交通模式和紧急医疗服务在创伤激活中的预通知运输估计。

IF 1.5 Q3 EMERGENCY MEDICINE
Open Access Emergency Medicine Pub Date : 2024-11-29 eCollection Date: 2024-01-01 DOI:10.2147/OAEM.S480081
Sophia Gorgens, Ella R Rastegar, Manuel Beltran Del Rio, Cristy Meyer, Daniel M Rolston, Maria Sfakianos, Eric N Klein, Timmy Li, Rashmeet Gujral, Matthew A Bank, Daniel Jafari
{"title":"交通模式和紧急医疗服务在创伤激活中的预通知运输估计。","authors":"Sophia Gorgens, Ella R Rastegar, Manuel Beltran Del Rio, Cristy Meyer, Daniel M Rolston, Maria Sfakianos, Eric N Klein, Timmy Li, Rashmeet Gujral, Matthew A Bank, Daniel Jafari","doi":"10.2147/OAEM.S480081","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>To determine whether traffic patterns affect the accuracy of emergency medical services (EMS) prediction of transport interval to the emergency department (ED).</p><p><strong>Methods: </strong>Using a retrospective study, we examined all trauma activations at a level one, urban trauma center in Manhasset, New York, between 5/22/2021 and 3/30/2022. Inclusion criteria included patients ≥18 years and arrival by EMS. Field trauma activations involve prenotification communication through a government intermediary. Transport during \"peak hours\" was defined as hospital arrival of EMS between 06:00-10:00 and 16:00-20:00, Monday through Friday. ETI and actual transit interval (ATI) were extracted from the recorded prenotification calls and hospital records respectively. In instances with a time range, the arithmetic mean was used. ATI was defined as the time from prenotification call to arrival at the hospital. A 25% difference between EMS ETI and ATI was chosen to categorize each arrival as overestimated (ATI/ETI < 0.75), accurate (ATI/ETI within 0.75-1.25), and underestimated (ATI/ETI > 1.25). Fisher's exact and Wilcoxon Rank Sum tests were used for comparative analysis as appropriate.</p><p><strong>Results: </strong>Of the 369 trauma transports, 117 had prenotification reports with an ETI and were included in our analysis. Of those, 29 (25%) occurred during peak hours. Overall, EMS more often underestimated ETI (55%) than exactly (32%), or overestimated ETI (12%) (p<0.0001). This was true during peak and off-peak hours with underestimated, accurate, and overestimated arrivals being 59%, 31%, 10% (p<0.01); and 54%, 33%, 12% (p<0.001), respectively. There was no statistically significant difference between peak vs off-peak hours when comparing the proportion of under vs over-estimated times of arrival (p=0.263).</p><p><strong>Conclusion: </strong>While our hypothesis was not borne out, further research on the antecedents of underestimated transport intervals in traumas is warranted. This will allow for targeted solutions to best support EMS clinicians in communicating transport times back to the ED.</p>","PeriodicalId":45096,"journal":{"name":"Open Access Emergency Medicine","volume":"16 ","pages":"297-303"},"PeriodicalIF":1.5000,"publicationDate":"2024-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11613700/pdf/","citationCount":"0","resultStr":"{\"title\":\"Traffic Patterns and Emergency Medical Services Prenotification Transport Estimates in Trauma Activations.\",\"authors\":\"Sophia Gorgens, Ella R Rastegar, Manuel Beltran Del Rio, Cristy Meyer, Daniel M Rolston, Maria Sfakianos, Eric N Klein, Timmy Li, Rashmeet Gujral, Matthew A Bank, Daniel Jafari\",\"doi\":\"10.2147/OAEM.S480081\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>To determine whether traffic patterns affect the accuracy of emergency medical services (EMS) prediction of transport interval to the emergency department (ED).</p><p><strong>Methods: </strong>Using a retrospective study, we examined all trauma activations at a level one, urban trauma center in Manhasset, New York, between 5/22/2021 and 3/30/2022. Inclusion criteria included patients ≥18 years and arrival by EMS. Field trauma activations involve prenotification communication through a government intermediary. Transport during \\\"peak hours\\\" was defined as hospital arrival of EMS between 06:00-10:00 and 16:00-20:00, Monday through Friday. ETI and actual transit interval (ATI) were extracted from the recorded prenotification calls and hospital records respectively. In instances with a time range, the arithmetic mean was used. ATI was defined as the time from prenotification call to arrival at the hospital. A 25% difference between EMS ETI and ATI was chosen to categorize each arrival as overestimated (ATI/ETI < 0.75), accurate (ATI/ETI within 0.75-1.25), and underestimated (ATI/ETI > 1.25). Fisher's exact and Wilcoxon Rank Sum tests were used for comparative analysis as appropriate.</p><p><strong>Results: </strong>Of the 369 trauma transports, 117 had prenotification reports with an ETI and were included in our analysis. Of those, 29 (25%) occurred during peak hours. Overall, EMS more often underestimated ETI (55%) than exactly (32%), or overestimated ETI (12%) (p<0.0001). This was true during peak and off-peak hours with underestimated, accurate, and overestimated arrivals being 59%, 31%, 10% (p<0.01); and 54%, 33%, 12% (p<0.001), respectively. There was no statistically significant difference between peak vs off-peak hours when comparing the proportion of under vs over-estimated times of arrival (p=0.263).</p><p><strong>Conclusion: </strong>While our hypothesis was not borne out, further research on the antecedents of underestimated transport intervals in traumas is warranted. This will allow for targeted solutions to best support EMS clinicians in communicating transport times back to the ED.</p>\",\"PeriodicalId\":45096,\"journal\":{\"name\":\"Open Access Emergency Medicine\",\"volume\":\"16 \",\"pages\":\"297-303\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2024-11-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11613700/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Open Access Emergency Medicine\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2147/OAEM.S480081\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q3\",\"JCRName\":\"EMERGENCY MEDICINE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Open Access Emergency Medicine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2147/OAEM.S480081","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q3","JCRName":"EMERGENCY MEDICINE","Score":null,"Total":0}
引用次数: 0

摘要

目的:探讨交通模式是否影响急诊医疗服务(EMS)对急诊科(ED)转运间隔预测的准确性。方法:采用回顾性研究,我们检查了2021年5月22日至2022年3月30日期间纽约曼哈塞特一级城市创伤中心的所有创伤激活情况。纳入标准为患者≥18岁,EMS到达。战地创伤激活涉及通过政府中介机构进行预先通报。“高峰时段”的运输被定义为周一至周五06:00-10:00和16:00-20:00之间的EMS到达医院。ETI和实际传输间隔(ATI)分别从记录的通知呼叫和医院记录中提取。在有时间范围的情况下,使用算术平均值。ATI定义为从预先通知电话到到达医院的时间。选择EMS ETI和ATI之间25%的差异将每个到达分类为高估(ATI/ETI < 0.75),准确(ATI/ETI在0.75-1.25之间)和低估(ATI/ETI > 1.25)。适当时采用Fisher精确检验和Wilcoxon秩和检验进行比较分析。结果:在369例创伤运输中,117例有ETI的预通知报告,并纳入我们的分析。其中29例(25%)发生在高峰时段。总的来说,EMS往往低估了ETI(55%),而不是准确地(32%),或高估了ETI(12%)。(结论:虽然我们的假设没有得到证实,但对创伤中低估转运间隔的前因的进一步研究是有必要的。这将允许有针对性的解决方案,以最好地支持EMS临床医生将运输时间传回急诊室。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Traffic Patterns and Emergency Medical Services Prenotification Transport Estimates in Trauma Activations.

Objective: To determine whether traffic patterns affect the accuracy of emergency medical services (EMS) prediction of transport interval to the emergency department (ED).

Methods: Using a retrospective study, we examined all trauma activations at a level one, urban trauma center in Manhasset, New York, between 5/22/2021 and 3/30/2022. Inclusion criteria included patients ≥18 years and arrival by EMS. Field trauma activations involve prenotification communication through a government intermediary. Transport during "peak hours" was defined as hospital arrival of EMS between 06:00-10:00 and 16:00-20:00, Monday through Friday. ETI and actual transit interval (ATI) were extracted from the recorded prenotification calls and hospital records respectively. In instances with a time range, the arithmetic mean was used. ATI was defined as the time from prenotification call to arrival at the hospital. A 25% difference between EMS ETI and ATI was chosen to categorize each arrival as overestimated (ATI/ETI < 0.75), accurate (ATI/ETI within 0.75-1.25), and underestimated (ATI/ETI > 1.25). Fisher's exact and Wilcoxon Rank Sum tests were used for comparative analysis as appropriate.

Results: Of the 369 trauma transports, 117 had prenotification reports with an ETI and were included in our analysis. Of those, 29 (25%) occurred during peak hours. Overall, EMS more often underestimated ETI (55%) than exactly (32%), or overestimated ETI (12%) (p<0.0001). This was true during peak and off-peak hours with underestimated, accurate, and overestimated arrivals being 59%, 31%, 10% (p<0.01); and 54%, 33%, 12% (p<0.001), respectively. There was no statistically significant difference between peak vs off-peak hours when comparing the proportion of under vs over-estimated times of arrival (p=0.263).

Conclusion: While our hypothesis was not borne out, further research on the antecedents of underestimated transport intervals in traumas is warranted. This will allow for targeted solutions to best support EMS clinicians in communicating transport times back to the ED.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Open Access Emergency Medicine
Open Access Emergency Medicine EMERGENCY MEDICINE-
CiteScore
2.60
自引率
6.70%
发文量
85
审稿时长
16 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信