Development of a novel model to integrate multimorbidity in fracture risk assessment

Clinical conditions such as osteoporosis are currently managed using a “single disease” approach. However, population ageing will lead to a sharp increase in the prevalence of multiple chronic conditions, leading to complex chronic conditions associations. Limited knowledge about interactions and associations between common chronic conditions impede optimal patient management.

Our team has demonstrated that chronic conditions present at the time of fracture cluster naturally in 4 or 5 specific groups for women and men. are able to capture individuals with more advanced stages of health conditions and who experience a significantly higher risk of death.

In this research project, our team will develop a novel electronic risk assessment tool to help clinicians managed complex patients with fracture and high morbidity burden. This research project will use advanced biostatistical methodology as well as artificial intelligence (ie machine learning) using a large and complex cohort based on linkage of multiple administrative databases.

This research project will be suitable for a graduate of data science, biostatistics, mathematics and statistics, epidemiology, bioinformatics.

For additional information please also visit the lab website https://www.garvan.org.au/research/labs/clinical-studies-and-epidemiology

How to Apply

Express your interest in this project by emailing Professor Jacqueline Center at j.center@garvan.org.au. Include a copy of your CV and your academic transcript(s).