<link rel="stylesheet" href="styles.f3b1fba60ec7970c.css">

Evaluating the accuracy of an automatic counting system to detect dispensing of hand hygiene product

Loading...
Thumbnail Image
Unable to use the file because of accessibility barriers? Send us feedback

Publication Date

2024

Publisher

Elsevier

Rights

© 2024 The Authors. Published by Elsevier B.V. on behalf of Australasian College for Infection Prevention and Control.

https://creativecommons.org/licenses/by/4.0/

Version

VoR

Review Status

Peer Reviewed

Field of Education

06 Health

Field of Research

4205 Nursing
3202 Clinical sciences
4203 Health services and systems

Degree

Department

Faculty

Supervisor

Awarding Institution

Degree

Department

Faculty

Supervisor

Awarding Institution

Abstract

Background Hand hygiene (HH) is an essential element of infection prevention and control programs. Direct observation of adherence to the 5 moments for HH is considered the gold standard in compliance monitoring. However, as direct observation introduces potential bias, other strategies have been proposed to supplement HH compliance data in healthcare facilities. This study evaluated the accuracy of an automatic counting system (MEZRIT™) to detect when a HH product (soap or alcohol-based hand rub) was dispensed, and thus measure product usage as opposed to compliance with the 5 moments for HH. Methods A quasi-experimental study was conducted in a nursing simulation lab where seven participants undertook basic nursing tasks which included performing HH. Sensors were attached to soap and alcohol-based hand rub dispensers to record the time at which a product was dispensed. HH events were video recorded (time-stamped) and validated against timestamps from the automatic counting system. Results 260 HH events were detected by the automatic counting system and confirmed by video recordings. 5182 non-HH events were calculated from analysis of the video recordings. The automatic counting system had 90 % sensitivity (95%CI 85.8–93.1 %), and 100 % specificity (95%CI 99.9–100 %). This model generated a positive predictive value of 100 % (95%Cl 98.4–100 %), and a negative predictive value of 99.5 % (95%CI 99.3–99.7 %). Conclusion The MEZRIT™ system accurately identified 90 % of HH events and excluded 100 % of non-HH events. The real-time monitoring of HH product usage may be beneficial in responding quickly to changes in product usage.

Description

Research Statement

Citation

Matterson, G., Browne, K., Russo, P. L., Dawson, S., Kent, H., & Mitchell, B. G. (2025). Evaluating the accuracy of an automatic counting system to detect dispensing of hand hygiene product. Infection, Disease & Health, 30(2), 105-110. https://doi.org/10.1016/j.idh.2024.11.001

Source Title

Infection, Disease & Health

Series

International Standard Serial Number

2468-0451

International Standard Book Number

Avondale University acknowledges our Sovereign God as Creator and Provider of all things. We respectfully acknowledge the Awabakal and Darramuragal people as the traditional custodians of the lands on which we live, work, study and worship across our Lake Macquarie and Sydney campuses. We pay our respects to Elders past, present and emerging, and extend that respect to all First Nations People.

Aboriginal Peoples are advised the Library Collection contains images, voices and names of deceased people in physical and online resources. The Library recognises the significance of the traditional cultural knowledges contained within its Collection. The Library acknowledge some materials contain language that may not reflect current attitudes, was published without consent or recognition, or, is offensive. These materials reflect the views of the authors and/or the period in which they were produced and do not represent the views of the Library.

Avondale University is a member of the worldwide Seventh-day Adventist system of universities and colleges.

CRICOS Provider No.: 02731D. RTO: 91191. TEQSA: PRV12015. ABN: 53 108 186 401.

© Avondale University Ltd 2026