Emergency Response Community Effectiveness: A simulation modeler for comparing Emergency Medical Services with smartphone-based Samaritan response
Emergency Response Community Effectiveness: A simulation modeler for comparing Emergency Medical Services with smartphone-based Samaritan response
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DOI：
10.1016/j.dss.2017.07.003
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发表时间：
2017-10-01
影响因子：
7.5
通讯作者：
Schwartz, David G.
中科院分区：
文献类型：
--
作者：
Khalemsky, Michael;Schwartz, David G.
移动的紧急响应应用程序涉及基于位置的警报和联网成员的物理响应，越来越多地出现在智能手机上，以解决各种紧急情况。EMS（紧急医疗服务）管理员，政策制定者和其他决策者需要确定这些系统何时能有效地补充传统的紧急医疗服务。我们开发了一个软件工具，紧急响应社区有效性建模器（ERCEM），接受参数，并比较潜在的智能手机发起的撒玛利亚人/成员响应传统EMS响应特定的医疗条件在给定的地理区域。本研究使用国家EMS信息系统（NEMSIS）的EMS数据，并根据城乡通勤区（RUCA）和经济研究服务（ERS）的城市化代码进行地理分析。为了证明ERCEM的能力，我们输入了一整年的NEMSIS数据，记录了美国各地的EMS响应事件。我们进行了三个实验，以探索不同人口密度特征的过敏反应，低血糖和阿片类药物过量事件，并进一步排列以考虑一系列潜在的应用程序采用水平，撒玛利亚人响应行为，通知半径等。和人口密度是决定撒玛利亚应急响应社区（ERC）有效性的关键因素。我们展示了志愿者部署mHealth应用程序进行应急响应的有效性如何与EMS相比进行建模和研究。决策者可以利用ERCEM生成不同紧急响应场景的详细模拟，以评估基于智能手机的撒玛利亚响应应用程序在不同地理区域针对一系列不同条件和治疗的功效。(C)2017爱思唯尔B. V.保留所有权利。
Mobile emergency response applications involving location-based alerts and physical response of networked members increasingly appear on smartphones to address a variety of emergencies. EMS (Emergency Medical Services) administrators, policy makers, and other decision makers need to determine when such systems present an effective addition to traditional Emergency Medical Services. We developed a software tool, the Emergency Response Community Effectiveness Modeler (ERCEM) that accepts parameters and compares the potential smartphone-initiated Samaritan/member response to traditional EMS response for a specific medical condition in a given geographic area. This study uses EMS data from the National EMS Information System (NEMSIS) and analyses geographies based on Rural-Urban Commuting Area (RUCA) and Economic Research Service (ERS) urbanicity codes. To demonstrate ERCEM's capabilities, we input a full year of NEMSIS data documenting EMS response incidents across the USA. We conducted three experiments to explore anaphylaxis, hypoglycemia and opioid overdose events across different population density characteristics, with further permutations to consider a series of potential app adoption levels, Samaritan response behaviors, notification radii, etc. Our model emphasizes how medical condition, prescription adherence levels, community network membership, and population density are key factors in determining the effectiveness of Samaritan-based Emergency Response Communities (ERC). We show how the efficacy of deploying mHealth apps for emergency response by volunteers can be modelled and studied in comparison to EMS. A decision maker can utilize ERCEM to generate a detailed simulation of different emergency response scenarios to assess the efficacy of smartphone-based Samaritan response applications in varying geographic regions for a series of different conditions and treatments. (C) 2017 Elsevier B.V. All rights reserved.