Modelling emergency response times for Out-of-Hospital Cardiac Arrest (OHCA) patients in rural areas of the North of England using routinely collected data.

IF 2.3 3区 医学 Q1 EMERGENCY MEDICINE BMC Emergency Medicine Pub Date : 2025-01-11 DOI:10.1186/s12873-025-01170-7
Megan Harries, Anastasia Ushakova
{"title":"Modelling emergency response times for Out-of-Hospital Cardiac Arrest (OHCA) patients in rural areas of the North of England using routinely collected data.","authors":"Megan Harries, Anastasia Ushakova","doi":"10.1186/s12873-025-01170-7","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>National response time targets for ambulance services are known to be more strongly maintained in urban areas compared to rural. That may mean that responses in rural areas could be less immediate which can in turn affect survival of those experiencing cardiac arrest. Thus, analysis of variation in response times using routinely collected data can be used to understand which rural areas have the highest need for emergency intervention. In this study we have focused, given the heterogeneity of demographic make up, on a specific area of the North of England. Some areas in North England have shown to have a large proportion of cardiac arrests occurring in a rural setting, specifically, in the anonymised study region this was almost half of the cases at 46.3%. Response times to these areas were found to be over 3.5 minutes slower than for urban areas making it worthy of further exploration.</p><p><strong>Methods: </strong>A retrospective observation analysis was conducted on routinely collected data from regional ambulance services for areas within the North of England from April 2016 to March 2021. Information was collected on service and geographic characteristics for 1915 incidents. A multivariable linear mixed effect regression model was used to understand the association between geographical, service factors and response times to cardiac arrest patients. To advance previous research which up to now only used visualisations to analyse ambulance response times, the study used a mixed effects model with a variety of predictors, capturing geographical variation alongside service characteristics.</p><p><strong>Results: </strong>From the cases analysed it was found that the mean response time to scene was 9.1 minutes, with a standard deviation of 6.4 minutes. After adjustment for geographic variation and incorporating robust standard errors into the model: distance to the nearest ambulance station (coefficient = 0.61, 95% confidence interval [CI]: 0.56-0.66), urgency of the call (Category 2, second most urgent, compared to the most urgent coefficient = 1.66, 95% CI: 1.13 - 2.18), location of the nearest ambulance station to the incident and the type of crew who attended the incident (Advanced Paramedic when compared to just Paramedic, coefficient = -0.70, 95% CI: -1.24 - -0.16) were all factors which affected response times to scene.</p><p><strong>Conclusion: </strong>For each extra km the incident was away from an ambulance station, the response time to scene increased by 37 seconds. The ambulance station which displayed the largest increase in response time, Station L was 170 seconds (95% CI: 79, 261) longer than Station N, which had a median performance across all stations, as measured by median survival rate to return of spontaneous circulation (ROSC). The rural geography of the North of England means that lots of cardiac arrest incidents occur a considerable distance away from the stations, emphasising the need to use alternative emergency services technologies within these rural areas to attend to patients sooner.</p>","PeriodicalId":9002,"journal":{"name":"BMC Emergency Medicine","volume":"25 1","pages":"8"},"PeriodicalIF":2.3000,"publicationDate":"2025-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11724540/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"BMC Emergency Medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s12873-025-01170-7","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"EMERGENCY MEDICINE","Score":null,"Total":0}
引用次数: 0

Abstract

Background: National response time targets for ambulance services are known to be more strongly maintained in urban areas compared to rural. That may mean that responses in rural areas could be less immediate which can in turn affect survival of those experiencing cardiac arrest. Thus, analysis of variation in response times using routinely collected data can be used to understand which rural areas have the highest need for emergency intervention. In this study we have focused, given the heterogeneity of demographic make up, on a specific area of the North of England. Some areas in North England have shown to have a large proportion of cardiac arrests occurring in a rural setting, specifically, in the anonymised study region this was almost half of the cases at 46.3%. Response times to these areas were found to be over 3.5 minutes slower than for urban areas making it worthy of further exploration.

Methods: A retrospective observation analysis was conducted on routinely collected data from regional ambulance services for areas within the North of England from April 2016 to March 2021. Information was collected on service and geographic characteristics for 1915 incidents. A multivariable linear mixed effect regression model was used to understand the association between geographical, service factors and response times to cardiac arrest patients. To advance previous research which up to now only used visualisations to analyse ambulance response times, the study used a mixed effects model with a variety of predictors, capturing geographical variation alongside service characteristics.

Results: From the cases analysed it was found that the mean response time to scene was 9.1 minutes, with a standard deviation of 6.4 minutes. After adjustment for geographic variation and incorporating robust standard errors into the model: distance to the nearest ambulance station (coefficient = 0.61, 95% confidence interval [CI]: 0.56-0.66), urgency of the call (Category 2, second most urgent, compared to the most urgent coefficient = 1.66, 95% CI: 1.13 - 2.18), location of the nearest ambulance station to the incident and the type of crew who attended the incident (Advanced Paramedic when compared to just Paramedic, coefficient = -0.70, 95% CI: -1.24 - -0.16) were all factors which affected response times to scene.

Conclusion: For each extra km the incident was away from an ambulance station, the response time to scene increased by 37 seconds. The ambulance station which displayed the largest increase in response time, Station L was 170 seconds (95% CI: 79, 261) longer than Station N, which had a median performance across all stations, as measured by median survival rate to return of spontaneous circulation (ROSC). The rural geography of the North of England means that lots of cardiac arrest incidents occur a considerable distance away from the stations, emphasising the need to use alternative emergency services technologies within these rural areas to attend to patients sooner.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
使用常规收集的数据对英格兰北部农村地区院外心脏骤停(OHCA)患者的紧急响应时间进行建模。
背景:众所周知,与农村地区相比,城市地区更能强有力地维持救护车服务的国家反应时间目标。这可能意味着农村地区的反应可能不那么迅速,这反过来又会影响心脏骤停患者的生存。因此,利用常规收集的数据对反应时间的变化进行分析,可用于了解哪些农村地区最需要紧急干预。在这项研究中,考虑到人口构成的异质性,我们将重点放在英格兰北部的一个特定地区。在英格兰北部的一些地区,有很大比例的心脏骤停发生在农村环境中,特别是在匿名研究地区,这几乎是一半的病例,为46.3%。这些地区的响应时间比城市地区慢3.5分钟以上,值得进一步探索。方法:对2016年4月至2021年3月英格兰北部地区区域救护车服务常规收集数据进行回顾性观察分析。收集了1915年事件的服务和地理特征信息。采用多变量线性混合效应回归模型了解地理、服务因素与心脏骤停患者反应时间之间的关系。为了推进之前的研究,到目前为止只使用可视化来分析救护车反应时间,该研究使用了具有多种预测因子的混合效应模型,捕捉了地理差异和服务特征。结果:从病例分析中发现,对现场的平均反应时间为9.1分钟,标准差为6.4分钟。在调整地理差异并将稳健标准误差纳入模型后:到最近救护站的距离(系数= 0.61,95%置信区间[CI]: 0.56-0.66),呼叫的紧急程度(第2类,第二紧急,与最紧急系数= 1.66相比,95% CI:1.13 - 2.18)、离事故最近的救护站的位置以及参加事故的人员类型(高级护理人员与普通护理人员相比,系数= -0.70,95% CI: -1.24 - -0.16)都是影响现场响应时间的因素。结论:事故距离救护站每多一公里,对现场的反应时间就会增加37秒。反应时间增加最多的救护站,L站比N站长170秒(95% CI: 79, 261), N站在所有站点中表现中位数,以自然循环恢复的中位存活率(ROSC)衡量。英格兰北部的农村地理位置意味着许多心脏骤停事件发生在离车站相当远的地方,强调需要在这些农村地区使用替代紧急服务技术来更快地照顾病人。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
BMC Emergency Medicine
BMC Emergency Medicine Medicine-Emergency Medicine
CiteScore
3.50
自引率
8.00%
发文量
178
审稿时长
29 weeks
期刊介绍: BMC Emergency Medicine is an open access, peer-reviewed journal that considers articles on all urgent and emergency aspects of medicine, in both practice and basic research. In addition, the journal covers aspects of disaster medicine and medicine in special locations, such as conflict areas and military medicine, together with articles concerning healthcare services in the emergency departments.
期刊最新文献
Construction and evaluation of a triage assessment model for patients with acute non-traumatic chest pain: mixed retrospective and prospective observational study. Design and psychometric testing of a moral intelligence instrument for pre-hospital emergency medical services personnel: a sequential-exploratory mixed-method study. Empowerment of volunteer nursing service providers during disasters: A qualitative study. Enhancing trauma triage in low-resource settings using machine learning: a performance comparison with the Kampala Trauma Score. Incidence and outcomes of dysnatremia in crush injury patients admitted to Türkiye's largest hospital following the Kahramanmaraş earthquake.
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1