Active Public Health & Healthcare Computing & AI

Infrastructure and Services - Trust and Transparency

In plain English

AI plain-English summary

HDR UK is asking patients and the public to help shape how their health data is used for research, rather than simply assuming they approve. This matters because medical research increasingly relies on large datasets—GP records, hospital notes, and other patient information—to find new treatments and improve care. But if people do not trust how their data is handled, they may opt out, starving researchers of the information they need. The gap is not technical but social: researchers have built the infrastructure, but have not yet fully embedded public oversight into how it runs. If this programme succeeds, it will create a system where patients help decide what questions are asked and how data is governed, not just as a one-off consultation but as an ongoing part of how HDR UK operates. The result could be research that answers questions the public actually cares about, while building the confidence needed for people to allow their data to be used. That trust is the foundation for every future study that relies on patient data—from drug trials to disease surveillance.

View original technical description
HDR UK’s mission, to enable research that improves people’s lives, needs patients and the public to have confidence that their data is being used in safe and trustworthy ways. This programme enables the public to shape HDR UK’s work, demonstrating accountability, transparency and showing that research answers questions that are important to patients and the public. By working with the public to understand their perspective on and shape research programmes HDR UK can build confidence in the way patient data is being used for research, ensuring the new tools and infrastructure developed is founded on public trust. This can bring together the needs of research and patients, in a way that benefits everyone.

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Researchers

Andy Boyd (Principal Investigator)Cassie Smith (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.