{"title":"移动电子分诊,通过众包和传感器检测信息改善应急反应","authors":"Liliya I. Besaleva, Alfred C. Weaver","doi":"10.1145/2534088.2534089","DOIUrl":null,"url":null,"abstract":"Emergency resources are often insufficient to satisfy fully the demands for professional help and supplies after a public disaster. Furthermore, in a mass casualty situation, the emphasis shifts from ensuring the best possible outcome for each individual patient to ensuring the best possible outcome for the greatest number of patients. Historically, various manual and electronic medical triage systems have been used both under civil and military conditions to determine the order and priority of emergency treatment, transport, and best possible destination for the patients [3][4][5]. Unfortunately, none of those solutions has proven flexible, accurate, scalable or unobtrusive enough to meet the public's expectations [1]. We demonstrate a system for real-time patient assessment which uses mobile electronic triaging accomplished via crowdsourced and sensor-detected information. With the use of our system, emergency management professionals receive most of the information they need for preparing themselves to perform a timely and accurate treatment of their patients even before dispatching a response team to the event. During our demonstration, we will show how our system behaves with different combinations of information inputs and compare its resulting outputs with evaluations done by medical experts. The public will be given the chance to participate in real-time demos by posing as victims and providing self-reported information about their health.","PeriodicalId":91386,"journal":{"name":"Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference)","volume":"93 1","pages":"10:1-10:2"},"PeriodicalIF":0.0000,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Mobile electronic triaging for emergency response improvement through crowdsourced and sensor-detected information\",\"authors\":\"Liliya I. Besaleva, Alfred C. Weaver\",\"doi\":\"10.1145/2534088.2534089\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Emergency resources are often insufficient to satisfy fully the demands for professional help and supplies after a public disaster. Furthermore, in a mass casualty situation, the emphasis shifts from ensuring the best possible outcome for each individual patient to ensuring the best possible outcome for the greatest number of patients. Historically, various manual and electronic medical triage systems have been used both under civil and military conditions to determine the order and priority of emergency treatment, transport, and best possible destination for the patients [3][4][5]. Unfortunately, none of those solutions has proven flexible, accurate, scalable or unobtrusive enough to meet the public's expectations [1]. We demonstrate a system for real-time patient assessment which uses mobile electronic triaging accomplished via crowdsourced and sensor-detected information. With the use of our system, emergency management professionals receive most of the information they need for preparing themselves to perform a timely and accurate treatment of their patients even before dispatching a response team to the event. During our demonstration, we will show how our system behaves with different combinations of information inputs and compare its resulting outputs with evaluations done by medical experts. The public will be given the chance to participate in real-time demos by posing as victims and providing self-reported information about their health.\",\"PeriodicalId\":91386,\"journal\":{\"name\":\"Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference)\",\"volume\":\"93 1\",\"pages\":\"10:1-10:2\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2534088.2534089\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2534088.2534089","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Mobile electronic triaging for emergency response improvement through crowdsourced and sensor-detected information
Emergency resources are often insufficient to satisfy fully the demands for professional help and supplies after a public disaster. Furthermore, in a mass casualty situation, the emphasis shifts from ensuring the best possible outcome for each individual patient to ensuring the best possible outcome for the greatest number of patients. Historically, various manual and electronic medical triage systems have been used both under civil and military conditions to determine the order and priority of emergency treatment, transport, and best possible destination for the patients [3][4][5]. Unfortunately, none of those solutions has proven flexible, accurate, scalable or unobtrusive enough to meet the public's expectations [1]. We demonstrate a system for real-time patient assessment which uses mobile electronic triaging accomplished via crowdsourced and sensor-detected information. With the use of our system, emergency management professionals receive most of the information they need for preparing themselves to perform a timely and accurate treatment of their patients even before dispatching a response team to the event. During our demonstration, we will show how our system behaves with different combinations of information inputs and compare its resulting outputs with evaluations done by medical experts. The public will be given the chance to participate in real-time demos by posing as victims and providing self-reported information about their health.