What’s the problem?
People often wait hours in a hospital emergency department (ED) for conditions that aren’t serious, causing unnecessary waiting time and adding pressure on an already stretched system. Queensland’s Minor Injury and Illness Clinics (MIICs) were established to treat exactly these patients, yet many people still self-refer to a facility that doesn’t match the severity of their condition. Two factors drive this: patients’ limited ability to accurately self-assess their symptoms, and the absence of any established guidelines or tools to help them choose the right facility. These factors lead to compromised patient outcomes and systemic healthcare inefficiencies.
What’s UQ’s innovation?
In collaboration with Metro South Health, a team from the UQ Business School is designing an AI-powered tele-triage solution that directs patients to the acute care facility best suited to their clinical needs. Patients could enter their symptoms into the online triage system to receive a recommendation on whether to attend an ED or an MIIC.
An AI-powered system can respond to patients at scale, allowing it to ease pressure on EDs without requiring additional healthcare personnel. The underlying algorithms can also uncover patterns in large-scale patient data that even experienced clinicians cannot see, refining the ED-versus-MIIC recommendation. The model is being developed from retrospective patient data from Logan Hospital’s ED and the Eight Mile Plains Satellite Health Centre’s MIIC, and will be validated by clinical experts and through pilot studies.
What’s the impact?
An AI-powered triage system would better match emergency care to need at every level. Patients would receive an immediate recommendation and be seen in the right setting for the severity of their case, reducing wait times and the risk of delayed treatment. The system would ease ED overcrowding and cost, reducing the strain on staff, and allow MIICs to play a fuller role in community healthcare.
Did you know?
Conservatively, the Princess Alexandra Hospital Emergency Department manages at least 25,000 patients per year whose clinical needs could be better met in alternative care settings.
Led by
- Hetiao (Slim) Xie
PhD Researcher, Business Information Systems, UQ Business School
| AI Research Strength | Health & Biomedical |
|---|---|
| Key Partners | Metro South Health Princess Alexandra Hospital |
| Funding | PA Research Foundation The University of Queensland |
| Key Publications | Xie, Hetiao (Slim), Namvar, Morteza, Akhlaghpour, Saeed, and Staib, Andrew (2025). Predicting patient acuity in tele-triage using large language models: a computational design science approach. Pacific Asia Conference on Information Systems (PACIS), Kuala Lumpur, Malaysia, 5-9 July 2025. Atlanta, GA USA: Association for Information Systems. |
Published 15 September 2026