A range of significant research projects are now being undertaken by Digital Health CRC with our university and industry participants – and they aim to deliver big improvements in personalised care; population health; and the analysis of factors impacting on the quality, costs and outcomes of healthcare.

More projects are currently in the final stages of development, and anticipated to commence soon.

“We are immensely excited to see our important research program coming to fruition, with three innovative projects now underway” the CEO of Digital Health CRC, Dr Victor Pantano, said.

“Our research program is one of the main ways that Digital Health CRC – together with our university and industry participants – will add significant value to the health sector, health professionals and health consumers, not only in Australia but across the globe.”

“Through our unique Industry-PhD model, we will also be contributing to the development of the future digital health workforce, as many of our research projects will see PhD students embedded in digital health companies while undertaking their research.”

“We look forward to working with our participants to deliver innovative research outcomes in the digital health space during the life of our CRC.”

A summary of the first three research projects is below.



 

Project 1:
Devising algorithms for a personalised digital community healthcare model

 
Digital Health CRC Flagship Program under which project falls
Changing health trajectories in chronic disease

Research participant
Flinders University

Research Lead
Niranjan Bidargaddi, Associate Professor of Personal Health Informatics at the College of Medicine and Public Health

Industry participant
goAct

Industry Lead
John N. Fouyaxis, Director and Chief Technology Officer

More information: David Tomlins – [email protected] / 02 8088 4222

Project description

This project will develop innovative algorithms to assist improved decision-making and personalised care by healthcare professionals in the community and primary care sector. The research activities will be focused on the AISquared and MINDtick platforms that are currently deployed independently in community mental health services.

The AISquared platform brings utility and adds real-world value to electronic health record (EHR) data from the Australian Government’s My Health Record initiative. The platform applies algorithms to patients’ EHR data consolidated in My Health Record to help community healthcare professionals anticipate who might be at risk of relapse ahead of time.

The MindTick platform facilitates continuous health assessments during individuals’ day-to-day lives, and delivers in-the-moment interventions in a personalised manner. Since individuals have their phone with them most of the time, they can be prompted to complete an assessment or be persuaded to engage in a particular intervention at virtually any time.

This project will create new tools by harnessing the data in MINDtick and AISquared, devising algorithms that lead to improved decision support and early intervention opportunities, and integrating these tools within existing programs to enable a personalised digital community healthcare model.

In community health clinic settings, these tools will guide case managers to better manage caseloads, prioritise patients for discharge and incorporate additional insights on patients’ health and behaviours outside the clinic, in order to further personalise decisions and monitor patient health trajectories and outcomes.



 

Project 2:
Interpreting health information and low value care

 
Digital Health CRC Flagship Program under which project falls
Transparency of data to optimize clinical practice and referral

Research participant
Federation University

Research Lead
Manzur Murshed, Professor and Research Director at the Centre for Multimedia Computing, Communications, and Artificial Intelligence Research (MCCAIR)

Academic Mentor
Fergal Grace, Professor of Clinical Exercise Science at the School of Health Science & Psychology

Industry participant
Lorica Health

Industry Lead
Daniel Cooper, Head of Consulting and Research

More information: David Tomlins – [email protected] / 02 8088 4222

Project description

Risk adjustment is a common issue among medical providers, who are cautious in supporting any initiative regarding transparency and information sharing. Risk adjustment refers to the use of patient and provider level information to explain variation in healthcare spending, resource utilisation and health outcomes over a fixed interval of time.

Medical providers argue that factors influencing the complexity of a procedure – for example, the age and obesity of a patient – must be considered when analysing such variation in order to form an accurate basis for comparison. Patient factors are a significant driver of cost and resource utilisation.

This project will review existing public models of risk adjustment and recommend techniques, approaches and communication frameworks suitable for public and semi-public (ie. via intermediaries) transparency and information sharing purposes.

It will identify the most robust statistical and data science methods for addressing challenges of comparing clinicians and interpreting healthcare information with respect of quality, cost and outcomes.



 

Project 3:
Spatial management of health risk – applying geospatial technology for risk visualisation, hotspot identification, and analysis of geographic variation

 
Digital Health CRC Flagship Program under which project falls
Changing health trajectories in chronic disease

Research participant
University of Canberra (Health Research Institute)

Research lead
Mark Daniel, PhD, MSc, Professor of Epidemiology

Industry participant
Health Management Systems (HMS)

Industry lead
Donna Price (Vice President)

More information: David Tomlins – [email protected] / 02 8088 4222

Project description

Where people live and where they access health services play a key role in understanding patterns of healthcare utilisation as well as health itself. Both healthcare management organisations and funders of health services would benefit greatly from having geospatial technologies to assist them in the allocation of scarce resources and in planning processes. Yet, despite the large amount of research dedicated to geospatial analysis in health, stakeholders rarely have access to more than a report or a set of static maps, usually not up-to-date, at crude levels of scale with low resolution.

This project will develop a comprehensive, interactive, real-time Health Atlas that enables the better visualisation of spatially-based population data – and, importantly, improved risk stratification using built, physical and social environmental data together with patient-level information.

The Health Atlas will enable and support innovations in the spatial targeting and evaluation of personalised healthcare interventions, predicated on spatial knowledge of the environmental contexts of healthcare clients and their characteristics.

It will provide a set of social, built and physical environmental variables that can be attached to Medicaid (USA) claims data, and will also enable map flows of health consumers – relating where they live to where they access health services, and identifying important differences between potential and realised access to care.

The project will focus primarily on chronic diseases associated with lifestyle risk factors (eg., Type 2 diabetes, cardiovascular disease, overweight and obesity, and lifestyle-related cancers).

Using the Health Atlas, Medicaid agencies will be able to visualise data about their customers and also answer specific questions such as “Where is the largest gap between the demand and supply of mental health services for this subset of the population?” or “How much of the geographic variation in this service utilisation or health variable is explained by the variation in these other variables?”

Examples of these variables include the accessibility (distance) and availability (density) of primary care centres, clinics and hospitals, public open spaces and parks, healthful and unhealthful food outlets, and exercise facilities; as well as other factors like dwelling and population density, housing mix, land use, commercial density, public transportation, walkability and climatic conditions.