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使用射频识别技术确定紧急医疗服务卸载时间。

Use of Radio Frequency Identification to Establish Emergency Medical Service Offload Times.

作者信息

Steer Sheila, Bhalla Mary C, Zalewski Jon, Frey Jennifer, Nguyen Victor, Mencl Francis

出版信息

Prehosp Emerg Care. 2016;20(2):254-9. doi: 10.3109/10903127.2015.1076093. Epub 2015 Sep 18.

Abstract

Emergency medical services (EMS) crews often wait for emergency department (ED) beds to become available to offload their patients. Presently there is no national benchmark for EMS turnaround or offload times, or method for objectively and reliably measuring this. This study introduces a novel method for monitoring offload times and identifying variance. We performed a descriptive, observational study in a large urban community teaching hospital. We affixed radio frequency identification (RFID) tags (Confidex Survivor™, Confidex, Inc., Glen Ellyn, IL) to 65 cots from 19 different EMS agencies and placed a reader (CaptureTech Weatherproof RFID Interpreter, Barcoding Inc., Baltimore, Maryland) in the ED ambulance entrance, allowing for passive recording of traffic. We recorded data for 16 weeks starting December 2009. Offload times were calculated for each visit and analyzed using STATA to show variations in individual and cumulative offload times based on the time of day and day of the week. Results are presented as median times, confidence intervals (CIs), and interquartile ranges (IQRs). We collected data on 2,512 visits. Five hundred and ninety-two were excluded because of incomplete data, leaving 1,920 (76%) complete visits. Average offload time was 13.2 minutes. Median time was 10.7 minutes (IQR 8.1 minutes to 15.4 minutes). A total of 43% of the patients (833/1,920, 95% CI 0.41-0.46) were offloaded in less than 10 minutes, while 27% (513/1,920, 95% CI 0.25-0.29) took greater than 15 minutes. Median times were longest on Mondays (11.5 minutes) and shortest on Wednesdays (10.3 minutes). Longest daily median offload time occurred between 1600 and 1700 (13.5 minutes), whereas the shortest median time was between 0800 and 0900 (9.3 minutes). Cumulative time spent waiting beyond 15 minutes totaled 72.5 hours over the study period. RFID monitoring is a simple and effective means of monitoring EMS traffic and wait times. At our institution, most squads are able to offload their patients within 15 minutes, with many in less than 10 minutes. Variations in wait times are seen and are a topic for future study.

摘要

紧急医疗服务(EMS)工作人员常常要等待急诊部(ED)有空床位才能将患者转运出去。目前,对于EMS周转或转运时间,尚无全国性的基准,也没有客观可靠的测量方法。本研究引入了一种监测转运时间和识别差异的新方法。我们在一家大型城市社区教学医院开展了一项描述性观察研究。我们将射频识别(RFID)标签(Confidex Survivor™,Confidex公司,伊利诺伊州 Glen Ellyn)贴在来自19个不同EMS机构的65张担架床上,并在急诊部救护车入口处放置了一个读取器(CaptureTech 防水RFID解释器,条形码公司,马里兰州巴尔的摩),以便被动记录流量。我们从2009年12月开始记录了16周的数据。计算每次就诊的转运时间,并使用STATA进行分析,以显示基于一天中的时间和一周中的日期的个体和累计转运时间的变化。结果以中位数时间、置信区间(CIs)和四分位间距(IQRs)表示。我们收集了2512次就诊的数据。由于数据不完整,排除了592次,剩下1920次(76%)完整就诊。平均转运时间为13.2分钟。中位数时间为10.7分钟(IQR为8.1分钟至15.4分钟)。共有43%的患者(833/1920,95%CI 0.41 - 0.46)在不到10分钟内被转运出去,而27%(513/1920,95%CI 0.25 - 0.29)的患者花费超过15分钟。中位数时间在周一最长(11.5分钟),在周三最短(10.3分钟)。每日最长中位数转运时间出现在16:00至17:00之间(13.5分钟),而最短中位数时间在08:00至09:00之间(9.3分钟)。在研究期间,等待超过15分钟的累计时间总计72.5小时。RFID监测是监测EMS流量和等待时间的一种简单有效的手段。在我们机构,大多数小队能够在15分钟内将患者转运出去,许多在不到10分钟内就能完成。等待时间存在差异,这是未来研究的一个课题。

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