National Injury Surveillance for Actionable Research (NISAR-ED)
Building Australia’s national injury surveillance infrastructure
National Injury Surveillance for Actionable Research - Emergency Department (NISAR-ED) is developing a coordinated Emergency Department injury surveillance capability to transform routinely collected clinical data into actionable intelligence for injury prevention, research, policy and public health reporting.
Burden
$11.4B
Annual health system expenditure on injury in Australia (2023-24)
AIHW
Scale
~9 Million
Emergency Department presentations annually in Australia
AIHW
Gap
~20-25%
of all Emergency Department presentations are injury-related, many lacking structured information on how the injury occurred.
AIHW
Despite the scale and cost of injury in Australia, critical information on how injuries occur is not routinely captured in structured data, limiting the ability to measure causes, monitor trends, and inform prevention and system response.
About
National Injury Surveillance for actionable Research - Emergency Department
NISAR-ED is a national research and data infrastructure initiative led by University of New South Wales (UNSW) and funded by the Medical Research Future Fund.
NISAR-ED establishes a scalable, jurisdiction-based system that processes structured and unstructured ED data to generate ICD-11 external cause of injury information. This supports more accurate identification of risks such as family and domestic violence, self-harm, product-related harm, and workplace injury, informing prevention, policy and health system planning.
Why this matters
A critical unmet need in Australian health information
Injury is a major contributor to the burden of disease in Australia. However, there is no coordinated national Emergency Department injury surveillance system capable of systematically capturing how injuries occur — limiting the ability to generate actionable, nationally consistent data.
Limited visibility of injury causes
Without structured external cause data, it is difficult to measure how and why injuries occur across populations.
Inability to monitor trends
The lack of consistent data limits the ability to track injury patterns over time and across jurisdictions.
Reduced ability to act
This constrains prevention efforts, evaluation of interventions, and evidence-informed policy and regulatory decision-making.
People
Project leadership, investigators and delivery team
Operational leadership is shared between UNSW and the Australian Institute of Health and Welfare (AIHW), supporting alignment with national data standards and jurisdictional implementation.
Leadership
Dr Lisa Sharwood
Principal Investigator and Project Lead, UNSW
Dr Sharwood leads the design, implementation and national coordination of NISAR-ED. She is an injury epidemiologist and health data scientist, focused on developing injury surveillance systems that are both methodologically robust and operationally feasible within health system settings.
Her experience includes over 25 years in academia and clinical research, also spanning senior roles across the Australian Government, including the Attorney-General's Department, the Australian Institute of Health and Welfare, and the Department of Health and Aged Care. She has a clinical background in emergency nursing, informing a strong emphasis on implementation, governance and translation.
Vicki Bennett
Deputy Lead (AIHW) and Director, Data Classifications
Vicki Bennett is a qualified Health Information Manager with a Masters in Health Informatics and brings deep experience across hospitals and Commonwealth health agencies. Vicki provides operational co-leadership of NISAR-ED through the Australian Insitute of Health and Welfare (AIHW), with responsibility for classification standards, validation processes and alignment with national health data collections.
Her role as Deputy Lead and Chief Investigator, representing AIHW as partner on this project, ensures that NISAR-ED outputs are consistent with national data governance requirements and are suitable for integration into existing reporting frameworks. Vicki's team will provide human-in-the-loop validation of machine learning outputs, supporting classification rigour using LLMs.
Investigators and collaborators
NISAR-ED brings together expertise in injury epidemiology, injury prevention, injury and trauma response and care, implementation science, health services research, health economics, Emergency Medicine and nursing, machine learning, government policy and public health reporting
Associate Professor Janneke Berecki-Gisolf
Director, Victorian Injury Surveillance Unit, MUARC
Professor Rebecca Ivers AM
Professor of Public Health, Deputy Dean Global, School of Population Health, UNSW
Professor Louisa Jorm
Foundational Director, Centre for Big Data Research in Health, UNSW
Ms Jacqueline Rek
Unit head, Injury Data, AIHW
Dr Oscar Perez Concha
Senior lecturer, Machine Learning, Centre for Big Data Research in Health, UNSW
Professor Robyn Clay-Williams
Professor of Implementation Science and Health Services Research, Macquarie University
Professor Rita Shackel
Professor of Law & Ethics, Sydney Law School, University of Sydney
Professor Henry Cutler
Director, Macquarie University Centre for the Health Economy
Professor Michael Dinh
Emergency Physician, Director RPA Green Light Institute, SLHD | University of Sydney
Professor Fiona Shand
Head, Suicide Prevention Research, Black Dog Institute, UNSW
Professor Kelsey Hegarty
Lead, Safer Families Centre of Research Excellence, University of Melbourne
Professor Trudy Rebbeck
NHMRC Centre of Research Excellence in Better Health Outcomes for Compensable Injury, University of Sydney
Project team
NISAR-ED is delivered through a national collaboration involving epidemiologists, data scientists, clinical coders, and jurisdictional health system partners.
Nadav Rayman
Data and Systems Specialist, BizData
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Nadav Rayman is the Director of Data Strategy and Solution Advisory at BizData. Nadav holds a degree in Economics and draws on 20 years' practical experience of data-driven projects.
Peter O'Sullivan
Web Developer, BizData
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Peter has over 14 years of experience in the software industry, having worked as a Lead Developer at Allori and a Product Owner at The Beddoes Group before joining Covaler. He is skilled in Microsoft 365, business development, and web application development.
Islam Ibrahim
ICD-11 Coding Specialist
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Islam is a medical doctor and international expert in health classifications who led the first national implementation of ICD-11 morbidity coding in Kuwait. Within NISAR-ED, she leads the application of ICD-11 coding for Emergency Department data.
Loc Nguyen
Data Scientist, UNSW
-
Loc Nguyen is a Data Scientist at UNSW, leading the design and development of AI models for automated ICD-11 coding within NISAR-ED. His work spans natural langauge processing, large language models, and end-to-end system design, translating unstructured Emergency Department data into structured, reproducible surveillance outputs. Working in partnership with the CSIRO Australian e-Health Research Centre, he plays a key role in scaling the platform from coded data to a nationally deployable injury surveillance capability.
The NISAR-ED approach
Turning Emergency Department data into actionable injury surveillance
NISAR-ED builds on data that are already collected in Emergency Departments and uses advanced analytics, natural language processing and structured coding workflows to derive meaningful injury surveillance outputs without adding burden to frontline clinicians.
The project is designed to support structured coding, validation, local reporting, and extract generation for national surveillance use cases, while remaining adaptable to jurisdiction-specific infrastructure and governance arrangements.
What NISAR-ED enables
- Earlier identification of emerging injury risks
- Better targeted injury prevention strategies
- Improved national consistency in injury intelligence
- Support for ICD-11 implementation in Australia
- Public health reporting that can inform policy and practice
What changes with NISAR-ED
From limited diagnostic visibility to actionable surveillance intelligence
Current state | What NISAR-ED adds |
|---|---|
Diagnosis codes mainly describe the injury sustained | Structured understanding of external cause, intent, location, context and contributing factors |
Jurisdictional variation limits comparability and national insight | A coordinated model supporting standardised injury surveillance outputs across jurisdictions |
Limited visibility of non-admitted injury presentations | Emergency Department data contributing to population-level injury surveillance and prevention |
Prevention opportunities are harder to target and evaluate | Actionable surveillance intelligence to inform prevention, policy and system response |
Partnerships
NISAR-ED is supported by national partners contributing expertise in data classification and national reporting, injury surveillance and epidemiology, clinical engagement and implementation context, and the regulatory use of injury data. These key partner contributions support system design, validation and implementation to enhance injury surveillance and its application.
Funding and support
$2.98M
Support from the Australian Government through the Medical Research Future Fund - National Critical Research Infrastructure Initiative (NCR1000116).
$3M
Approximate in-kind contribution from project partners and collaborators.
Together, this support enables the development of Australia's first coordinated Emergency Department injury surveillance infrastructure.
Implementation approach
Designed for secure, jurisdiction-based deployment
NISAR-ED is deployed within each jurisdiction’s existing systems, ensuring that sensitive data remain under local control. The platform supports standardised coding, validation and reporting while enabling consistent injury surveillance outputs across jurisdictions.
Data remains in jurisdiction
Data are processed within jurisdiction-controlled environments, avoiding the need to transfer identifiable information to external systems.
Human oversight and validation
Clinical coding and validation workflows support data quality, transparency and continuous improvement of system outputs.
Local use with national consistency
Outputs support local reporting and decision-making, while enabling standardised data for broader injury surveillance and national use.
Research and engagement
Knowledge and insights from the NISAR-ED program
Explore the evidence disseminated through NISAR-ED, including peer-reviewed publications, conference presentations, stakeholder and media engagement and emerging evidence.
Research outputs
- Sharwood 2025 – AI for Injury Surveillance in Emergency Departments
- Peer-reviewed publications, reports and preprints will be added as they become available.
Conference activity
NISAR-ED research is presented at leading national and international forums. Upcoming presentations include the World Safety Conference, Cape Town, South Africa, in September 2026.
Newsletters
Read project updates covering implementation progress, partner engagement, research activity and opportunities for collaboration.
Media engagement
Watch an overview of the NISAR-ED project and its role in strengthening injury surveillance and supporting national data.
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