Chaitawat Wantaka, Prasong Kitidumrongsuk, P. Soontornpipit, Jutatip Sillabutra
{"title":"冲程快速跟踪系统数据模型的设计与开发","authors":"Chaitawat Wantaka, Prasong Kitidumrongsuk, P. Soontornpipit, Jutatip Sillabutra","doi":"10.1109/IEECON.2018.8712241","DOIUrl":null,"url":null,"abstract":"This study aimed to design and develop two data sets that could better manage acute ischemic stroke patients. The cases were focused on the acute ischemic stroke who presented a stroke FAST track sign to thrombolytic treatment. As the staffs were needed to follow their treatment processes and protocols within the timeline, they required patient data on hand and the seamless communication must be provided. However, the existing system was barely to meet those requirements as it always has the gap between paper-base and electronic-base systems. In order to design the new data sets, the stakeholders related to the stroke FAST track system were analyzed and interviewed. The whole processes and protocols were carefully considered. In addition, after reviewing and analyzing the clinical practice guidelines (CPGs) and workflow for stroke FAST track, this study designed the new workflow and developed 2 models. The first data set was a simple model for partially improve stored stroke FAST track in the case of hospital field. The second model was designed for interoperability from mobile application and electronics referral data. Later the data sets for both models were presented back to the stakeholder for verifying the database used in hospitals.","PeriodicalId":6628,"journal":{"name":"2018 International Electrical Engineering Congress (iEECON)","volume":"101 1","pages":"1-4"},"PeriodicalIF":0.0000,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Design and Development of Data Model for Stroke FAST Track System\",\"authors\":\"Chaitawat Wantaka, Prasong Kitidumrongsuk, P. Soontornpipit, Jutatip Sillabutra\",\"doi\":\"10.1109/IEECON.2018.8712241\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study aimed to design and develop two data sets that could better manage acute ischemic stroke patients. The cases were focused on the acute ischemic stroke who presented a stroke FAST track sign to thrombolytic treatment. As the staffs were needed to follow their treatment processes and protocols within the timeline, they required patient data on hand and the seamless communication must be provided. However, the existing system was barely to meet those requirements as it always has the gap between paper-base and electronic-base systems. In order to design the new data sets, the stakeholders related to the stroke FAST track system were analyzed and interviewed. The whole processes and protocols were carefully considered. In addition, after reviewing and analyzing the clinical practice guidelines (CPGs) and workflow for stroke FAST track, this study designed the new workflow and developed 2 models. The first data set was a simple model for partially improve stored stroke FAST track in the case of hospital field. The second model was designed for interoperability from mobile application and electronics referral data. Later the data sets for both models were presented back to the stakeholder for verifying the database used in hospitals.\",\"PeriodicalId\":6628,\"journal\":{\"name\":\"2018 International Electrical Engineering Congress (iEECON)\",\"volume\":\"101 1\",\"pages\":\"1-4\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 International Electrical Engineering Congress (iEECON)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IEECON.2018.8712241\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Electrical Engineering Congress (iEECON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEECON.2018.8712241","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Design and Development of Data Model for Stroke FAST Track System
This study aimed to design and develop two data sets that could better manage acute ischemic stroke patients. The cases were focused on the acute ischemic stroke who presented a stroke FAST track sign to thrombolytic treatment. As the staffs were needed to follow their treatment processes and protocols within the timeline, they required patient data on hand and the seamless communication must be provided. However, the existing system was barely to meet those requirements as it always has the gap between paper-base and electronic-base systems. In order to design the new data sets, the stakeholders related to the stroke FAST track system were analyzed and interviewed. The whole processes and protocols were carefully considered. In addition, after reviewing and analyzing the clinical practice guidelines (CPGs) and workflow for stroke FAST track, this study designed the new workflow and developed 2 models. The first data set was a simple model for partially improve stored stroke FAST track in the case of hospital field. The second model was designed for interoperability from mobile application and electronics referral data. Later the data sets for both models were presented back to the stakeholder for verifying the database used in hospitals.