Veronica Preda BSc(Med), MBBS(Hons), MPH, FRACP, PhD , Zehurn Ong MD , Chandana Wijeweera MD , Terence Carney PhD , Robyn Clay-Williams BEng, PhD , Denuka Kankanamge BBMedSci, MD , Tamara Preda BSc(Med), MBBS, FRACS, MMedSurg , Ioannis Kopsidas MD, PhD John , Michael Keith Wilson MD, FRACS
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Artificial intelligence (AI) use for personal protective equipment training, remediation, and education in health care
Background
Personal protective equipment (PPE) is a first-line transmission-based precaution for reducing the spread of nosocomial infections between health care workers (HCWs), patients, and staff. The COVID-19 pandemic highlighted a problematic skill gap in effective PPE donning/doffing.
Methods
We performed a single-center, mixed-methods, prospective cohort study of 293 HCWs in Sydney, Australia. Participants were assessed using SXR AI-PPE, an artificial intelligence (AI) system that autonomously evaluates donning/doffing of PPE while providing real-time feedback on user technique.
Results
Longitudinal results showed improved accuracy rates for correct donning/doffing after each guided session conducted at 3-monthly intervals, with a 100% accuracy rate for correct use of PPE after 2 guided sessions. These improvements were maintained with 3-monthly training sessions.
Conclusions
The SXR AI-PPE platform is a comprehensive tool capable of training PPE donning/doffing by HCWs in real time with implications for reducing PPE contamination and risk of nosocomial infections.
期刊介绍:
AJIC covers key topics and issues in infection control and epidemiology. Infection control professionals, including physicians, nurses, and epidemiologists, rely on AJIC for peer-reviewed articles covering clinical topics as well as original research. As the official publication of the Association for Professionals in Infection Control and Epidemiology (APIC)