Centre for Health Informatics | AIHI - Australian Institute of Health Innovation

Centre for Health Informatics | AIHI - Australian Institute of Health Innovation

About the Centre

The Centre for Health Informatics (CHI) is Australia's largest academic research group in digital health. CHI is one of three research centres within the Australian Institute of Health Innovation (AIHI). CHI is also the lead agency of the NHMRC Centre for Research Excellence in eHealth (CRE).

The Centre for Health Informatic's work is internationally recognised for its ground-breaking contributions in the development of tools to support systematic reviews, developing evaluation methodologies for IT safety, analysis of social network data, consumer eHealth and clinical analytics.

We are particularly interested in collaborations in the application of artificial intelligence (AI) in medicine and healthcare. Student projects are available on request.

Our principal aim is to map the complex organisational systems that shape today’s health system and to design rigorous, system-wide computational systems that provide a sustainable platform for future health systems, locally and internationally.

The Centre for Health Informatics has worked with major healthcare providers, research institutions, universities and governments, including the Australian Patient Safety Foundation, the Commission for Quality and Safety in Healthcare, the Australian Digital Health Agency, the US National Toxicology Program and Therapeutic Guidelines Limited. The Centre also has partnerships and collaborations internationally and actively pursues relationships with leaders in their fields.

Our industry partnerships have resulted in two spinoff companies and we actively work with industry to deliver innovative and targeted solutions based on research evidence. Our students have gone on to have promising careers and leadership roles as researchers, practitioners and entrepreneurs.

Driving change in healthcare

The Centre for Health Informatics drives change in healthcare and biomedicine by making contributions to:


Break-through discoveries in computational, communication, cognitive and organisational science needed to support health service innovation and biomedical researchers.


Providing expert input and leadership into government, shaping eHealth and digital health policy priorities and goals.


Invention of novel information technologies and methods that can transfer into industry and health services.


Training future researchers through postgraduate research degrees, and educating clinicians, technologists and policy makers in health informatics through postgraduate programs.

Join our team or partner with us

We welcome research scientists and students with a background as clinicians, computer scientists and engineers to join our team. We invite industry to partner with us to create business opportunities through research and innovation.

Centre for Health Informatics 

Our research areas 


The NHMRC Centre of Research Excellence (CRE) in eHealth targets major evidence gaps in the safety and quality of clinical and consumer eHealth systems. The CRE has three major research streams: eHealth safety, consumer eHealth, and clinical decision support.

Investigators in the CRE come from Macquarie University, the University of NSW, Sydney University, Bond University, and the University of South Australia. Professor Coiera directs the $2.5 million CRE, whose work program supports collaborative research between the Centre for Health Informatics at Macquarie University and its four partner Universities.

Find out more about the CRE at ehealth.edu.au


Professor Enrico Coiera, Director 
Associate Professor Farah Magrabi, Associate Professor
Dr Blanca Gallego Luxan, Senior Research Fellow
Dr Annie Lau, Senior Research Fellow
Dr Guy Tsafnat, Senior Research Fellow
Dr Adam Dunn, Senior Research Fellow


Mr Tom Bowden, PhD Student
Mr Tobias Hodgson, PhD Student
Mr David Lyell, PhD Student
Mr Ken Lee, MPhil Student

Media links

For more information or to join our team

Contact Professor Enrico Coiera, enrico.coiera@mq.edu.au+61 2 9850 2403

Artificial intelligence (AI) in medicine

The future of sustainable,. effective and safe healthcare will ultimately involve the use of artificial intelligence (AI) to support clinical decision making. Appropriately used, AI should enhance the ability of clinicians and the healthcare system to deliver accurate, timely and appropriate care. The implementation of AI will thus change the way we deliver healthcare and has the potential to be truly transformational technology.

For more information or to join our team

Contact Professor Enrico Coiera, enrico.coiera@mq.edu.au+61 2 9850 2403

Patient safety informatics

The use of information technology (IT) to support care delivery or digital health, is integral to the modern-day transformations of health systems to improve quality and safety. IT is also a key enabler for encouraging patients to actively participate in care processes for diagnosis, treatment and prevention.

At the same time, digital technologies can introduce new, often unforeseen, modes of failure that affect the safety and quality of care and lead to patient harm and death. Unlike other risks to patient safety, IT can — because of its scale and scope — increase the risk of harm to many patients during the delivery of health care. With large and complex IT systems being rapidly deployed, the opportunity for patient harm can be significantly increased if safety of the IT systems themselves is not improved.

Our Patient Safety Informatics research program takes a cross-disciplinary approach to improve the safety of digital health in Australia by making theoretical, methodological and policy contributions which translate into changes to healthcare delivery and improved patient outcomes.

We are investigating the patient safety risks of current and future digital health technologies including artificial intelligence (AI). Our goal is to design sociotechnical solutions to mitigate these risks and to develop new methods for the timely detection of, and response to, emerging threats.

We welcome clinicians, information technologists, engineers and students who wish to pursue excellence in informatics and share our passion for improving the safety eHealth through good design and the appropriate application of technology.  


Associate Professor Farah Magrabi, Team Leader
Dr Ying Wang, Research Fellow
Dr Mi-Ok Kim, Post-doctoral Research Fellow
Jessica Chen, Intern
Dr Mei-Sing Ong, Visiting Fellow 
Dr Saba Akbar, Visiting Fellow 

Current projects

Media links

For more information or to join our team

Contact Associate Professor Farah Magrabi, farah.magrabi@mq.edu.au, +61 2 9850 2429

Health analytics

The recent availability of digital biomedical data and the enabling technology to collect, store and analyse this data will transform health care from traditional models to learning health care systems, where research and practice are integrated in a sustained manner. These learning health care systems require new methods where analytics are performed in real time at the point-of-care. At the Health Analytics Lab at AIHI, we are designing, developing and testing such models so that they can be implemented in future Electronic Health Record systems.

Our core strength lies in the combination of deep analytic and computing theory and methods with understanding of clinical decision support systems. This enables us to advance the scientific knowledge of health analytics while translating our research. We welcome researchers, clinicians and students who wish to pursue excellence in analytics and technology and share a common interest in health informatics.


Dr Blanca Gallego Luxan, Team Leader
Dr Thierry Wendling, Post-doctoral Research Fellow
Dr William Tong, Post-doctoral Research Fellow
Ms Georgina Kennedy, PhD Student & Research Assistant
Dr Christoph Camphausen, MPhil Student
Dr Appukutty Manickman, PhD Student
Dr Mohammed Khalifa, PhD Student
Dr Thilo Schuler, PhD Student
Mr Aidan O'Brien, MRes Student
Ms Maisie Lee, Intern
Dr Oscar Perez-Concha, Visiting Fellow

Current projects

For more information or to join our team

Contact Dr Blanca Gallego-Luxan, blanca.gallegoluxan@mq.edu.au +61 2 9850 2435

Consumer informatics

Focusing on those with the highest stake in our healthcare system, our research program investigates the impact, design, and science of Information and Communication Technology (ICT) on consumers, patients and their carers.

Our research program is unique nationally and internationally.  It  focuses on the:

  1. Impact of Consumer eHealth: How does ICT affect our health decisions, behaviours, and outcomes?
  2. Design of Consumer eHealth: How can we design ICT that would improve our engagement with health services?
  3. Science of Consumer eHealth: What is the theoretical understanding that underpins the way we use and design ICT for consumers, patients and carers?

(Collaborations are warmly welcome.  Student projects are available upon request.)


Dr Annie Lau, Team Leader
Dr Liliana Laranjo,  Postdoctoral Research Fellow
Dr Kathleen Yin,  Postdoctoral Research Fellow
Ms Paige Newman, Research Officer
Ms Ly Tong, PhD Student & Research Assistant

Current projects

Media links

For more information or to join our team

Contact Dr Annie Lau, annie.lau@mq.edu.au, +61 2 9850 2436

Computable evidence lab

The Computable Evidence Lab (CEL) members focusses on how clinical decisions can be made quickly and safely based on evidence. We focus on ways in which automation can help gather, synthesize and disseminate evidence to inform decision making at the right place and time for the decision.

There are three main themes across the lab:

  1. Machine Learning - algorithms that find patterns in data for a variety of applications such as prediction, classification and artificial intelligence.
  2. Natural Language Processing - algorithms that find, appraise and extract information from text.
  3. Heuristic Systems - rule based systems that encapsulate and use domain expertise to solve a particular problem.

Evidence based medicine already provides a robust model for gathering, synthesis and dissemination of evidence in the systematic review model. At CEL we follow this model for different kinds of evidence summaries and different kinds of evidence from sources such as genomics and electronic health records. The Computable Evidence Lab is leading the way for new ways to think about evidence. Evidence should be ubiquitous, inexpensive and available to enable safe and effective healthcare systems.


Dr Guy Tsafnat, Team Leader
Mr Vitaliy Kim, Senior Programmer
Ms Vimala Jacob, Database Architect
Mr Michael Van Treeck, Programmer
Mr Atapatu (Sachith) Algama, Programmer
Mr Nan Zhou, PhD Student

Current projects

For more information or to join our team

Contact Dr Guy Tsafnat, guy.tasfnat@mq.edu.au, +61 2 9850 2430

Evidence surveillance

The aims of the program are to observe and measure the systems of knowledge transfer in medical evidence. Using data mining, network science, and machine learning, we undertake projects that examine networks of interacting researchers, clinical trials, clinicians, and the communities they serve. Our broad focus includes the entire pipeline of evidence translation – from the design and undertaking of clinical trials, through the reporting and synthesis of evidence in published research and the media, and into the use of clinical evidence in policy, practice, and the decision-making of clinicians and their patients.


Dr Adam Dunn, Team Leader
Dr Didi Surian, Postdoctoral Research Fellow
Mr Zubair Shah, Postdoctoral Research Fellow
Dr Amalie Dyda, Postdoctoral Research Fellow
Ms Paige Newman, Research Officer
Ms Rabia Bashir, PhD Student
Ms Marke Steffens, PhD Student 

Current projects

Media links

For more information or to join our team

Contact Dr Adam, adam.dunn@mq.edu.au, +61 2 9850 2413

Centre management 

Ms Jenny Waldie, Business Manager
Ms Denise Tsiros, Manager Operations & Students
Ms Leanne Bamford-Barnes, Fellowship Program Manager 

Our staff

Resources related to this Centre




  1. Lau, A. Participatory Health through Social Media, 1st Ed from Shabbir Syed-Abdul, Elia Gabarron. Academic Press, 2016
  2. Coiera E. Guide to Health Informatics. 3rd ed. United Kingdom: CRC Press Imprint; 2015.
  3. Sintchenko, V (Ed). Infectious disease Informatics, Springer, 2010
  4. Sintchenko V. Decision by design: Decision support for antibiotic prescribing in critical care. Saarbrucken: VDM-Verlag Dr Müller; 2009. 
  5. Westbrook JI, Coiera EW, Callen JL, Aarts J (eds). Information technology in Health Care 2007, Proceedings of the 3rd International Conference on Information Technology in Health Care; Socio-technical approaches, IOS Press, 311pp.
  6. Lau, A. The impact of cognitive biases on information searching and decision making, UNSW, 2006
  7. Fieshi M, Coiera E, Li Y (eds). Proceedings of the 11th World Congress on Medical Informatics – Medinfo 2004, IOS Press, 2 vols.

 Annual Reports

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