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Case studies

There is a wide range of ways that patient data can be used to provide better care and improve health. Explore the case studies to learn more. Please let us know if you have good examples to share.

  • Using data to identify and approach people for research: a public dialogue in Wales

    Welsh Government commissioned the National Centre for Social Research (NATCEN) to conduct a deliberative public dialogue exercise to explore views on the use of health data for identifying and approaching individuals about research studies that may be relevant to them, without prior consent. The exercise involved 35 participants in Wales, engaging with researchers across 4 sessions (3 online, 1 in-person) including a full day deliberation session. The report of the exercise concluded that recruitment processes reliant on un-consented patient data to identify and approach people for research studies could be deemed to satisfy a broad constituency within the dialogue, provided conditions were met. These conditions were broadly grouped into categories including: effective oversight, focus on quality of research and equality of access to studies; demonstrating public benefit; effective public consultation on plans for such services; and transparency of processes and uses.

  • How is health data used in the current measles outbreak?

    This case study explores how the UK Health Security Agency uses health data to track the spread of measles and supports the health service to respond

  • Archived case studies

    Find out how to access our old case studies

  • Predicting A&E admissions to improve preparedness

    Developing an AI tool to help NHS Trusts better predict demand for A&E so that it can be better prepared

  • Developing chatbots to address ethnic disparities in STIs

    Designing and piloting an AI chatbot for supporting people with STIs/HIV from ethnic minority backgrounds

  • Identifying long stay patients in hospital using AI

    Preventing people staying too long in hospital unnecessarily by modelling and calculating risk scores

  • Public views about AI in healthcare

    Involving the public in understanding the barriers and facilitators to implementing AI in healthcare

  • A mini citizens’ jury to debate data

    Delivering a verdict on public perceptions of the use of data in healthcare

  • OneLondon Citizens’ Summit

    Giving Londoners the opportunity to share their thoughts on the complex issues around health data

  • Preparedness to prevent future pandemics

    Data surveillance to identify disease cases that pose a significant risk to public health

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