基于网络的 FHIR® 问卷回复图形探索原型。

AMIA ... Annual Symposium proceedings. AMIA Symposium Pub Date : 2024-01-11 eCollection Date: 2023-01-01
Johann Frei, Florian J Auer, Steffen Netzband, Yevgeniia Ignatenko, Frank Kramer
{"title":"基于网络的 FHIR® 问卷回复图形探索原型。","authors":"Johann Frei, Florian J Auer, Steffen Netzband, Yevgeniia Ignatenko, Frank Kramer","doi":"","DOIUrl":null,"url":null,"abstract":"<p><p>The evaluation of clinical questionnaires is an important part of gaining knowledge in empirical research. The electronically captured responses are encoded in a standard format such as HL7 FHIR® that facilitates data exchange and systems interoperability. However, this also complicates access of the information to explore and interpret the results without appropriate tools. In this work, we present the design of a web-based graphical exploration tool for categorical questionnaire response data that can interact with FHIR-conformant HTTP endpoints. The web app enables non-technical users with simplified, direct visual access to highly structured FHIR questionnaire response data and preserves the applicability in arbitrary data exploration tasks. We describe the abstract feature design with the derived technical implementation to allow a universal, user-configurable data subselection mechanism to generate conditional one- and two-data-dimensional charts. The applicability of our developed prototype is demonstrated on synthetic FHIR data with the source code available at https://github.com/frankkramer-lab/FHIR-QR-Explorer.</p>","PeriodicalId":72180,"journal":{"name":"AMIA ... Annual Symposium proceedings. AMIA Symposium","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10785863/pdf/","citationCount":"0","resultStr":"{\"title\":\"Web-based Prototype for Graphical Exploration of FHIR® Questionnaire Responses.\",\"authors\":\"Johann Frei, Florian J Auer, Steffen Netzband, Yevgeniia Ignatenko, Frank Kramer\",\"doi\":\"\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The evaluation of clinical questionnaires is an important part of gaining knowledge in empirical research. The electronically captured responses are encoded in a standard format such as HL7 FHIR® that facilitates data exchange and systems interoperability. However, this also complicates access of the information to explore and interpret the results without appropriate tools. In this work, we present the design of a web-based graphical exploration tool for categorical questionnaire response data that can interact with FHIR-conformant HTTP endpoints. The web app enables non-technical users with simplified, direct visual access to highly structured FHIR questionnaire response data and preserves the applicability in arbitrary data exploration tasks. We describe the abstract feature design with the derived technical implementation to allow a universal, user-configurable data subselection mechanism to generate conditional one- and two-data-dimensional charts. The applicability of our developed prototype is demonstrated on synthetic FHIR data with the source code available at https://github.com/frankkramer-lab/FHIR-QR-Explorer.</p>\",\"PeriodicalId\":72180,\"journal\":{\"name\":\"AMIA ... Annual Symposium proceedings. AMIA Symposium\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-01-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10785863/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"AMIA ... Annual Symposium proceedings. AMIA Symposium\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2023/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"AMIA ... Annual Symposium proceedings. AMIA Symposium","FirstCategoryId":"1085","ListUrlMain":"","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/1/1 0:00:00","PubModel":"eCollection","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

临床问卷评估是实证研究中获取知识的重要组成部分。电子采集的回答以标准格式编码,如 HL7 FHIR®,有利于数据交换和系统互操作性。然而,如果没有适当的工具,这也会使获取信息以探索和解释结果变得更加复杂。在这项工作中,我们介绍了一种基于网络的分类问卷答复数据图形探索工具的设计,该工具可与符合 FHIR 的 HTTP 端点进行交互。该网络应用程序可使非技术用户以简化、直接的可视化方式访问高度结构化的 FHIR 问卷答复数据,并可适用于任意数据探索任务。我们介绍了抽象的功能设计和衍生的技术实现,以实现通用的、用户可配置的数据子选择机制,生成有条件的一维和二维图表。我们在合成 FHIR 数据上演示了所开发原型的适用性,源代码可在 https://github.com/frankkramer-lab/FHIR-QR-Explorer 上获取。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Web-based Prototype for Graphical Exploration of FHIR® Questionnaire Responses.

The evaluation of clinical questionnaires is an important part of gaining knowledge in empirical research. The electronically captured responses are encoded in a standard format such as HL7 FHIR® that facilitates data exchange and systems interoperability. However, this also complicates access of the information to explore and interpret the results without appropriate tools. In this work, we present the design of a web-based graphical exploration tool for categorical questionnaire response data that can interact with FHIR-conformant HTTP endpoints. The web app enables non-technical users with simplified, direct visual access to highly structured FHIR questionnaire response data and preserves the applicability in arbitrary data exploration tasks. We describe the abstract feature design with the derived technical implementation to allow a universal, user-configurable data subselection mechanism to generate conditional one- and two-data-dimensional charts. The applicability of our developed prototype is demonstrated on synthetic FHIR data with the source code available at https://github.com/frankkramer-lab/FHIR-QR-Explorer.

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
期刊最新文献
Towards Fair Patient-Trial Matching via Patient-Criterion Level Fairness Constraint. Towards Understanding the Generalization of Medical Text-to-SQL Models and Datasets. Transferable and Interpretable Treatment Effectiveness Prediction for Ovarian Cancer via Multimodal Deep Learning. Understanding Cancer Caregiving and Predicting Burden: An Analytics and Machine Learning Approach. Usability and Recall Evaluation of Virtual Reality Ontology Object Manipulation (VROOM) System.
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1