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基于代理的模拟研究:调整风险政策以尽量减少大流行期间围手术期人员短缺

Risk-adjusted policies to minimise perioperative staffing shortages during a pandemic: An agent-based simulation study.

机构信息

Industrial and Systems Engineering and Engineering Management, The University of North Carolina at Charlotte, Charlotte, NC, USA.

Department of Anesthesiology, Prisma Health - Upstate, Greenville, SC, USA.

出版信息

Epidemiol Infect. 2023 Apr 3;151:e66. doi: 10.1017/S0950268823000511.

DOI:10.1017/S0950268823000511
PMID:37006137
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10154643/
Abstract

Healthcare workers' (HCWs) safety and availability to care for patients are critical during a pandemic such as the one caused by severe acute respiratory syndrome coronavirus 2. Among providers of different specialities, it is critical to protect those working in hospital settings with a high risk of infection. Using an agent-based simulation model, various staffing policies were developed and simulated for 90 days using data from the largest health systems in South Carolina. The model considers staffing policies that include geographic segregation, interpersonal contact limits, and a combination of factors, including the patient census, transmission rates, vaccination status of providers, hospital capacity, incubation time, quarantine period, and interactions between patients and providers. Comparing the existing practices to various risk-adjusted staffing policies, model predictions show that restricted teaming and rotating schedules significantly (-value <0.01) reduced weekly HCW unavailability and the number of infected HCWs by 22% and 38%, respectively, when the vaccination rates among HCWs were lower (<75%). However, as the vaccination rate increases, the benefits of risk-adjusted policies diminish; and when 90% of HCWs were vaccinated, there were no significant (-value = 0.09) benefits. Although these simulated outcomes are specific to one health system, our findings can be generalised to other health systems with multiple locations.

摘要

医护人员(HCWs)的安全和为患者提供护理的能力在像由严重急性呼吸综合征冠状病毒 2 引起的大流行期间至关重要。在不同专业的提供者中,保护那些在感染风险高的医院环境中工作的人至关重要。本研究使用基于代理的仿真模型,根据南卡罗来纳州最大的卫生系统的数据,制定并模拟了 90 天的各种人员配备政策。该模型考虑了包括地理隔离、人际接触限制以及包括患者普查、传播率、医护人员疫苗接种状况、医院容量、潜伏期、隔离期和患者与医护人员之间的相互作用等因素在内的人员配备政策。将现有做法与各种风险调整人员配备政策进行比较,模型预测表明,当医护人员的疫苗接种率较低(<75%)时,限制团队合作和轮班计划可分别显著(-值<0.01)减少每周 HCW 缺勤人数和感染 HCW 人数 22%和 38%。然而,随着疫苗接种率的提高,风险调整政策的益处会减少;当 90%的 HCWs 接种疫苗时,就没有显著的(-值=0.09)益处。尽管这些模拟结果是针对一个卫生系统的,但我们的发现可以推广到具有多个地点的其他卫生系统。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4571/10154643/2a5984843a1c/S0950268823000511_fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4571/10154643/ee14d796a60f/S0950268823000511_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4571/10154643/2a5984843a1c/S0950268823000511_fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4571/10154643/ee14d796a60f/S0950268823000511_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4571/10154643/2a5984843a1c/S0950268823000511_fig3.jpg

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