College of Science and Engineering, Flinders University, GPO Box 2100, Adelaide, SA 5001, Australia.
Enware Australia Pty Ltd., 11 Endeavour Road, Caringbah, NSW 2229, Australia.
Int J Environ Res Public Health. 2019 Apr 13;16(8):1332. doi: 10.3390/ijerph16081332.
Within hospitals and healthcare facilities opportunistic premise plumbing pathogens (OPPPs) are a major and preventable cause of healthcare-acquired infections. This study presents a novel approach for monitoring building water quality using real-time surveillance of parameters measured at thermostatic mixing valves (TMVs) across a hospital water distribution system. Temperature was measured continuously in real-time at the outlet of 220 TMVs located across a hospital over a three-year period and analysis of this temperature data was used to identify flow events. This real-time temperature and flow information was then compared with microbial water quality. Water samples were collected randomly from faucets over the three-year period. These were tested for total heterotrophic bacteria, spp. and . A statistically significant association with total heterotrophic bacteria concentrations and the number of flow events seven days prior ([865] = -0.188, < 0.01) and three days prior to sampling ([865] = -0.151, < 0.01) was observed, with decreased heterotrophic bacteria linked to increased flushing events. Only four samples were positive for and statistical associations could not be determined; however, the environmental conditions for these four samples were associated with higher heterotrophic counts. This study validated a simple and effective remote monitoring approach to identifying changes in water quality and flagging high risk situations in real-time. This provides a complementary surveillance strategy that overcomes the time delay associated with microbial culture results. Future research is needed to explore the use of this monitoring approach as an indicator for different opportunistic pathogens.
在医院和医疗设施中,机会性前提管道病原体(OPPPs)是医院获得性感染的主要且可预防的原因。本研究提出了一种使用实时监测恒温混合阀(TMV)参数的新方法来监测建筑物水质。在三年的时间里,连续实时测量了位于医院内的 220 个 TMV 出口处的温度,并且分析了这些温度数据以识别流量事件。然后,将实时温度和流量信息与微生物水质进行比较。在三年的时间里,随机从水龙头收集水样。这些水样用于测试总异养菌、 和 。观察到总异养菌浓度与七天前([865] = -0.188, < 0.01)和三天前([865] = -0.151, < 0.01)的流量事件数量之间存在统计学显著关联,冲洗事件增加与异养菌减少有关。只有四个样本对 呈阳性,无法确定统计学关联;然而,这四个样本的环境条件与更高的异养计数有关。本研究验证了一种简单有效的远程监测方法,可以实时识别水质变化和标记高风险情况。这提供了一种补充的监测策略,可以克服与微生物培养结果相关的时间延迟。需要进一步研究探索使用这种监测方法作为不同机会性病原体的指示物。