{"title":"将医疗信息系统的电子学习扩展到一个简单的建议工具","authors":"P. Rajković, D. Jankovic, A. Milenković","doi":"10.1109/HealthCom.2016.7749473","DOIUrl":null,"url":null,"abstract":"Developing suggestion tools in the scope of health information systems can be a complex task, followed by a risk of not being accepted by the end users. Thus, we decide to start the implementation around the existing functionality. In this paper we present a case study showing the adaptation of e-learning medical information system extension to a set of simple suggestion tools. While some features of initial system had to be modified, the domain specific knowledge collected for the e-learning extension is used to suppress potential errors. Presented suggestion tool is based on highly configurable lists of pre-defined entities that can be easily selected, and after the verification from the medical practitioner, copied into an active visit. After four years of active use, and several iteration of update, described suggestion tools are mostly accepted among the general practitioners, especially within certain scenarios where faster medication prescription is a must.","PeriodicalId":167022,"journal":{"name":"2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Adaption of medical information system's e-learning extension to a simple suggestion tool\",\"authors\":\"P. Rajković, D. Jankovic, A. Milenković\",\"doi\":\"10.1109/HealthCom.2016.7749473\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Developing suggestion tools in the scope of health information systems can be a complex task, followed by a risk of not being accepted by the end users. Thus, we decide to start the implementation around the existing functionality. In this paper we present a case study showing the adaptation of e-learning medical information system extension to a set of simple suggestion tools. While some features of initial system had to be modified, the domain specific knowledge collected for the e-learning extension is used to suppress potential errors. Presented suggestion tool is based on highly configurable lists of pre-defined entities that can be easily selected, and after the verification from the medical practitioner, copied into an active visit. After four years of active use, and several iteration of update, described suggestion tools are mostly accepted among the general practitioners, especially within certain scenarios where faster medication prescription is a must.\",\"PeriodicalId\":167022,\"journal\":{\"name\":\"2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom)\",\"volume\":\"41 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HealthCom.2016.7749473\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HealthCom.2016.7749473","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Adaption of medical information system's e-learning extension to a simple suggestion tool
Developing suggestion tools in the scope of health information systems can be a complex task, followed by a risk of not being accepted by the end users. Thus, we decide to start the implementation around the existing functionality. In this paper we present a case study showing the adaptation of e-learning medical information system extension to a set of simple suggestion tools. While some features of initial system had to be modified, the domain specific knowledge collected for the e-learning extension is used to suppress potential errors. Presented suggestion tool is based on highly configurable lists of pre-defined entities that can be easily selected, and after the verification from the medical practitioner, copied into an active visit. After four years of active use, and several iteration of update, described suggestion tools are mostly accepted among the general practitioners, especially within certain scenarios where faster medication prescription is a must.