Artificial intelligence (AI) use for personal protective equipment training, remediation, and education in health care
Year: 2025
Type: article
Abstract: 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.
Authors: Veronica Preda, Zehurn Ong, Chandana Wijeweera, Terence Carney, Robyn Clay-Williams, Denuka Kankanamge, Tamara Preda, Ioannis Kopsidas, Michael Keith Wilson
Language: English
Subfield: Infectious Diseases
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $3,360
OpenAlex ID: W4408912901