Mrs Yun-Ju Shih1,2, Mr Ilias Papadopoulos3, Mrs Kathryn Obrien1, Mrs Michelle Doidge1, Mrs Sally Healy1, Mrs Rebecca Adam1, Mrs Corinne Miles1, Mrs Belinda Henderson1
1Queensland Infection Prevention and Control Unit, Communicable Disease Branch, Population Health Division, Queensland Health, Australia, 2Syndromic and HAI Surveillance, Epidemiology and Evidence Group, Public Health Intelligence Branch, Population Health Division, Queensland Health, , Australia, 3Data and Reporting Services, Public Health Intelligence Branch, Population Health Division, Queensland Health, Australia
Biography:
Yun-Ju Shih is an Epidemiologist for the Queensland Infection and Prevention Control Unit, Queensland Health. Yun-Ju completed Master's in Epidemiology from the National Taiwan University. Yun-Ju is passionate about informed data-driven decision-making to improve the health of all. She specialises in disease modelling, data analysis, and applied Epidemiology.
Abstract:
Background
Effective infection prevention and control (IPC) relies on timely and accurate data. In Queensland Health, statewide IPC surveillance systems collect healthcare-associated infection (HAI) data, but existing reporting tools were inflexible and required significant manual effort from IPC staff to create visualisations tailored to local needs. This project aimed to develop a standardised, user-friendly dashboard system to streamline HAI data reporting and visualisation across all hospitals and health services (HHSs).
Methods
Weekly statewide IPC surveillance data is extracted, processed through a standardised data model, and integrated into Power BI dashboards. The dashboards are securely hosted within the Department of Health, with role-based access enabling IPC staff to view their HHS-specific data. The dashboards provide high-level visualisations with drill-down functionality to meet local requirements.
Results
The dashboards were successfully implemented across 16 HHSs, with 147 users granted secure access. Key metrics, including bloodstream infections, multidrug-resistant organisms, occupational exposures, and hand hygiene compliance, are now available in a standardised format. The system also enables timely cross-facility HAI attribution, previously unavailable, and supports customisable timeframes and detailed data views.
Conclusion
The dashboards have enhanced IPC data accessibility and standardisation across Queensland. As staff continue to build familiarity with the new system, the dashboards are well positioned to become a centralised tool for monitoring HAI trends. Ongoing consultation and iterative improvements will ensure sustained usability and impact.