Integrated Community Care For People With Complex Multi-morbidities
Funder
National Health and Medical Research Council
Funding Amount
$2,500,000.00
Summary
The focus of the Centre of Research Excellence (CRE) for Integrated Community Care for People with Complex Multi-morbidities (CRE-CoM) will be on reducing hospitalisation through innovative, high quality, collaborative research of home and community-based service systems, including the development of digital and virtual modes of community-based service delivery.
Evidence Innovation: Transforming The Efficiency Of Systematic Review
Funder
National Health and Medical Research Council
Funding Amount
$928,417.00
Summary
Australia invests considerable resources developing reliable summaries of research evidence to understand the benefits and risks of drugs and health programs. We will use information technologies and ‘crowdsourcing’ to improve the production of evidence summaries, evaluate this approach in a randomised study, and facilitate implementation throughout Australia. This will improve the translation of research into health practice and policy, reducing research waste and improving health outcomes.
Lipidomics of vision. Presbyopia and cataract are the major causes of visual impairment worldwide. Nevertheless, our understanding of lens ageing at both a cellular and molecular level is limited. This project will gain new insight into the effect of age on lens membrane lipids and their role in the development of presbyopia and cataract.
Application Of Machine Learning Techniques To Disease Surveillance To Identify Risk Groups For Blood Borne Viruses And Sexually Transmissible Infections
Funder
National Health and Medical Research Council
Funding Amount
$76,365.00
Summary
Electronic medical records from general practice are used to provide clinically detailed disease surveillance data to inform public health decisions. Risk factor information is not systematically recorded making it difficult to identify risk groups using these data. This PhD will improve surveillance by applying new data science methods to de-identified electronic medical records from general practice to better identify risk groups for blood borne viruses and sexually transmissible infections.