Supporting the digital transformation of healthcare, psycho-oncology, care interventions and health communications.
Led by Professor Nilmini Wickramasinghe, our digital health program draws upon human-centred health initiatives as well as partnerships with government and industry to provide insight into current management techniques for health data.
We investigate ways of supporting and promoting health initiatives that include:
supportive care interventions
other aspects of health communication and promotion, including data management of individual health care records.
To gain insights into current management techniques and existing gaps in health data management, we partner with the following government and industry bodies:
federal, state and local government
international development agencies
governments in target partner countries
In collaboration with the Baker Heart and Diabetes Institute, we’re applying established methods from astrophysics to the early detection of heart disease through two projects:
detection of early aortic valve disease
quantification of cardiac calcification.
Early identification or prediction of the likely onset of cardiovascular disease, diabetes and obesity is crucial to improving public health. Our AstroMedical Innovation project translates data-driven processes and techniques from astronomy and astrophysics into the domain of medical imaging and diagnosis. The aim is to develop faster, more robust and more powerful diagnostic tools.
We’re working with Epworth HealthCare to explore opportunities to design a blockchain solution to support hospital billing processes. Blockchain is a revolutionary technology that has changed the way data is transferred, managed and shared with different parties, and its impressive success in other sectors has left the healthcare industry wondering whether it can be effectively applied to key activities in their sector.
Read more about Swinburne’s research into blockchain technology.
We’re undertaking a longitudinal study to assess the benefits of a bespoke diabetes mobile health solution (DiaMonD) and how it can:
improve self-empowerment of various populations to enable better management of this chronic condition
enable a high quality of life
lead to higher clinician and patient satisfaction.
Pilot studies have been carried out in Australia, Canada, China, Germany and the United States, and funding for aspects of this project has been received from ATN-DAAD, DAAD-UA, Epworth Medical Foundation, Harbin Institute of Technology and a Schoeller Senior Research Fellowship.
In partnership with Epworth HealthCare, we’ve secured seed funding to develop the concept of a digital twin in the domain of uterine cancer, in an attempt to deliver high patient value, a better patient experience and superior clinical outcomes. A digital twin is a digital replica or model of a process, product or service, providing a link between the physical and digital world that can help prevent problems and downtime, develop new opportunities and plan for the future. Given the benefits discovered using digital twins in the manufacturing sphere, we’re further exploring the benefits of applying and possibly modifying the concept for the healthcare industry.
Read more about other Swinburne research on digital twins.
In partnership with Epworth HealthCare and funded by an Epworth Research Institute seed grant, we’re developing best practice guidelines for the design, development and deployment of digital health solutions in the healthcare environment. A variety of health information systems, such as electronic medical record systems and point of care solutions, are currently being implemented into healthcare organisations. What remains unclear is:
what is their return on investment?
how do we ensure the expected benefits are realised?
how do we ensure high patient and clinical satisfaction alongside good technical and clinical outcomes?
Our aim with these guidelines is to help deliver high-value and high-quality patient-centred care.
Further information on this project can also be found on the Personalised Health Care program page.
In partnership with Epworth HealthCare and funded by an Epworth Research Institute seed grant, we’re developing an Australian health data model that can make it possible to accurately predict patients with a high likelihood of readmission at the time of their initial admission, as well as to mitigate likely risks during their patient journey. Reducing unplanned readmissions and mitigating risks in acute care contexts is important for providing high quality care and a superior patient experience.