records (e.g. educational and social information) and other modalities including imaging, mobile health and genomics will help generate a more complete picture of the patient and their health. Example projects will focus on areas of stroke, lung cancer and serious mental illness.
Better use of unstructured text will help streamline matching of patients to clinical trials and stratification of patients for disease classification, outcome prediction, patient trajectories across the life-course, adverse drug reactions, and identify drug-repurposing opportunities.
Research team (in UoE)
Catherine Sudlow, Honghan Wu, Beatrice Alex, William Whiteley, Grant Mair, Andreas Grivas, Hang Dong, etc.
Health Data Research UK