Suppr超能文献

利用基于医院网络的监测来监测抗生素耐药性,作为自我报告的更有力替代方法。

Using hospital network-based surveillance for antimicrobial resistance as a more robust alternative to self-reporting.

机构信息

The National Institute for Health Research (NIHR) Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, University of Oxford, Oxford, United Kingdom.

Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.

出版信息

PLoS One. 2019 Jul 25;14(7):e0219994. doi: 10.1371/journal.pone.0219994. eCollection 2019.

Abstract

Hospital performance is often measured using self-reported statistics, such as the incidence of hospital-transmitted micro-organisms or those exhibiting antimicrobial resistance (AMR), encouraging hospitals with high levels to improve their performance. However, hospitals that increase screening efforts will appear to have a higher incidence and perform poorly, undermining comparison between hospitals and disincentivising testing, thus hampering infection control. We propose a surveillance system in which hospitals test patients previously discharged from other hospitals and report observed cases. Using English National Health Service (NHS) Hospital Episode Statistics data, we analysed patient movements across England and assessed the number of hospitals required to participate in such a reporting scheme to deliver robust estimates of incidence. With over 1.2 million admissions to English hospitals previously discharged from other hospitals annually, even when only a fraction of hospitals (41/155) participate (each screening at least 1000 of these admissions), the proposed surveillance system can estimate incidence across all hospitals. By reporting on other hospitals, the reporting of incidence is separated from the task of improving own performance. Therefore the incentives for increasing performance can be aligned to increase (rather than decrease) screening efforts, thus delivering both more comparable figures on the AMR problems across hospitals and improving infection control efforts.

摘要

医院的绩效通常通过自我报告的统计数据来衡量,例如医院传播的微生物或表现出抗微生物药物耐药性(AMR)的微生物的发生率,这鼓励了高发生率的医院提高其绩效。然而,增加筛查力度的医院会显示出更高的发生率和较差的表现,从而破坏了医院之间的可比性,并抑制了检测,从而阻碍了感染控制。我们提出了一种监测系统,其中医院测试先前从其他医院出院的患者,并报告观察到的病例。我们使用英国国家医疗服务体系(NHS)的医院入院统计数据,分析了英格兰各地的患者流动情况,并评估了需要参与这种报告计划的医院数量,以提供发病率的可靠估计。由于英国每年有超过 120 万例从其他医院出院的患者入院,即使只有一小部分医院(155 家医院中的 41 家)参与(每家医院对这些入院患者中的至少 1000 人进行筛查),所提议的监测系统也可以估计所有医院的发病率。通过报告其他医院的情况,发病率的报告与提高自身绩效的任务分开。因此,可以调整提高绩效的激励措施,以增加(而不是减少)筛查力度,从而在医院之间提供更可比的 AMR 问题数据,并改善感染控制工作。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ad7/6657867/24e6cefb9f9b/pone.0219994.g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验