A new quantitative method for determining patient risk for reusable medical device categorization based on using and interpreting Kremer's cleaning classification system.

IF 3.9 3区 医学 Q1 INFECTIOUS DISEASES Journal of Hospital Infection Pub Date : 2024-10-16 DOI:10.1016/j.jhin.2024.09.024
T Kremer, N J Rowan, G McDonnell
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Abstract

The cleaning of reusable medical devices involves inherent challenges that can impact on the effectiveness of the cleaning process; consequently, the subsequent safety of patients. Fluid dynamics play a critical role in determining the flow and distribution of cleaning agents where the design of the device can either facilitate or hinder this important process. Complex geometries, narrow channels, or irregular surfaces can impede effective flushing of contaminants leading to incomplete cleaning that creates a greater likelihood for patient contamination risks. Device features (n =23) were exposed to the most challenging cleaning conditions to find the point of failure in both fluid dynamics and soil retention. Experimental results obtained from the aforementioned along with associated compound risks were used to assign a risk value. Using the "hardest to clean" device feature approach as the base risk value, the total quantitative risk score was calculated for different reusable medical devices from numerical values obtained from addressing 14 questions focusing on variability in geometry, material use, types of cleaning, and intended patient use. Patient risk values for devices with different features were calculated from using Kremer's cleaning categories based on position within value ranges. Occurrences less than 18 correspond to minimal risk devices while a total risk score between the values of 18-39 are moderate and equal to or above 40 scores corresponds to the maximal category. Application of this quantitative assessment approach will facilitate appropriate mitigation of risk for cleaning reusable medical devices by informing use of targeted effective interventions. Future use of this Kremer cleaning classification will complement and augment disinfection and sterilization modalities.

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基于使用和解释 Kremer 的清洁分类系统,确定可重复使用医疗器械分类患者风险的新定量方法。
可重复使用医疗设备的清洁工作面临着固有的挑战,这些挑战会影响清洁过程的效果,进而影响患者的安全。流体动力学在决定清洁剂的流动和分布方面起着至关重要的作用,而设备的设计既可以促进也可以阻碍这一重要过程。复杂的几何形状、狭窄的通道或不规则的表面会阻碍污染物的有效冲洗,导致清洁不彻底,从而增加患者污染风险的可能性。设备特征(n = 23)暴露在最具挑战性的清洁条件下,以找到流体动力学和土壤滞留的失效点。根据上述实验结果和相关的复合风险来确定风险值。将 "最难清洁 "设备特征方法作为基础风险值,根据解决 14 个问题所获得的数值,计算出不同可重复使用医疗设备的总量化风险分值,这些问题的重点是几何形状、材料使用、清洁类型和预期患者用途的可变性。根据数值范围内的位置,使用 Kremer 的清洁类别计算出具有不同特征的器械的患者风险值。发生率小于 18 的设备风险最小,而总风险值在 18-39 之间的设备风险中等,等于或大于 40 的设备风险最大。应用这种定量评估方法将有助于适当降低清洗可重复使用医疗器械的风险,为使用有针对性的有效干预措施提供信息。未来使用克雷默清洁分类法将对消毒和灭菌方法起到补充和增强作用。
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来源期刊
Journal of Hospital Infection
Journal of Hospital Infection 医学-传染病学
CiteScore
12.70
自引率
5.80%
发文量
271
审稿时长
19 days
期刊介绍: The Journal of Hospital Infection is the editorially independent scientific publication of the Healthcare Infection Society. The aim of the Journal is to publish high quality research and information relating to infection prevention and control that is relevant to an international audience. The Journal welcomes submissions that relate to all aspects of infection prevention and control in healthcare settings. This includes submissions that: provide new insight into the epidemiology, surveillance, or prevention and control of healthcare-associated infections and antimicrobial resistance in healthcare settings; provide new insight into cleaning, disinfection and decontamination; provide new insight into the design of healthcare premises; describe novel aspects of outbreaks of infection; throw light on techniques for effective antimicrobial stewardship; describe novel techniques (laboratory-based or point of care) for the detection of infection or antimicrobial resistance in the healthcare setting, particularly if these can be used to facilitate infection prevention and control; improve understanding of the motivations of safe healthcare behaviour, or describe techniques for achieving behavioural and cultural change; improve understanding of the use of IT systems in infection surveillance and prevention and control.
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