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集中救护车目的地决策:一项回顾性数据分析,旨在确定其对 EMS 系统分布、高峰事件和转院状态的影响。

Centralized Ambulance Destination Determination: A Retrospective Data Analysis to Determine Impact on EMS System Distribution, Surge Events, and Diversion Status.

机构信息

University of California, San Francisco, Department of Emergency Medicine, San Francisco, California.

San Francisco Emergency Medical Services Agency, San Francisco, California.

出版信息

West J Emerg Med. 2021 Oct 26;22(6):1311-1316. doi: 10.5811/westjem.2021.8.53198.

Abstract

INTRODUCTION

Emergency medical services (EMS) systems can become impacted by sudden surges that can occur throughout the day, as well as by natural disasters and the current pandemic. Because of this, emergency department crowding and ambulance "bunching," or surges in ambulance-transported patients at receiving hospitals, can have a detrimental effect on patient care and financial implications for an EMS system. The Centralized Ambulance Destination Determination (CAD-D) project was initially created as a pilot project to look at the impact of an active, online base hospital physician and paramedic supervisor to direct patient destination and distribution, as a way to improve ambulance distribution, decrease surges at hospitals, and decrease diversion status.

METHODS

The project was initiated March 17, 2020, with a six-week baseline period; it had three additional study phases where the CAD-D was recommended (Phase 1), mandatory (Phase 2), and modified (Phase 3), respectively. We used coefficients of variation (CV) statistical analysis to measure the relative variability between datasets (eg, CAD-D phases), with a lower variation showing better and more even distribution across the different hospitals. We used analysis of co-variability for the CV to determine whether level loading was improved systemwide across the three phases against the baseline period. The primary outcomes of this study were the following: to determine the impact of ambulance distribution across a geographical area by using the CV; to determine whether there was a decrease in surge rates at the busiest hospital in this area; and the effects on diversion.

RESULTS

We calculated the CV of all ratios and used them as a measure of EMS patient distribution among hospitals. Mean CV was lower in Phase 2 as compared to baseline (1.56 vs 0.80 P < 0.05), and to baseline and Phase 3 (1.56 vs. 0.93, P <0.05). A lower CV indicates better distribution across more hospitals, instead of the EMS transports bunching at a few hospitals. Furthermore, the proportion of surge events was shown to be lower between baseline and Phase 1 (1.43 vs 0.77, P <0.05), baseline and Phase 2 (1.43 vs. 0.33, P < 0.05), and baseline and Phase 3 (1.43 vs 0.42, P < 0.05). Diversion was shown to increase over the system as a whole, despite decreased diversion rates at the busiest hospital in the system.

CONCLUSION

In this retrospective study, we found that ambulance distribution increased across the system with the implementation of CAD-D, leading to better level loading. The surge rates decreased at some of the most impacted hospitals, while the rates of hospitals going on diversion paradoxically increased overall. Specifically, the results of this study showed that there was an improvement when comparing the CAD-D implementation vs the baseline period for both the ambulance distribution across the system (level loading/CV), and for surge events at three of the busiest hospitals in the system.

摘要

介绍

紧急医疗服务(EMS)系统可能会受到全天突发情况以及自然灾害和当前大流行的影响。因此,急诊科拥挤和救护车“集中”,或接收医院的救护车转运患者激增,会对患者护理和 EMS 系统的财务产生不利影响。集中救护车目的地确定(CAD-D)项目最初是作为一个试点项目创建的,目的是研究积极的在线基地医院医生和护理人员主管指导患者目的地和分配的效果,以改善救护车分配,减少医院拥堵,并减少转移状态。

方法

该项目于 2020 年 3 月 17 日启动,为期六周的基线期;它有三个额外的研究阶段,分别是 CAD-D 被推荐(阶段 1)、强制(阶段 2)和修改(阶段 3)。我们使用变异系数(CV)统计分析来衡量数据集(例如 CAD-D 阶段)之间的相对变化,变化越小表明分布在不同医院之间的效果更好且更均匀。我们使用共变分析来确定 CV 中是否在整个三个阶段相对于基线期提高了系统范围内的水平加载。本研究的主要结果如下:通过 CV 确定地理区域内救护车分布的影响;确定该地区最繁忙医院的拥堵率是否降低;以及对转移的影响。

结果

我们计算了所有比率的 CV,并将其用作衡量医院间 EMS 患者分布的指标。与基线相比,第二阶段的平均 CV 较低(1.56 与 0.80,P <0.05),与基线和第三阶段相比也是如此(1.56 与 0.93,P <0.05)。较低的 CV 表示在更多的医院中分布更好,而不是 EMS 运输集中在少数几家医院。此外,与基线相比,基线和第一阶段(1.43 与 0.77,P <0.05),基线和第二阶段(1.43 与 0.33,P <0.05),以及基线和第三阶段(1.43 与 0.42,P <0.05)之间的突发事件比例显示较低。尽管系统中最繁忙的医院的转移率下降,但整个系统的转移率却显示出增加的趋势。

结论

在这项回顾性研究中,我们发现随着 CAD-D 的实施,整个系统的救护车分布增加,从而实现更好的水平加载。在一些受影响最大的医院,拥堵率有所下降,而转诊率却反常地增加。具体来说,与基线期相比,这项研究的结果表明,在系统中比较 CAD-D 的实施情况时,无论是在系统内救护车分布(水平加载/CV)方面,还是在系统中三个最繁忙的医院的突发事件方面,都有了改善。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/278e/8597692/52ce15d46bb4/wjem-22-1311-g001.jpg

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