Evaluation of accessibility of open-source EHRs for visually impaired users.

AMIA ... Annual Symposium proceedings. AMIA Symposium Pub Date : 2024-01-11 eCollection Date: 2023-01-01
Megha M Moncy, Manya Pilli, Manasi Somasundaram, Saptarshi Purkayastha, Cathy R Fulton
{"title":"Evaluation of accessibility of open-source EHRs for visually impaired users.","authors":"Megha M Moncy, Manya Pilli, Manasi Somasundaram, Saptarshi Purkayastha, Cathy R Fulton","doi":"","DOIUrl":null,"url":null,"abstract":"<p><p>This study investigates the accessibility of open-source electronic health record (EHR) systems for individuals who are visually impaired or blind. Ensuring the accessibility of EHRs to visually impaired users is critical for the diversity, equity, and inclusion of all users. The study used a combination of automated and manual accessibility testing with screen readers to evaluate the accessibility of three widely used open-source EHR systems. We used three popular screen readers - JAWS (Windows), NVDA (Windows), and Apple VoiceOver (OSX) to evaluate accessibility. The evaluation revealed that although each of the three EHR systems was partially accessible, there is room for improvement, particularly regarding keyboard navigation and screen reader compatibility. The study concludes with recommendations for making EHR systems more inclusive for all users and more accessible.</p>","PeriodicalId":72180,"journal":{"name":"AMIA ... Annual Symposium proceedings. AMIA Symposium","volume":"2023 ","pages":"1165-1174"},"PeriodicalIF":0.0000,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10785889/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}
引用次数: 0

Abstract

This study investigates the accessibility of open-source electronic health record (EHR) systems for individuals who are visually impaired or blind. Ensuring the accessibility of EHRs to visually impaired users is critical for the diversity, equity, and inclusion of all users. The study used a combination of automated and manual accessibility testing with screen readers to evaluate the accessibility of three widely used open-source EHR systems. We used three popular screen readers - JAWS (Windows), NVDA (Windows), and Apple VoiceOver (OSX) to evaluate accessibility. The evaluation revealed that although each of the three EHR systems was partially accessible, there is room for improvement, particularly regarding keyboard navigation and screen reader compatibility. The study concludes with recommendations for making EHR systems more inclusive for all users and more accessible.

分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
评估开放源电子病历对视障用户的无障碍性。
本研究调查了视障人士或盲人对开源电子健康记录(EHR)系统的可访问性。确保电子病历对视障用户的无障碍性对所有用户的多样性、公平性和包容性至关重要。这项研究结合使用屏幕阅读器进行自动和手动无障碍测试,以评估三种广泛使用的开源电子病历系统的无障碍程度。我们使用了三种流行的屏幕阅读器--JAWS(Windows)、NVDA(Windows)和 Apple VoiceOver(OSX)来评估无障碍性。评估结果表明,虽然这三种电子病历系统都具有部分无障碍性,但仍有改进的余地,尤其是在键盘导航和屏幕阅读器兼容性方面。研究最后提出了一些建议,以提高电子病历系统对所有用户的包容性和无障碍性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Ethicara for Responsible AI in Healthcare: A System for Bias Detection and AI Risk Management. 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.
×
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