Determinants of healthcare worker turnover in intensive care units: A micro-macro multilevel analysis.
Determinants of healthcare worker turnover in intensive care units: A micro-macro multilevel analysis.
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DOI：
10.1371/journal.pone.0251779
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发表时间：
2021
期刊：
影响因子：
3.7
通讯作者：
Temime L
中科院分区：
文献类型：
--
作者：
Daouda OS;Hocine MN;Temime L
卫生保健工作者的高流动率是世界各地医院日益普遍的现象，特别是在重症监护病房（icu）。除了严重的经济后果外，这也是患者护理的一个主要问题（护理的连续性中断，护理质量和安全性下降，药物错误率增加，……）。本文的目的是利用526名法国注册护士和辅助护士（ran）的数据，了解icu级别护士的流失率如何从个人和icu级别的多个协变量来解释。2013年在巴黎地区医院icu进行横断面研究。首先，我们对Croon和van Veldhoven于2007年提出的多层次建模方法进行了小规模扩展，并通过全面的模拟研究验证了其性质。其次，我们将该方法应用于解释法国icu的RAN周转。在模拟研究的基础上，我们提出的方法允许估计回归系数相对偏差低于7%的群体水平因素和低于12%的个人水平因素。在我们的数据中，平均观察到RAN周转率为每年0.19 （SD = 0.09）。根据我们的研究结果，来自同事和主管的社会支持以及长期的专业经验与流失率呈负相关。相反，孩子的数量和由于工作量而无法跳过休息的可能性与较高的流动率显着相关。在ICU层面，ICU的床位数量、中间护理床位（持续护理单元）的存在和工作人员与患者的比例成为重要的预测因素。这项研究的发现可能有助于医院内的决策者通过突出的主要决定因素的更替的区域注册医生。此外，本文提出的新方法可能对面临类似微观宏观数据的研究人员有用。
High turnover among healthcare workers is an increasingly common phenomenon in hospitals worldwide, especially in intensive care units (ICUs). In addition to the serious financial consequences, this is a major concern for patient care (disrupted continuity of care, decreased quality and safety of care, increased rates of medication errors, …). The goal of this article was to understand how the ICU-level nurse turnover rate may be explained from multiple covariates at individual and ICU-level, using data from 526 French registered and auxiliary nurses (RANs). A cross-sectional study was conducted in ICUs of Paris-area hospitals in 2013. First, we developed a small extension of a multi-level modeling method proposed in 2007 by Croon and van Veldhoven and validated its properties using a comprehensive simulation study. Second, we applied this approach to explain RAN turnover in French ICUs. Based on the simulation study, the approach we proposed allows to estimate the regression coefficients with a relative bias below 7% for group-level factors and below 12% for individual-level factors. In our data, the mean observed RAN turnover rate was 0.19 per year (SD = 0.09). Based on our results, social support from colleagues and supervisors as well as long durations of experience in the profession were negatively associated with turnover. Conversely, number of children and impossibility to skip a break due to workload were significantly associated with higher rates of turnover. At ICU-level, number of beds, presence of intermediate care beds (continuous care unit) in the ICU and staff-to-patient ratio emerged as significant predictors. The findings of this research may help decision makers within hospitals by highlighting major determinants of turnover among RANs. In addition, the new approach proposed here could prove useful to researchers faced with similar micro-macro data.
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影响因子：
2.8
作者：
Hämmig O
通讯作者：
Hämmig O
影响因子：
5
作者：
COHEN, S;KAMARCK, T;MERMELSTEIN, R
通讯作者：
MERMELSTEIN, R
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作者：
Jones, Gabrielle;Hocine, Mounia;Temime, Laura
通讯作者：
Temime, Laura
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3.8
作者：
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影响因子：
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作者：
AKAIKE, H
通讯作者：
AKAIKE, H