Negative aspects of a young person’s life can lead to poor mental health. However, services are stretched so often intervene late, leaving young people to suffer with longer lasting or more severe problems.
It is possible to spot patterns showing where professional help is needed early. However, this is difficult as the information needed is secured in different places – for example, across health, education and social care records – and falls under the remit of different UK Research and Innovation research councils (such as the Medical Research Council or the Economic and Social Research Council).
The main problems are:
- Predictive models aren’t accurate enough: there are difficulties linking different types of data together, potentially resulting in many important risk or resilience factors being missed.
- Models built in one place may not be effective in others: we need a way to securely analyse data from different places.
- There is no agreement on how to make sure data are managed safely, fairly and transparently.
To solve these problems, this research will:
- Combine two new technologies to demonstrate it is possible to analyse data across trusted research environments in different places and preserve individual privacy.
- Consult with patients, the public, organisations contributing data and legal/ethics experts to agree the best way to oversee data use, ensuring it’s managed safely and fairly.
Principal investigator: Dr Anna Moore, University of Cambridge
Project partners: University of Cambridge, AIMES, InterMine, Bitfount, Kaleidoscope, Eastern AHSN, University of Essex, University of Birmingham, Cambridgeshire County Council, and the Anna Freud National Centre for Children and Families
Funded amount: £342,708