Hospitals as Complex Social Systems: Agent-Based Simulations of Hospital-Acquired Infections
Hospitals as Complex Social Systems: Agent-Based Simulations of Hospital-Acquired Infections
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医院作为复杂的社会系统：基于代理的医院获得性感染模拟
DOI：
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发表时间：
2012
期刊：
影响因子：
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通讯作者：
S. Eubank
中科院分区：
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作者：
J. Jiménez;B. Lewis;S. Eubank
本研究的目的是开发一个高度详细的，基于代理的模拟，以比较医疗保健获得性感染（HAI）的药物治疗。一个复杂的医院模型是使用病人信息和医护人员数据从两个地区医院在弗吉尼亚州西南部。在其他HAI中选择一种特定的HAI（艰难梭菌）作为研究的病原体，因为其在美国的流行率增加。利用基于主体的仿真的基本原理，建立了复杂的医院仿真模型。然后使用具有两种不同场景的疾病模型对模拟进行测试：没有药物治疗抗菌剂的基线和使用抗菌剂（非达霉素）。该模型成功模拟了患者和医护人员之间超过164，000次的个人接触。每一种治疗都使用一个月的真实的医院数据进行了一百次评估。假设1的平均病例数为2.66例，假设2为2.33例。假设1的最高病例数为21例，而假设2最多为11例。了解患者和医院工作人员之间的复杂互动可以帮助医院了解感染的传播，同时降低医疗成本。
The objective of this study was to develop a highly-detailed, agent-based simulation to compare medical treatments against healthcare-acquired infections (HAIs). A complex hospital model was built using patient information and healthcare worker data from two regional hospitals in Southwest Virginia. A specific HAI, Clostridium difficile, was chosen among other HAIs as the pathogen for the study due to its increased prevalence in the United States. The complex hospital simulation was created using the first principles of agent-based simulation. The simulation was then tested using a disease model with two different scenarios: a baseline with no medical treatment antimicrobials, and the use of an antimicrobial (fidaxomicin). The model successfully simulated over 164,000 personal contacts between patients and healthcare workers. Each medical treatment was evaluated one hundred times using one month of real hospital data. The mean case count was 2.66 for scenario 1 and 2.33 for scenario 2. The highest case count for scenario 1 was 21 cases whereas scenario 2 had a maximum of 11 cases. Understanding complex interactions between patients and hospital personnel could help hospitals understand transmission of infections while simultaneously reducing healthcare costs.