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开发一种分析工具,用于评估 EMS 系统设计变更及其对心脏骤停结局的影响:将地理信息系统与生存率登记数据相结合。

Developing an analytical tool for evaluating EMS system design changes and their impact on cardiac arrest outcomes: combining geographic information systems with register data on survival rates.

机构信息

Swedish Civil Contingencies Agency (MSB), Karlstad, Sweden.

出版信息

Scand J Trauma Resusc Emerg Med. 2013 Feb 15;21:8. doi: 10.1186/1757-7241-21-8.

DOI:10.1186/1757-7241-21-8
PMID:23415045
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3579715/
Abstract

BACKGROUND

Out-of-hospital cardiac arrest (OHCA) is a frequent and acute medical condition that requires immediate care. We estimate survival rates from OHCA in the area of Stockholm, through developing an analytical tool for evaluating Emergency Medical Services (EMS) system design changes. The study also is an attempt to validate the proposed model used to generate the outcome measures for the study.

METHODS AND RESULTS

This was done by combining a geographic information systems (GIS) simulation of driving times with register data on survival rates. The emergency resources comprised ambulance alone and ambulance plus fire services. The simulation model predicted a baseline survival rate of 3.9 per cent, and reducing the ambulance response time by one minute increased survival to 4.6 per cent. Adding the fire services as first responders (dual dispatch) increased survival to 6.2 per cent from the baseline level. The model predictions were validated using empirical data.

CONCLUSION

We have presented an analytical tool that easily can be generalized to other regions or countries. The model can be used to predict outcomes of cardiac arrest prior to investment in EMS design changes that affect the alarm process, e.g. (1) static changes such as trimming the emergency call handling time or (2) dynamic changes such as location of emergency resources or which resources should carry a defibrillator.

摘要

背景

院外心脏骤停(OHCA)是一种常见且急性的医疗状况,需要立即进行救治。我们通过开发一种评估紧急医疗服务(EMS)系统设计变更的分析工具,来估计斯德哥尔摩地区的 OHCA 存活率。该研究还试图验证用于生成研究结果衡量指标的建议模型。

方法和结果

这是通过将驾驶时间的地理信息系统(GIS)模拟与生存率的登记数据相结合来实现的。应急资源包括仅救护车和救护车加消防服务。模拟模型预测基础生存率为 3.9%,将救护车响应时间缩短一分钟可将生存率提高至 4.6%。将消防服务作为第一响应者(双重调度)可将生存率从基础水平提高至 6.2%。使用经验数据验证了模型预测。

结论

我们提出了一种易于推广到其他地区或国家的分析工具。该模型可用于预测心脏骤停的结果,然后再对影响报警流程的 EMS 设计变更进行投资,例如:(1)静态变更,如缩短紧急电话处理时间;或(2)动态变更,如应急资源的位置或哪些资源应携带除颤器。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f244/3579715/85e1d26c7356/1757-7241-21-8-5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f244/3579715/af4abd95bc6d/1757-7241-21-8-1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f244/3579715/3434a791585f/1757-7241-21-8-2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f244/3579715/724b92e3ff52/1757-7241-21-8-3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f244/3579715/7681167722c3/1757-7241-21-8-4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f244/3579715/85e1d26c7356/1757-7241-21-8-5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f244/3579715/af4abd95bc6d/1757-7241-21-8-1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f244/3579715/3434a791585f/1757-7241-21-8-2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f244/3579715/724b92e3ff52/1757-7241-21-8-3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f244/3579715/7681167722c3/1757-7241-21-8-4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f244/3579715/85e1d26c7356/1757-7241-21-8-5.jpg

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