PROACT

PROACT

Predictive Analytics for Optimised Care in Youth Mental Health

Objectives

To apply advanced data analytics to youth mental health data to (i) predict mental health outcomes, (ii) profile youth mental health needs, and (iii) personalize supports.

Design

The research will be conducted across five work packages

1. Prediction: machine learning strategies will be applied to youth mental health data to predict mental health outcomes, identify patterns in service usage, predict surges and inform service planning
2. Profiling: the needs of young people accessing services will be identified, access and care pathways will be mapped to inform service provision and identify target groups
3. Personalize: the application of machine learning to ecological momentary assessment mental health data will be reviewed to inform the development of personalized supports
4. Proof of Concept: conduct a think aloud study with clinicians using a ML-informed decision support tool to evaluate clinical usability in informing personalized data-driven care
5. Integrate: dissemination and integration of findings within YMH practice and policy.

Expected Outcomes

Develop data-driven approaches to predict mental health outcomes, anticipate changes in service demand, improve workforce planning, and reduce wait times, to ensure timely and effective mental health support for young people. Use advanced data insights to identify young people at risk of disengaging from services, tailor interventions to individual needs, enhance early identification of those at-risk. Utilise findings to actively inform youth mental health policy.

Summary

The PROACT project aims to apply advanced data analytics to youth mental health data to inform data-driven, precision, personalized support. Advanced data analytics, applied to anonymised data can help guide optimal care pathways in order to provide the right care, first time. This project brings together expertise across mental health research, data analytics, lived experience, clinical practise and policy. The project is the result of a partnership between the University of Limerick and Jigsaw: The National Centre for Youth Mental Health. An important outcome of this research project is the opportunity for integrated learning and development across disciplines as mental health research clinicians and policy makers learn from those with expertise in data analytics and vice versa.

Research Team

• Dr Ruth Melia, Associate Professor in Clinical Psychology, University of Limerick
• Dr Jeff Moore, Director of Research, Jigsaw: The National Centre for Youth Mental Health
• Prof Pepijn Van de Ven, Professor of AI and Machine Learning, University of Limerick
• Derek Chambers, General Manager (Policy Implementation) National Mental Health, HSE Access & Integration
• Jack Kirby, Youth Advocate, Jigsaw National Office
• Eva Lenihan, Youth Advocate, Jigsaw National Office

Funding Grant

Health Research Board Secondary Data Analysis Project Award