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2020 年 3 月至 2021 年 2 月期间,退伍军人健康管理局在大规模实验室中实施 COVID-19 检测。

Implementation of large-scale laboratory-based detection of COVID-19 in the Veterans Health Administration, March 2020 - February 2021.

机构信息

US Department of Veterans Affairs, Public Health Surveillance and Research, Palo Alto, CA, USA.

US Department of Veterans Affairs, Public Health Surveillance and Research, Palo Alto, CA, USA.

出版信息

Diagn Microbiol Infect Dis. 2022 Mar;102(3):115617. doi: 10.1016/j.diagmicrobio.2021.115617. Epub 2021 Dec 11.

Abstract

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) presented numerous operational challenges to healthcare delivery networks responsible for implementing large scale detection of Coronavirus Disease 2019 (COVID-19), the infection caused by SARS-CoV-2. We describe testing performance, review data quality metrics, and summarize experiences during the scale up of laboratory-based detection of COVID-19 in the Veterans Health Administration, the largest healthcare system in the United States. During March 2020 to February 2021, we observed rapid increase in testing volume, decreases in test turnaround time, improvements in testing of hospitalized persons, changes in test positivity, and varying utilization of different tests. Though performance metrics improved over time, surges challenged testing capacity and data quality remained suboptimal. Future planning efforts should focus on fortifying supply chains for consumables and equipment repair, optimizing distribution of testing workload across laboratories, and improving informatics to accurately monitor operations and intent for testing during a public health emergency.

摘要

严重急性呼吸综合征冠状病毒 2(SARS-CoV-2)给负责大规模检测 2019 年冠状病毒病(COVID-19)的医疗保健网络带来了诸多运营挑战,COVID-19 是由 SARS-CoV-2 引起的感染。我们描述了检测性能,审查了数据质量指标,并总结了在美国最大的医疗保健系统 Veterans Health Administration 中扩大基于实验室的 COVID-19 检测规模的经验。在 2020 年 3 月至 2021 年 2 月期间,我们观察到检测量迅速增加,检测周转时间缩短,住院患者检测情况改善,检测阳性率变化,以及不同检测方法的使用情况不同。虽然性能指标随着时间的推移而有所提高,但疫情高峰期仍对检测能力构成挑战,数据质量仍不理想。未来的规划工作应侧重于加强消耗品和设备维修的供应链,优化实验室之间的检测工作量分配,并改进信息学,以在公共卫生紧急情况下准确监测运营和检测意向。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2eb6/8665666/105c1e15945c/gr1_lrg.jpg

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