Understanding complexity in youth mental health using integrated population-level data

This PhD project is supported by a National Health and Medical Research Council (NHMRC) Partnership grant in collaboration with Orygen (Centre for Youth Mental Health, The University of Melbourne), the Victorian Department of Health, Ambulance Victoria and headspace National. The collaboration brings together key researchers in the areas of youth mental health, health economics, and biostatistics to generate new knowledge that will lead to a better understanding of health service use and outcomes in youth mental health. The PhD project supervisors are from the health services and outcomes research team at Orygen. The team is conducting a range of research programs covering topics such as outcome measurement, novel treatments and service models, measuring quality of life and health utility, examining service trajectories using data linkage, and economic modelling. The team has statistical expertise across a range of areas including secondary and linked data analysis, longitudinal surveys, disease modelling, and application of novel statistical and machine learning methods in health science. The supervisory team include Prof Sue Cotton, Dr Caroline Gao (Orygen), and Dr Jana Menssink (Orygen). The project aims to use machine learning and data linkage of administrative and health datasets in order to: (i) Better understand youth help-seeking, resource use and productivity implications; (ii) identify risk factors for poor outcome; and (iii) identify spatial and temporal risk factors that are associated with heavy acute mental health service use in geospatial areas. The PhD project will be focusing on using state-of-art machine learning techniques to explore the complexity and heterogeneity in youth mental health using large scale health service utilisation data.