Publications
Peninsula Health Retrospective Evaluation
A Retrospective Evaluation of a Multidisciplinary Management Strategy Implemented to Optimise Outpatient Care, Hospitalisation Rates and Clinical Outcomes in a Single Centre Cohort of COVID-19 Positive Pregnant Women in Australia during the Omicron BA.1 surge
Alfred Health COVID Positive Pathway
Summary of the multidisciplinary, collaborative and integrated model of care for supporting covid positive patients:
- Virtual care (COVID Monitor platform) emerged as essential to scalability.
- Significant opportunities for hospital avoidance were observed, along with minimal adverse outcomes and a high level of acceptability for patients, carers and staff.
- The pathway was successfully decentralised and integrated within community health.
Lancet publication showcasing the clinical benefits from using COVID Monitor
A Safe and Successful Digital Self-Assessment Tool for Outpatients With Proven and Suspected COVID-19
JMRI publication The Rapid Development of Virtual Care Tools in Response to COVID-19
The rapid pivot to telemedicine and virtual care provided immediate and longer term benefits
ScienceDirect publication showcasing the clinical benefits from using COVID Trace
Staff to staff transmission as a driver of healthcare worker infections with COVID-19
JMIR Application of Natural Language Processing for Quality Assurance
Machine Learning increases efficiency and timeliness of National Procedural Clinical Standards KPI reporting
2021 ResearchFest Infectious Diseases and Medical Imaging posters
We investigated whether COVIDCare, a patient-reported telehealth symptom monitoring system, was successful at delivering safe monitoring and care for these patients leading to decreased hospital presentations.
Case Studies & Articles
“Substantial” hospital avoidance with Alfred Health’s COVID-19 community pathway
The model of care established and implemented by Alfred Health provides a template for the expansion of home-based care for future pandemics and as a way to better treat other chronic conditions at home
Improving Clinical and Patient Insights with Data and AI
Hear from Associate Professor Natalie Yang, Austin Health’s Medical Director of Radiology, about their use of Radiology Hub to improve radiology reporting quality and efficiencies, assisted by medical natural language processing
Unleashing the Value of Health Data
Together with Databricks hear about how Austin Health is using data analytics + AI to improve clinical care and reduce costs
Microsoft Case Study: Application of AI for COVID-19 Patients
The application of AI for helping to assess lung function of COVID-19 patients through use of a Virtual Roth Score
Databricks Case Study: COVID-19 Virtual Care
Austin Health employing COVID Monitor to track progress of patients in their homes and arrange for urgent medical care
Our approach to rapid delivery for Healthcare
“The results are quite incredible - we had a roadmap that was aimed at enabling a more agile approach of developing all sorts of different features and capabilities using platforms such as Azure,” Alan Pritchard - Austin Health Director of EMR and ICT services
The shift to virtual care in response to COVID-19
PWC publication on the future of virtual care in Australia, noting reference to our digital first approach to monitor, detect and escalate clinical deterioration while they convalesce at home.
A deeper understanding of AI is key to building a better future ...
AI in healthcare is an emerging field, for us focused on how to help support clinical decisions by providing more information about the patient's current situation.
COVID-19 QR Check-in App
Our partnership with ACT Health in the delivery of a standardised COVID-19 Check-in Application for Australia
Databricks APAC Rising Star of the Year Award 2021
Azure Databricks has been the cornerstone of the AI and machine learning solutions we’ve delivered across retail and healthcare
Men's Health & Fauci
Who said bobblehead dolls can't make the news? An interview with Men's Health magazine and Austin Health