Exploring "precision medicine" approaches to child and adolescent mental health: predicting treatment outcome and getting to big data
There is a call for precision medicine whereby child mental health interventions are tailored to meet the specific needs of individual young people. Evidence from other contexts suggests that precision medicine has benefits for effective treatment outcomes and efficient resource use. However, there is a lack of evidence in child mental health about which characteristics of a young person are associated with treatment outcome and resource use - crucial to underpin any precision medicine model. The aim of this research is to address this vital gap and thereby expand the use of data resources for mental health research while at the same time further developing the skills base in this complex field.
MQ are supporting this work, through which UCL and CORC are linking data about young people accessing child mental health services from the Mental Health Services Data Set (shared by NHS Digital) to data from the CORC dataset. Anonymity must be maintained throughout and we are linking the datasets using a probabilistic method, working with variables such as gender, care contact date, and organisation/team details. We will draw on this data to explore associations between case-mix characteristics and effective treatment outcomes and efficient resource use.
The project will then work with young people, carers and therapists on the best ways of using this type of information in clinical discussions with young people and families. We will be reaching out to our CORC network to contribute to this phase, so please watch this space! For more information in the interim, please contact us at corc@annafreud.org.