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Data, artificial intelligence, and other health technologies

Data, artificial intelligence, and other health technologies

This theme focuses on how data, and technologies like artificial intelligence, will change our health futures.

Data is now at the centre of human lives. Data allow humans to visualise, measure, monitor, intervene, predict, plan, communicate and much more. We all generate masses of data every day—whether we know it or not—and these data are valuable to many different interests.

Health services have always involved of some kind—ranging from ancient tools to modern imaging machines—but healthcare artificial intelligence, built on healthcare data, promises a new and transformative kind of health technology.

ACHEEV is actively working on the ethical, legal and social implications of using artificial intelligence (AI) in health services. We are asking how AI should be used in health and in other industries relevant to health, such as agriculture.

Using innovative social and deliberative research methods, and ethics and social science analysis, we generate new frameworks and recommendations that reflect what matters to patients and communities, to inform the use of data, AI and other technologies. Our goal is to produce new ways of thinking that will reduce harm, increase benefit and promote justice.

Ongoing projects

UOW researchers

Research assistants

  • Diana Popic
  • Lucy Carolan

Project description

The Newborn Bloodspot Screening (NBS) program is one the most effective and trusted population screening services in Australia. Almost all Australian babies – about 99% – are tested in the program. Australia is now considering using genomic tests in the NBS program to improve outcomes for babies and their families. But, as with any technological change, we must first assess the ethical, legal, and social implications, and in doing so, consider the views of all stakeholders.

Our team will run a community jury and ask Australians for their views on using genomics in the NBS program. The community jury will draft recommendations relevant to policymakers deciding on what the NBS program will look like in the future.

Our research is one part of a larger research project that aims to understand the perspectives of all stakeholders, build a reference economic model for newborn screening, and develop a health technology assessment criteria. 

Website

gEnomics4newborns: Research to integrate ethics and equity with effectiveness and economics for genomics in newborn screening

Funding

The gEnomics4newborns research project is part of Medical Research Future Fund grant awarded in 2022.

UOW researchers

External collaborators

Research assistants

  • Lucy Carolan
  • Diana Popic

Project description

Artificial intelligence (AI) could improve the accuracy and cost-effectiveness of mammograms. Led by Dr Luke Marinovich (University of Sydney), this project will assess the use of AI in breast cancer screening, and its acceptability to the community. Breast cancer screening currently involves radiologists reading mammograms to identify abnormal tissue for further assessment. However, up to 35% of cancers are missed at this screening phase. AI is a rapidly evolving form of technology that uses computer programs to read mammograms, potentially improving the accuracy of the test and reducing costs for our health system. This project will provide information on the effectiveness and usability of AI in breast cancer screening. 

Our research team is interested to know whether women will be comfortable with AI being used to assess their mammograms. To investigate this question, ACHEEV will run multiple online dialogue groups, and prepare participants for engagement in dialogue groups by informing them of relevant topics.

Information videos presented to participants can be found here:

Our comprehensive study will also provide an economic evaluation of the technology, to compare the costs of implementing AI against it benefits.

Website

Artificial Intelligence to Improve Breast Cancer Screening

Funding

National Breast Cancer Foundation Investigator-Initiated Research Scheme. 2020-2022, $822,561.28

Outcomes

UOW researchers

External collaborators

Research assistants

  • Belinda Fabrianesi

Project description

There is a strong demand in Australia for access to general practice data for a range of important health research. Some population-based general practice data are available through organisations such as NPS MedicineWise and Primary Health Networks, as well as via large cohort studies. However, general practice data are not systematically linked to population-based linked health data.

Anecdotally, there is some evidence that general practice data custodians and users may not understand the legal environment in which they are operating and the risks and harms that may result from inappropriate data/research governance processes. Nor are they always familiar with various codes of conduct and standards. There is also little information on Australian community attitudes to use of general practice data for research purposes. Advice on what is and is not appropriate for research use of primary care data would be particularly valuable in this context.

This project will investigate the facilitators, barriers and challenges to accessing general practice data for research as well as community attitudes to the use of this data for research. The outcome of the project will be a report on ‘Ethics, legal and social implications of the use of general practice data in research’ which will include suggestions on law or policy reform, potential regulatory changes and future research.

Project partners

Funding

Project completed – awaiting papers to be published.

UOW researchers

External collaborators

Research assistants

  • Belinda Fabrianesi
  • Lucy Carolan

Project description

General practice data are an important resource for researchers, policy makers and planners. However, the potential for use of these data for research is still largely unrealised. Although there is broad public support for the secondary use of health data, the public and some practitioners remain concerned about sharing patients’ health data outside the clinical encounter. These concerns are amplified by the complex social and relational nature of general practice. If we are to make better use of general practice data, we must both build public understanding of how the data are used and address concerns about privacy and misuse.

In this project, we will use co-design and deliberative approaches, bringing together publics, GPs, policy makers and regulators, to design a best practice framework for the use of general practice data for research purposes. The outcome will be policies, practices and regulatory guidance to enhance the social, ethical and legal acceptability of the use of general practice data for research.

Project partners

Funding

UOW researchers

External collaborators

Project description

This study supports the early diagnosis and treatment of ageing-related conditions among older Australians by enabling older people to provide evidence-informed views on the screening of a sub-set of these conditions (i.e. cardiovascular disease [CVD], diabetes, dementia and frailty) in order to facilitate the translation of these practices into health policy. Phase 1 of our project will use deliberative processes (specifically, citizens’ juries) to engage older people in the following question: ‘Under what circumstances should health service providers perform screening of older people for condition X within the community?’ We will administer four juries, with each addressing a different ageing-related condition. This phase of our study addresses a critical research gap in the field, as there have been few attempts to conduct juries with older people about dementia screening, and none related to screening for CVD, diabetes or frailty. Aside from supporting the participation of older consumers in general (aged 50+ years), our study is innovative in that we will purposively recruit participants to maximise diversity across vulnerable and under-represented groups, including: Culturally and Linguistically Diverse (CALD) individuals, people identifying as gender and/or sexually diverse (GSD), persons living in rural/remote regions and areas of high socio-economic disadvantage, and persons living with frailty and/or early dementia and their proxies. Phase 2 of the project will translate key findings from the consumer juries into recommendations for consideration within two policy roundtables. Membership of these roundtables will be drawn from key professional groups with an interest in ageing-related conditions (general practitioners [GPs], practice nurses, geriatricians, allied health providers and pharmaceutical, health insurance and aged care industry representatives). During Phase 3, we will convene a small working group of diverse older Australians to co-design a set of knowledge translation (KT) resources that will summarise overall findings and recommendations from the project and package these for effective dissemination.

Project partners

Funding

  • NHMRC MRFF Dementia, Ageing and Aged Care Mission 2021, $584,430

Researchers

Research assistance

Project description

Australian agriculture is currently facing the intersecting challenges of soil degradation, water depletion, biodiversity loss, climate change, and demographic changes. Simultaneously, research in agricultural robotics and artificial intelligence (AI) is being positioned to deliver precision agriculture (i.e. precise amounts of water and fertiliser as per information provided by AIs), in addition to the potential for robotics to carry out weeding, fruit and vegetable picking, food handling and packaging. While there has been considerable research into the technological benefits of AI and robotics, there has been little interrogation of the ethical and social issues which may be generated from this agricultural shift. The aim of this project is to improve understanding of the social and ethical issues raised by the application of AI and robotics in agriculture. The project is a cross-institutional collaboration. It will use a combination of online dialogue groups and citizen’s juries to engage with farmers, members of rural communities and consumer groups to explore and discover the social and ethical issues anticipated by these key stakeholders regarding the incorporation of AI and robotics into agriculture.

Funding

The project has received ARC Discovery Project funding to the total of $630,000AUD.

Timeframe

May 2023 to December 2024

Outcomes

  • Academic benefits generated via new knowledge in philosophy, bioethics, applied ethics, and social studies of sciences.
  • Likely to be central to discussions on the social and ethical implications of AI and robotics in agriculture, being the first to integrate stakeholder opinion with rigorous philosophical analysis.
  • Provide significant social benefits through the facilitation of public deliberation regarding the risks and benefits of AI and robotics in agriculture. This will assist farmers, corporations and governments to develop publicly informed policies which reflect community needs and concerns.
  • Academic papers published in highly regarded refereed journals.

Publications

Sparrow, R., Howard, M., & Degeling, C. (2021). Managing the risks of artificial intelligence in agriculture. NJAS-Impact in Agricultural and Life Sciences, 93(1), 172-196. https://doi.org/10.1080/27685241.2021.2008777

UOW researchers

External collaborators/investigators

Research assistants

  • Lucy Carolan

Project description

This project focuses on the ethical, legal and social dimensions of the use of machine learning systems in  diagnostic and screening tasks. This multi-method project engages with diverse stakeholders to understand, from their perspectives, what is happening and what should happen in diagnostic and screening machine learning technology.

We have interviewed a wide range of stakeholders, held dialogue groups with service users, conducted discrete choice experiments, and ran a national citizens’ jury with members of the public. Data collection is now complete, and we are continuing to work on reports and publications.

Funding

  • NHMRC Ideas Grant 1181960, 2020-2023, $823,476.40

Outcomes

Other outcomes

 

 

PhD projects

PhD candidate

Emma Frost

Supervisors

Research assistants

  • Lucy Carolan

Project description

Artificial intelligence (AI) applications in healthcare are rapidly being developed and implemented. Although these technologies show promise for improving aspects of healthcare, there are concerns that the implementation of AI into healthcare systems may lead to unintended harms. Any harms that come as a result of AI's implementation in healthcare are likely to affect patients and members of the public (publics), making publics important stakeholders in conversations about how AI applications are developed, designed, and implemented. Emma's PhD project explores strategies for, and complexities with, engaging publics in research about AI in healthcare.

Funding 

This project draws from funding from the NHRMC TAWSYN grant, and also uses resources generated from the UOW Global Challenges Grant. Emma is the recipient of a government Research Training Program (RTP) Scholarship.

Outcomes

 

PhD candidate

Rebecca Bosward

Supervisors:

Project description

Precision public health is in its formative years, and its scope and definition are continuously evolving. Precision public health approaches use new and existing technologies, analytics, and linked data from a variety of sources to improve population health outcomes. The use of big data and technologies in precision public health raises significant social and ethical challenges. This has facilitated the need for further research in the areas of ethics, public trust, governance and legislation and trans-disciplinary collaboration. The overarching aims of this research project are to systematically map definitions and concepts of precision public health, to investigate the ethical and social challenges and implications of precision public health and make recommendations for policy and practice.

Funding

  • Australian Government Research Training Program (AGRTP).

Outcomes

 

Completed Projects

Researchers

External collaborators

Project description

AI has been widely used in industries including finance, marketing, communications, human resources and policing. It is now making its way into other sectors including health care and social services. Few researchers have investigated what people think about the adoption of AI. This project employed a novel survey methodology to examine whether Australians support or oppose the adoption of AI in health and social services, and what aspects of AI implementation they think are most important.

Funding

  • 2019-2020 ($49,239), University of Wollongong Global Challenges Project Grant

Outcomes

 

Researchers

Research assistants

  • Belinda Fabrianesi

Project description

Big data is a catchall phrase encompassing the collection, linkage and analysis of very large data sets using automated processes such as machine learning. The use of large, linked health data sets provides a powerful vehicle through which to explore elements of human behaviour, evaluate health services, monitor new drugs and devices and answer valuable research questions. However, the sheer volume of sensitive information that can be linked and attributed to individuals can also lead to discrimination, loss of autonomy, infringements on privacy, reputation damage or embarrassment, identity fraud and commercial misuse of data. These are real concerns prominent in the public consciousness.

The project aims to better understand community attitudes towards private sector access to linked Government administrative health data in the development of new drugs and medical devices. In addition, it will develop citizen guidance on how to move forward to support potential uses of linked Government health administrative data with private industry.

Outcomes

 

Researchers

Project details

Our aim in this project is to increase knowledge about the experiences of users or motorised mobility devices (MMDs), and the everyday meanings of MMDs for users. The project is designed to provide empirical evidence that will be useful in informing planning and policy agendas in transport, disability, health, infrastructure planning, and the types of MMDs designed and sold in the future. This is a multi-stage project: ACHEEV researchers will lead a deliberative engagement with MMD users in relation to a future urban planning project, as a practical experiment in inclusive participatory planning.

Project partners

ATSA

Project website

Let's all move together

Funding

ARC Linkage LP180100913. 2019-2022. $356,000