Lacey, Gerard and Zhou, Jiang and Li, Xuchun and Craven, Christine and Gush, Chris (2020) The impact of automatic video auditing with real-time feedback on the quality and quantity of handwash events in a hospital setting. American Journal of Infection Control, 48 (2). pp. 162-166. ISSN 0196-6553

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Abstract

Background: Poor quality handwashing contributes to the spread of nosocomial infections. We investigate the impact of automatic video auditing (AVA) with feedback on the quality and quantity of handwashing in a hospital setting. Methods: AVA systems were mounted over all handwash sinks in a surgical unit. Phase 1 established baseline handwashing quality and quantity. Phase 2 examined the impact of real-time performance feedback, and phase 3 examined the incremental impact of weekly team performance reports. Phase 4 remeasured the baseline without feedback. Results: A total of 3,606 handwash events were audited. During phase 2 and 3, compliance with the World Health Organization technique improved from 15.7%-46% (P < .0001), and the average number of handwash events per patient per day increased from 0.91-2.25 (P < .0001). Performance returned to baseline in phase 4. Conclusions: AVA with real-time feedback significantly improved the quality and quantity of handwashing. The combination of AVA with electronic monitoring will allow simultaneous auditing of hand hygiene quantity and quality. The impact of cognitive offloading onto the technology may have contributed to the return to baseline at the end of the study, and suggests further research is required in this area

Item Type:	Article
Additional Information:	Gerard Lacey, Jiang Zhou, Xuchun Li, Christine Craven, Chris Gush, The impact of automatic video auditing with real-time feedback on the quality and quantity of handwash events in a hospital setting, American Journal of Infection Control, Volume 48, Issue 2, 2020, Pages 162-166, ISSN 0196-6553, https://doi.org/10.1016/j.ajic.2019.06.015. Copyright: Open access
Keywords:	Handwashing; Training; Feedback; IT for infection control Image processing; Artificial intelligence
Academic Unit:	Faculty of Science and Engineering > Electronic Engineering Faculty of Science and Engineering > Research Institutes > Hamilton Institute
Item ID:	16612
Identification Number:	https://doi.org/10.1016/j.ajic.2019.06.015
Depositing User:	Gerard Lacey
Date Deposited:	13 Oct 2022 10:37
Journal or Publication Title:	American Journal of Infection Control
Refereed:	Yes
URI:	Publisher
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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