Data_Sheet_1_Internet of Things to Explore Moment 2 of “WHO My Five Moments” for Hand Hygiene.pdf

Background: Electronic hand hygiene surveillance systems are developing and considered to be more reliable than direct observation for hand hygiene monitoring. However, none have the capability to assess compliance in complex nursing care.Materials and Methods: We combined two different technologies, a hand hygiene monitoring system (radiofrequency identification, RFID) and a nursing care recorder at the bedside, and we merge their data to assess hand hygiene performance during nursing. Nursing tasks were classified as standard task procedures or aseptic task procedures corresponding to moment 2 among the five moments for hand hygiene recommended by the WHO. All statistical analyses were performed using R, version 3.6.2. For mixed models, the package “lme4” was used.Results: From the merged database over the 2-year study period, 30,164 nursing tasks were identified for analysis, 25,633 were classified as standard task procedures, and 4,531 were classified as aseptic task procedures for nursing care. Hand disinfection with an alcohol-based solution was not detected with our system in 42.5% of all the recorded tasks, 37% of all the aseptic task procedures, and 47.1% of all the standard task procedures for nursing (p = 0.0362), indicating that WHO moment 2 was not respected in 37% of mandatory situations.Conclusion: Using a combination of different technologies, we were able to assess hand hygiene performance in the riskiest circumstances.

背景：电子手卫生监测系统正在不断发展，并被认为在监测手卫生方面比直接观察更为可靠。然而，目前尚无系统能够对复杂护理过程中的手卫生依从性进行评估。研究方法：本研究结合了两种不同的技术，即手卫生监测系统（无线电频率识别，RFID）和床旁护理记录器，并将它们的数据合并以评估护理过程中的手卫生表现。护理任务被分类为标准操作程序或无菌操作程序，这对应于世界卫生组织（WHO）推荐的五个手卫生时刻中的第二时刻。所有统计分析均使用 R 软件版本 3.6.2 进行。对于混合模型，使用了“lme4”软件包。结果：在为期两年的研究期间合并的数据库中，共识别出 30,164 项护理任务进行分析，其中 25,633 项被归类为标准操作程序，4,531 项被归类为无菌操作程序。在我们的系统中，在所有记录的任务中，42.5% 未检测到基于酒精的消毒液的手部消毒，37% 的无菌操作程序，以及 47.1% 的标准操作程序，这表明在 37% 的强制情况下并未遵守 WHO 的第二时刻。结论：通过结合不同的技术，我们能够在风险最高的环境中评估手卫生表现。