Opportunity: address challenges in recognising and managing deterioration in a timely manner in residential aged care facilities through digital innovation and evidence-based care coordination.
Opportunity: Implementation of Artificial Intelligence (AI) technologies in health care services is challenging with an absence of best-practice guidance, presenting an urgent need to bring together stakeholders who have a vested interest in the opportunities to establish a coherent, collaborative, and sustainable national approach supporting the implementation of AI in the Australian health system.
Opportunity: Led by La Trobe University with support from the DHCRC Synthetic Data (SynD) Community of Practice and international experts from Swansea University and the Secure Anonymised Information Linkage (SAIL) Databank, this series addresses critical barriers in health data access, privacy, and interoperability.
Opportunity: address an important implementation question: under what consumer, clinical, and organisational conditions in Australian healthcare will patients and clinicians consider AI-supported medical management acceptable, trustworthy and useful?
Opportunity: develop a proof-of-concept simulation focused on handling technical difficulties during a telehealth consultation to help learners practice troubleshooting, communication, and problem-solving skills in a realistic virtual environment.
Opportunity: AI-driven clinical decision support tools like the Ainsoff Deterioration Index (ADI) have the potential to improve patient outcomes, but robust evaluation frameworks are lacking. This project aimed to evaluate the ADI’s performance and clinical impact, supporting evidence-based AI across Australian healthcare.
Opportunity: This was a feasibility project that explored leveraging large language models (LLMs) to create a dashboard prototype for identifying and analysing emerging medication shortage-related trends in social media.
Opportunity: Learning from the PreHaRM experience, identifying points of convergence and disconnect, between policy and practice is critical for reducing implementation delays, and ensuring that AI technologies are introduced in ways that genuinely support clinical staff and improve patient outcomes.
Opportunity: This project explored how health consumers (e.g., patients, carers, public) perceive the use of Artificial Intelligence (AI) in digital health, with a focus on AI-generated summarisation of health information. As AI tools become increasingly integrated into healthcare systems, understanding how they are received by patients, carers, and the public is critical to ensure safe, ethical, and effective adoption in Australia.
Opportunity: translate vascular research, using retinal images and videos as a window into pressure-related physiological changes, into a practical platform that could assist clinicians with earlier and less invasive screening and triage for patients who may require further investigation for elevated intracranial pressure (ICP).
Opportunity: This project will develop an online tool to help classify different types of Artificial Intelligence (AI) solutions used in Australian healthcare. The online tool will adapt the Organisation for Economic Cooperation and Development (OECD) AI Classification Framework to the Australian context, reflecting recent government policies, including proposed mandatory guardrails for AI across the Australian economy.
Opportunity: modernise and further develop an existing online platform tailored for health workers for diabetes education as a fit-for-purpose solution for workforce eLearning in clinical environments.
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