首页> 美国卫生研究院文献>Scientific Reports >Measuring dynamic social contacts in a rehabilitation hospital: effect of wards patient and staff characteristics
【2h】

Measuring dynamic social contacts in a rehabilitation hospital: effect of wards patient and staff characteristics

机译:衡量康复医院中动态的社会联系:病房患者和员工特征的影响

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

Understanding transmission routes of hospital-acquired infections (HAI) is key to improve their control. In this context, describing and analyzing dynamic inter-individual contact patterns in hospitals is essential. In this study, we used wearable sensors to detect Close Proximity Interactions (CPIs) among patients and hospital staff in a 200-bed long-term care facility over 4 months. First, the dynamic CPI data was described in terms of contact frequency and duration per individual status or activity and per ward. Second, we investigated the individual factors associated with high contact frequency or duration using generalized linear mixed-effect models to account for inter-ward heterogeneity. Hospital porters and physicians had the highest daily number of distinct contacts, making them more likely to disseminate HAI among individuals. Conversely, contact duration was highest between patients, with potential implications in terms of HAI acquisition risk. Contact patterns differed among hospital wards, reflecting varying care patterns depending on reason for hospitalization, with more frequent contacts in neurologic wards and fewer, longer contacts in geriatric wards. This study is the first to report proximity-sensing data informing on inter-individual contacts in long-term care settings. Our results should help better understand HAI spread, parameterize future mathematical models, and propose efficient control strategies.
机译:了解医院获得性感染(HAI)的传播途径是改善其控制的关键。在这种情况下,描述和分析医院中动态的个人间联系方式至关重要。在这项研究中,我们使用可穿戴式传感器在200多个床位的长期护理机构中检测患者和医院工作人员之间的近距离互动(CPI),历时4个月。首先,动态CPI数据是根据每个状态或活动以及每个病房的接触频率和持续时间来描述的。其次,我们使用广义线性混合效应模型研究了与病程间异质性的与高接触频率或持续时间相关的个体因素。医院门房和医生的日常不同接触者每天最多,这使他们更有可能在个人中传播HAI。相反,患者之间的接触持续时间最高,这可能会影响HAI的获得风险。医院病房之间的接触方式有所不同,反映出不同的护理方式,具体取决于住院原因,其中神经病房的接触频率更高,而老年病房的接触时间越来越少。这项研究是第一个报告接近感测数据的信息,可告知长期护理环境中的个人之间的联系。我们的结果应有助于更好地理解HAI扩散,对未来的数学模型进行参数化,并提出有效的控制策略。

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号