A study on the accuracy of hand hygiene timing monitoring and its optimization strategy for intelligent hand hygiene system
10.3760/cma.j.cn211501-20240108-00065
- VernacularTitle:智能手卫生系统的手卫生时机监测准确性及其优化策略研究
- Author:
Xiaobin QIU
1
;
Yiyu ZHUANG
;
Xiangping CHEN
;
Yi ZHANG
;
Zhiyu LOU
Author Information
1. 浙江大学医学院附属邵逸夫医院护理部，杭州 310000
- Keywords:
Hand hygiene;
Infection control;
Technology
- From:
Chinese Journal of Practical Nursing
2024;40(34):2696-2700
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To optimize the accuracy of the intelligent hand hygiene system to monitor the hand hygiene timing warning, and provide a reference basis for healthcare workers to apply the intelligent hand hygiene system.Methods:Using a single-sample diagnostic pilot study method, 62 clinical nurses wearing smart badges working in the intensive care unit of Sir Run Run Shaw Hospital Affiliated to Zhejiang University School of Medicine in Hangzhou, from December 1, 2020 to December 31, 2021 were selected by convenience sampling methods. Direct observation was used as the gold standard. The accuracy of the warning timing of the intelligent hand hygiene monitoring system was optimized through adjusting the bed sensing rang,adjusting the time setting, adjusting the time settings according to the physical space of the ward and adding posture recognition.Results:The sensitivity of adjusting the bed sensing range was 0.935 (95% CI 0.918-0.949); the specificity was 0.008 (95% CI 0.001-0.074). The sensitivity of the temporal setting based on the physical space of the ward was 0.932(95% CI 0.915-0.946); the specificity was 0.205 (95% CI 0.087-0.410). The false positive rate with gesture recognition turned on was 86.1% higher than the false positive rate without gesture recognition which was 79.5%. The diagnostic OR based on the temporal setting of the physical space of the ward was the largest at 3.517(95% CI 1.213-10.193). Conclusions:The intelligent hand hygiene system exhibits high accuracy in monitoring hand hygiene timing. Adjusting the bed sensing range and individualizing the timing settings according to the physical space of the ward can improve the accuracy. Further optimization is needed for posture recognition to improve the accuracy.
