了解医疗保健中的工作场所暴力:来自瑞士医院网络八年案例研究的见解。

IF 2.2
Angela Greco
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引用次数: 0

摘要

背景:针对卫生保健工作者的工作场所暴力是全世界日益关注的问题,对工作人员的福祉、护理质量和患者安全产生了影响。然而,来自医院网络的纵向证据仍然有限,很少有研究使用统计过程控制的可视化方法来监测一段时间内的趋势。本研究考察了在瑞士公立医院网络中报告的攻击趋势是否显示出不同的时间模式,以及这种模式是否可以产生关于潜在相关组织和环境因素的假设。方法:我们对瑞士南部公立医院网络Ente Ospedaliero Cantonale (EOC)中报告的针对医护人员的攻击行为进行了一项回顾性观察研究,为期8年(2017-2024)。数据提取自网络内部质量和职业安全报告平台。每年为每家医院计算两个标准化指标:每1 000住院日的攻击次数和每1 000次出院的攻击次数。使用边界为±1、±2和±3个标准差的个体控制图来检查时间模式,并辅以探索性简单线性回归来估计整个网络、不包括洛迦诺医院(ODL)的网络和单独的ODL的总体线性趋势。结果:在整个网络中,报告的攻击行为总体呈上升趋势,2024年达到最高水平。当通过住院活动和出院进行标准化时,这两个指标在网络水平上显示出增加的轨迹。相比之下,ODL侵略率从2018年到2021年有所上升,随后到2024年连续下降。每1000个住院日的攻击次数从2021年的1.32次下降到2024年的0.78次。这种时间模式不同于在网络其余部分观察到的持续上升的模式。2017-2024年期间的探索性线性回归没有显示出ODL的统计显着总体线性趋势。2022-2024年报告的大多数事件是由患者实施的,护理人员是受影响最大的专业群体,老年病房占报告的比例最大。结论:本研究通过采用网络层面的视角、更长的观察期和统计过程控制知情的视觉方法,扩展了以往的单一医院证据。研究结果表明,在具有可比性的医院环境中,攻击倾向可能并不一致。虽然因果推理是不可能的,但在ODL观察到的独特的时间模式产生了关于可能与工作场所暴力轨迹差异相关的组织和环境因素的假设,值得进一步调查。使用标准化指标的持续监测可以支持组织学习、基准制定和有针对性的预防。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Understanding Workplace Violence in Healthcare: Insights from an Eight-Year Case Study in a Swiss Hospital Network.

Background: Workplace violence against healthcare workers is a growing concern worldwide, with consequences for staff well-being, care quality, and patient safety. However, longitudinal evidence from hospital networks remains limited, and few studies have used statistical process control-informed visual methods to monitor trends over time. This study examined whether reported aggression trends showed distinct temporal patterns across a Swiss public hospital network and whether such patterns could generate hypotheses regarding potentially associated organizational and contextual factors.

Methods: We conducted a retrospective observational study of reported aggressions toward healthcare staff across the Ente Ospedaliero Cantonale (EOC), the public hospital network of southern Switzerland, over an eight-year period (2017-2024). Data were extracted from the network's internal quality and occupational safety reporting platform. Two standardized indicators were calculated annually for each hospital: aggressions per 1,000 inpatient days and aggressions per 1,000 discharges. Individual control charts with boundaries at ± 1, ±2, and ±3 standard deviations were used to examine temporal patterns, complemented by exploratory simple linear regression to estimate overall linear trends across the full network, the network excluding Locarno Hospital (ODL), and ODL alone.

Results: Across the network, reported aggressions showed an overall upward pattern, with the highest levels recorded in 2024. When standardized by inpatient activity and discharges, both indicators showed increasing trajectories at network level. In contrast, at ODL aggression rates increased from 2018 to 2021, followed by consecutive annual decreases through 2024. Aggressions per 1,000 inpatient days decreased from 1.32 in 2021 to 0.78 in 2024. This temporal pattern differed from the continuing upward pattern observed across the rest of the network. Exploratory linear regression over the full 2017-2024 period did not show statistically significant overall linear trends at ODL. Most reported incidents in 2022-2024 were perpetrated by patients, nursing staff were the most affected professional group, and geriatric units accounted for the largest proportion of reports.

Conclusions: This study extends previous single-hospital evidence by adopting a network-level perspective, a longer observation period, and statistical process control-informed visual methods. The findings suggest that aggression trends may not be uniform across comparable hospital settings. Although causal inference is not possible, the distinct temporal pattern observed at ODL generates hypotheses regarding organizational and contextual factors potentially associated with differences in workplace violence trajectories and warrants further investigation. Continuous monitoring using standardized indicators may support organizational learning, benchmarking, and targeted prevention.

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