Dr Jessica Schults1,2, Mrs. Sally Healy3, Dr Sally Havers1,2,4, Ms. Belinda Henderson3, Ms. Karina Charles1,2, Mrs. Alison Smith1,2, Professor Lisa Hall5, Ms. Janine Carrucan6, Mrs. Sarah Smith2, Ms. Trish Hurst3, Ms. Robyn Birch7, Prof Claire Rickard1,2
1Herston Infectious Diseases Institute, Metro North Health, Herston, Australia, 2University of Queensland, School of Nursing Midwifery and Social Work, Centre for Clinical Research, St Lucia, Herston, Australia, 3Queensland Infection Prevention and Control Unit, Queensland Health, Australia, 4Darling Downs Health, Toowoomba, Australia, 5The University of Queensland, School of Public Health, Herston, Australia, 6Townsville Hospital and Health Service, Townsville, Australia, 7Central West Hospital and Health Service, Longreach, Australia
Biography:
Jessica is a conjoint Senior Research Fellow with the University of Queensland and Herston Infectious Diseases Institute (HeIDI). Her research is focused on preventing infections associated invasive medical devices. Jessica is interested in automated quality surveillance, and risk stratification using machine learning models.
Sally has been working in Infection Prevention and Control for over 13 years and is an Assistant Director with the Queensland Infection Prevention and Control Unit – running the healthcare-associated surveillance stream. Sally holds qualifications such as a Masters of Health Practice in Infection Prevention and Control, and expert credentialling with ACIPC.
Abstract:
Introduction
Healthcare associated infections (HAIs) continue to contribute significantly to Australia’s burden of disease. In Queensland, the use of varied surveillance approaches and protocols contributes to unnecessary complexity and limits targeted prevention activities. With end-user partners, we developed a core HAI surveillance measurement set to support State-wide reporting.
Methods
A modified, 2-round Delphi study was conducted in Queensland with field experts. In Round 1, an electronic survey was distributed to infection control professionals and infectious disease physicians through State-wide networks. Survey respondents rated HAI measures for importance (9-point Likert scale), feasibility (3-point Likert scale), usefulness (3-point Likert scale), and case definition acceptability (5-point Likert scale). Free text response options were also provided. In Round 2, a purposive expert panel met to review Round 1 ratings and reach consensus (defined as >70% agreement) on the final core measurement set.
Results
Forty-nine infection control professionals responded to the Round 1 survey. In March 2024, 14 clinical experts (11 infection control practitioners; 3 physicians) met to review measures which reached consensus threshold in Round 1. From the originally proposed 36 HAI measures, 13 achieved consensus for importance, usefulness and feasibility. Measures included blood stream infections, selected surgical site procedures and significant organisms. Consensus for extended spectrum beta-lactamase producing organisms, or caesarean section inclusion/exclusion was not achieved.
Conclusion
We developed a 13-measure core set to support State-wide HAI surveillance. Use of this standardised approach can support data aggregation and targeted prevention activities.