Active Public Health & Healthcare Mental Health

Infrastructure and Services - Useable Data

In plain English

AI plain-English summary

The UK holds vast amounts of health data, but much of it is stored in incompatible formats, making it nearly impossible to combine and analyse at scale. This programme tackles a fundamental infrastructure problem: health data is collected by hospitals, GP surgeries, clinical trials, and research studies, often using different systems and standards. A patient’s hospital records, for example, might not link easily to their primary care data or to a clinical trial they participated in. This fragmentation prevents researchers from working across large populations or combining datasets to spot patterns that single studies cannot reveal. If successful, the programme will create standardised tools and approaches that allow different types of health data to be brought together seamlessly. This would let researchers run larger, more powerful studies—for instance, testing new drugs or treatments across broader patient groups in clinical trials. The impact is largely invisible to the public: better data infrastructure means faster, more reliable health research without anyone having to change how they interact with the NHS. It is an engineering and standards project, not a discovery science one, but it underpins nearly every major advance in modern medicine.

View original technical description
The UK is home to a wide variety of different types of data, often with similar data held in different forms which makes bringing them together difficult. This programme will develop tools and approaches to bring that data together in standardised ways so that it is easier to use in health-related research, allowing researchers to work at larger scale and breadth to unlock new opportunities to improve health and wellbeing in the UK, for example through improving how new drugs and other approaches are tested through clinical trials.

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Researchers

Emily Jefferson (Principal Investigator)Harry Hemingway (Principal Investigator)Marion Mafham (Principal Investigator)Matthew Sydes (Principal Investigator)Monica Jones (Principal Investigator)

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Original classification

Intramural

Plain English summaries and category classifications on this site are generated by AI and may not perfectly reflect the original research.