Using discrete event computer simulation to improve patient flow in a Ghanaian acute care hospital
Using discrete event computer simulation to improve patient flow in a Ghanaian acute care hospital
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DOI：
10.1016/j.ajem.2014.05.012
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发表时间：
2014-08-01
影响因子：
3.6
通讯作者：
Ward, Michael J.
中科院分区：
文献类型：
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作者：
Best, Allyson M.;Dixon, Cinnamon A.;Ward, Michael J.
目标：拥挤和有限的资源增加了全世界急性护理机构和急诊科的压力。这些问题在发展中国家尤其普遍。离散事件模拟是一种基于计算机的工具，可用于估计复杂的医疗保健提供系统（如急诊室）的变化将如何影响运营绩效。使用这种模式，我们的目标是确定业务干预措施，可能会提高病人的吞吐量的一个急性护理设置在发展中国家。方法：我们开发了一个模拟模型，在加纳的一个区一级医院的急性护理测试的影响，资源中立（如，修改工作人员的开始时间和角色）和资源的额外（如，增加工作人员）的业务干预措施对病人的吞吐量。先前捕获的487例急性护理患者的去识别时间和运动数据用于开发和测试模型。主要结果是干预措施对患者住院时间（LOS）的模拟效果。结果：基础病例（无变化）方案的平均LOS为292分钟（95%置信区间[CI]，291-293）。孤立地说，增加人员配备、改变人员角色和改变轮班时间并不影响患者的总体LOS。具体而言，增加2名登记工作人员、病史记录员和医生导致LOS减少23.8分钟（95% CI，22.3-25.3）。然而，当轮班开始时间与患者到达模式相协调时，潜在的平均LOS减少了96分钟（95% CI，94-98），同时结合工作人员角色（登记和病史采集），总体平均LOS减少152分钟（95%CI，150-154）。结论：通过离散事件模拟建模确定的资源中性干预措施有可能提高加纳市立医院的急性护理吞吐量。离散事件模拟提供了另一种方法，以确定潜在的有效干预措施，以改善病人流量在紧急和急性护理资源有限的设置。(C)2014爱思唯尔公司All rights reserved.
Objectives: Crowding and limited resources have increased the strain on acute care facilities and emergency departments worldwide. These problems are particularly prevalent in developing countries. Discrete event simulation is a computer-based tool that can be used to estimate how changes to complex health care delivery systems such as emergency departments will affect operational performance. Using this modality, our objective was to identify operational interventions that could potentially improve patient throughput of one acute care setting in a developing country.Methods: We developed a simulation model of acute care at a district level hospital in Ghana to test the effects of resource-neutral (eg, modified staff start times and roles) and resource-additional (eg, increased staff) operational interventions on patient throughput. Previously captured deidentified time-and-motion data from 487 acute care patients were used to develop and test the model. The primary outcome was the modeled effect of interventions on patient length of stay (LOS).Results: The base-case (no change) scenario had a mean LOS of 292 minutes (95% confidence interval [CI], 291-293). In isolation, adding staffing, changing staff roles, and varying shift times did not affect overall patient LOS. Specifically, adding 2 registration workers, history takers, and physicians resulted in a 23.8-minute (95% CI, 22.3-25.3) LOS decrease. However, when shift start times were coordinated with patient arrival patterns, potential mean LOS was decreased by 96 minutes (95% CI, 94-98), and with the simultaneous combination of staff roles (registration and history taking), there was an overall mean LOS reduction of 152 minutes (95% CI, 150-154).Conclusions: Resource-neutral interventions identified through discrete event simulation modeling have the potential to improve acute care throughput in this Ghanaian municipal hospital. Discrete event simulation offers another approach to identifying potentially effective interventions to improve patient flow in emergency and acute care in resource-limited settings. (C) 2014 Elsevier Inc. All rights reserved.