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12 年大学医院旷工演变的数学建模。

Mathematical Modeling of the Evolution of Absenteeism in a University Hospital over 12 Years.

机构信息

Occupational and Environmental Medicine, CHU Clermont-Ferrand, F-63000 Clermont-Ferrand, France.

Biostatistics Unit, CHU Clermont-Ferrand, F-63000 Clermont-Ferrand, France.

出版信息

Int J Environ Res Public Health. 2022 Jul 6;19(14):8236. doi: 10.3390/ijerph19148236.

Abstract

Increased absenteeism in health care institutions is a major problem, both economically and health related. Our objectives were to understand the general evolution of absenteeism in a university hospital from 2007 to 2019 and to analyze the professional and sociodemographic factors influencing this issue. An initial exploratory analysis was performed to understand the factors that most influence absences. The data were then transformed into time series to analyze the evolution of absences over time. We performed a temporal principal components analysis (PCA) of the absence proportions to group the factors. We then created profiles with contributions from each variable. We could then observe the curves of these profiles globally but also compare the profiles by period. Finally, a predictive analysis was performed on the data using a VAR model. Over the 13 years of follow-up, there were 1,729,097 absences for 14,443 different workers (73.8% women; 74.6% caregivers). Overall, the number of absences increased logarithmically. The variables contributing most to the typical profile of the highest proportions of absences were having a youngest child between 4 and 10 years old (6.44% of contribution), being aged between 40 and 50 years old (5.47%), being aged between 30 and 40 years old (5.32%), working in the administrative field (4.88%), being tenured (4.87%), being a parent (4.85%), being in a coupled relationship (4.69%), having a child over the age of 11 (4.36%), and being separated (4.29%). The forecasts predict a stagnation in the proportion of absences for the profiles of the most absent factors over the next 5 years including annual peaks. During this study, we looked at the sociodemographic and occupational factors that led to high levels of absenteeism. Being aware of these factors allows health companies to act to reduce absenteeism, which represents real financial and public health threats for hospitals.

摘要

医疗机构旷工率上升是一个重大问题,无论是在经济方面还是健康方面。我们的目标是了解 2007 年至 2019 年期间大学医院旷工率的总体变化,并分析影响这一问题的职业和社会人口因素。首先进行了探索性分析,以了解对旷工影响最大的因素。然后将数据转换为时间序列,以分析随时间推移旷工率的变化。我们对缺勤比例进行了时间主成分分析(PCA),以对因素进行分组。然后,我们创建了每个变量的贡献的档案。然后,我们可以全局观察这些档案的曲线,也可以按时间段比较档案。最后,我们使用 VAR 模型对数据进行了预测分析。在 13 年的随访期间,共有 14443 名不同工人缺勤 1729097 次(73.8%为女性;74.6%为护理人员)。总体而言,旷工人数呈对数增长。对缺勤比例最高的典型档案贡献最大的变量是有 4 至 10 岁的最小孩子(占 6.44%)、年龄在 40 至 50 岁之间(占 5.47%)、年龄在 30 至 40 岁之间(占 5.32%)、在行政领域工作(占 4.88%)、有任期(占 4.87%)、有孩子(占 4.85%)、处于伴侣关系(占 4.69%)、孩子超过 11 岁(占 4.36%)和离异(占 4.29%)。预测结果表明,未来 5 年内缺勤比例最高的档案将停滞不前,包括每年的高峰期。在这项研究中,我们研究了导致高旷工率的社会人口和职业因素。了解这些因素可以使卫生公司采取行动减少旷工率,这对医院来说是真正的财务和公共卫生威胁。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/def9/9316583/e791e3a51072/ijerph-19-08236-g001.jpg

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