A/Prof. Jessica Schults1,2, Dr Sally Havers1,2,9, Ms Karina Charles1,2, Gaurav Langan1,2, Mrs Janine Carrucan7, Mrs Anita Tyrell9, Mrs Victoria Burton8, Ms Olivia Sarri6, Ms Alison Pickering5, Mrs Belinda Henderson3, Ms Daner Ball1,2, A/Prof Julia Clark8, Dr Naomi Runnegar10, Mrs Alison Smith1,2, Ms Bonnie Woods1,2, Prof Lisa Hall4, Prof Claire Rickard1,2
1The University Of Queensland, School of Nursing Midwifery and Social Work, Frazier Institute, Herston, Australia, 2Herston Infectious Diseases Institute, Metro North Health, Herston, Australia, 3Queensland Infection Prevention and Control Unit, Herston, Australia, 4The University of Queensland School of Public Health, Herston, Australia, 5Royal Brisbane and Women's Hospital, Herston, Australia, 6Surgical, Treatment and Rehabilitation Service (STARS) hospital, Herston, Australia, 7Townsville University Hospital, Douglas, Australia, 8Queensland Children's Hospital, South Brisbane, Australia, 9Darling Downs Health, Toowoomba Hospital, Toowoomba, Australia, 10Princess Alexandra Hospital, Metro South Health, Woolloongabba, Australia
Biography:
Jessica is a Principal Research Fellow in Queensland with the Herston Infectious Diseases Institute and the University of Queensland. She holds an NHMRC emerging leader fellowship in infection prevention and control and works with clinicians, consumers and health services to try and make better, easier and safer.
Abstract:
Background
Healthcare-associated infection (HAI) surveillance underpins infection prevention and control (IPC) programs and prevention activities, however contemporary data describing the operational workload are limited. We aimed to characterise HAI surveillance workflows and workload across Australian healthcare settings.
Methods
We conducted a multi-site time-and-motion observational study across five Queensland public hospitals between June and November 2025. Direct non-participant observations of infection prevention and control practitioners (IPCPs) undertaking routine HAI surveillance activities were performed during standard weekday shifts. Activities were categorised into predefined surveillance domains including case finding, validation/classification, documentation, communication, and administrative tasks. Data were analysed descriptively.
Results
A total of 128 hours of HAI surveillance activity were observed across 17 site-days (mean 7.5 hours/day). Most time was spent on data review and case finding (28%), documentation and data entry (22%), and case validation (13%). Active surveillance accounted for 37% of workload (47 hours) and required frequent movement between electronic medical records, laboratory systems, and reporting databases. Overall, 756 potential HAI events were screened, with 303 confirmed. Bloodstream infection surveillance was among the most resource-intensive activities (9.6 minutes per screened case; 15.3 minutes per confirmed case), while surgical site infection surveillance required up to 33 minutes per case at participating sites. Significant organism surveillance required 3.1 minutes per screened case and 6.8 minutes per confirmed event.
Conclusions
HAI surveillance is time-intensive, and dependent on fragmented manual workflows. Findings highlight the need for streamlined surveillance systems and greater infrastructure investment.