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美国个人防护装备库存中的质量保证抽样计划:一项用于检验降解率的计算机模拟研究

Quality Assurance Sampling Plans in US Stockpiles for Personal Protective Equipment: A Computer Simulation to Examine Degradation Rates.

机构信息

Mitchell T. Dubaniewicz is a student researcher, Department of Bioengineering, Swanson School of Engineering, University of Pittsburgh, and was on assignment with CDC/NIOSH/NPPTL.

Dana R. Rottach, PhD, is a Physical Scientist, and Patrick L. Yorio, PhD, is a Health Statistician; both at the National Personal Protective Technology Laboratory, National Institute for Occupational Safety and Health, Centers for Disease Control and Prevention, Pittsburgh, PA.

出版信息

Health Secur. 2019 Jul/Aug;17(4):324-333. doi: 10.1089/hs.2019.0042.

Abstract

Medical countermeasure stockpiles in the United States are designed to support healthcare workers and the public during public health emergencies; they include supplies of personal protective equipment (PPE). As part of typical PPE manufacturing processes, appropriate test methods are used to ensure that the devices provide adequate protective performance. At the time of manufacture, performance is often measured and weighed against an objective standard of quality, resulting in a pass or fail attribute being assigned to individual PPE items and thence to production lots. Incorporating periodic performance testing for stockpiled PPE can ensure that they maintain their protective qualities and integrity over time while in storage. There is an absence of guidance regarding how to design quality assurance programs for stockpiled PPE. The applicability of the Lot Quality Assurance Sampling (LQAS) approach to stockpiled PPE was examined in a previous study that compared and contrasted different sample sizes in recovering the true percentage of defective units in large lots in the LQAS framework. The current study carries this line of inquiry forward by integrating PPE degradation over time and comparing different sampling time intervals in recovering the true underlying degradation rate. The results suggest that product degradation is more easily detected when tested at shorter time intervals and for higher degradation rates. They further suggest that sampling interval groupings can be made based on the proficiency with which they recover the true underlying degradation rate.

摘要

美国的医疗对策储备旨在为公共卫生紧急情况下的医护人员和公众提供支持;其中包括个人防护设备 (PPE) 的供应。作为典型的 PPE 制造过程的一部分,需要使用适当的测试方法来确保设备提供足够的防护性能。在制造时,通常会根据质量的客观标准进行性能测量和衡量,从而为个别 PPE 物品以及生产批次分配通过或失败的属性。对储备的 PPE 进行定期性能测试可以确保它们在储存过程中随着时间的推移保持其防护质量和完整性。目前还没有关于如何为储备的 PPE 设计质量保证计划的指南。在之前的一项研究中,考察了 Lot Quality Assurance Sampling (LQAS) 方法对储备的 PPE 的适用性,该研究比较和对比了在 LQAS 框架中恢复大量缺陷单位真实百分比的不同样本大小。本研究通过整合随时间推移的 PPE 降解,并比较在恢复真实基础降解率时的不同采样时间间隔,进一步推进了这一研究思路。结果表明,当在较短的时间间隔内进行测试并且对于较高的降解率进行测试时,产品降解更容易被检测到。它们进一步表明,可以根据它们恢复真实基础降解率的熟练程度对采样间隔分组。

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