探索和查询电子健康记录的交互式信息可视化

A. Rind, T. Wang, W. Aigner, S. Miksch, K. Wongsuphasawat, C. Plaisant, B. Shneiderman
{"title":"探索和查询电子健康记录的交互式信息可视化","authors":"A. Rind, T. Wang, W. Aigner, S. Miksch, K. Wongsuphasawat, C. Plaisant, B. Shneiderman","doi":"10.1561/1100000039","DOIUrl":null,"url":null,"abstract":"Physicians are confronted with increasingly complex patient histories based on which they must make life-critical treatment decisions. At the same time, clinical researchers are eager to study the growing databases of patient histories to detect unknown patterns, ensure quality control, and discover surprising outcomes. Designers of Electronic Health Record systems (EHRs) have great potential to apply innovative visual methods to support clinical decision-making and research. This work surveys the state-of-the-art of information visualization systems for exploring and querying EHRs, as described in the scientific literature. We examine how systems differ in their features and highlight how these differences are related to their design and the medical scenarios they tackle. The systems are compared on a set of criteria: (1) data types covered, (2) multivariate analysis support, (3) number of patient records used (one or multiple), and (4) user intents addressed. Based on our survey and evidence gained from evaluation studies, we believe that effective information visualization can facilitate analysis of EHRs for patient treatment and clinical research. Thus, we encourage the information visualization community to study the application of their systems in health care. Our monograph is written for both scientific researchers and designers of future user interfaces for EHRs. We hope it will help them understand this vital domain and appreciate the features and virtues of existing systems, so they can create still more advanced systems. We identify potential future research topics in interactive support for data abstraction, in systems for intermittent users, such as patients, and in more detailed evaluations.","PeriodicalId":126315,"journal":{"name":"Found. Trends Hum. Comput. Interact.","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"222","resultStr":"{\"title\":\"Interactive Information Visualization to Explore and Query Electronic Health Records\",\"authors\":\"A. Rind, T. Wang, W. Aigner, S. Miksch, K. Wongsuphasawat, C. Plaisant, B. Shneiderman\",\"doi\":\"10.1561/1100000039\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Physicians are confronted with increasingly complex patient histories based on which they must make life-critical treatment decisions. At the same time, clinical researchers are eager to study the growing databases of patient histories to detect unknown patterns, ensure quality control, and discover surprising outcomes. Designers of Electronic Health Record systems (EHRs) have great potential to apply innovative visual methods to support clinical decision-making and research. This work surveys the state-of-the-art of information visualization systems for exploring and querying EHRs, as described in the scientific literature. We examine how systems differ in their features and highlight how these differences are related to their design and the medical scenarios they tackle. The systems are compared on a set of criteria: (1) data types covered, (2) multivariate analysis support, (3) number of patient records used (one or multiple), and (4) user intents addressed. Based on our survey and evidence gained from evaluation studies, we believe that effective information visualization can facilitate analysis of EHRs for patient treatment and clinical research. Thus, we encourage the information visualization community to study the application of their systems in health care. Our monograph is written for both scientific researchers and designers of future user interfaces for EHRs. We hope it will help them understand this vital domain and appreciate the features and virtues of existing systems, so they can create still more advanced systems. We identify potential future research topics in interactive support for data abstraction, in systems for intermittent users, such as patients, and in more detailed evaluations.\",\"PeriodicalId\":126315,\"journal\":{\"name\":\"Found. Trends Hum. Comput. Interact.\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-02-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"222\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Found. Trends Hum. Comput. Interact.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1561/1100000039\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Found. Trends Hum. Comput. Interact.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1561/1100000039","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 222

摘要

医生面临着越来越复杂的病人病史,他们必须根据这些病史做出生死攸关的治疗决定。与此同时,临床研究人员渴望研究不断增长的患者病史数据库,以发现未知模式,确保质量控制,并发现令人惊讶的结果。电子健康记录系统(EHRs)的设计者有很大的潜力应用创新的视觉方法来支持临床决策和研究。这项工作调查了科学文献中描述的用于探索和查询电子病历的信息可视化系统的最新技术。我们研究了系统在功能上的差异,并强调了这些差异与它们的设计和它们所处理的医疗场景之间的关系。根据一组标准对这些系统进行比较:(1)涵盖的数据类型,(2)多变量分析支持,(3)使用的患者记录数量(一个或多个),以及(4)解决的用户意图。根据我们的调查和评估研究的证据,我们认为有效的信息可视化可以促进患者治疗和临床研究的电子病历分析。因此,我们鼓励信息可视化社区研究他们的系统在医疗保健中的应用。我们的专著是为科学研究人员和未来电子病历用户界面的设计者而写的。我们希望它能帮助他们理解这个重要的领域,欣赏现有系统的特性和优点,这样他们就可以创建更先进的系统。我们确定了潜在的未来研究主题,包括对数据抽象的交互式支持、针对间歇性用户(如患者)的系统以及更详细的评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Interactive Information Visualization to Explore and Query Electronic Health Records
Physicians are confronted with increasingly complex patient histories based on which they must make life-critical treatment decisions. At the same time, clinical researchers are eager to study the growing databases of patient histories to detect unknown patterns, ensure quality control, and discover surprising outcomes. Designers of Electronic Health Record systems (EHRs) have great potential to apply innovative visual methods to support clinical decision-making and research. This work surveys the state-of-the-art of information visualization systems for exploring and querying EHRs, as described in the scientific literature. We examine how systems differ in their features and highlight how these differences are related to their design and the medical scenarios they tackle. The systems are compared on a set of criteria: (1) data types covered, (2) multivariate analysis support, (3) number of patient records used (one or multiple), and (4) user intents addressed. Based on our survey and evidence gained from evaluation studies, we believe that effective information visualization can facilitate analysis of EHRs for patient treatment and clinical research. Thus, we encourage the information visualization community to study the application of their systems in health care. Our monograph is written for both scientific researchers and designers of future user interfaces for EHRs. We hope it will help them understand this vital domain and appreciate the features and virtues of existing systems, so they can create still more advanced systems. We identify potential future research topics in interactive support for data abstraction, in systems for intermittent users, such as patients, and in more detailed evaluations.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信