Big data and electronic health records for glaucoma research.

IF 1 Q4 OPHTHALMOLOGY Taiwan Journal of Ophthalmology Pub Date : 2024-09-13 eCollection Date: 2024-07-01 DOI:10.4103/tjo.TJO-D-24-00055
Isaac A Bernstein, Karen S Fernandez, Joshua D Stein, Suzann Pershing, Sophia Y Wang
{"title":"Big data and electronic health records for glaucoma research.","authors":"Isaac A Bernstein, Karen S Fernandez, Joshua D Stein, Suzann Pershing, Sophia Y Wang","doi":"10.4103/tjo.TJO-D-24-00055","DOIUrl":null,"url":null,"abstract":"<p><p>The digitization of health records through electronic health records (EHRs) has transformed the landscape of ophthalmic research, particularly in the study of glaucoma. EHRs offer a wealth of structured and unstructured data, allowing for comprehensive analyses of patient characteristics, treatment histories, and outcomes. This review comprehensively discusses different EHR data sources, their strengths, limitations, and applicability towards glaucoma research. Institutional EHR repositories provide detailed multimodal clinical data, enabling in-depth investigations into conditions such as glaucoma and facilitating the development of artificial intelligence applications. Multicenter initiatives such as the Sight Outcomes Research Collaborative and the Intelligent Research In Sight registry offer larger, more diverse datasets, enhancing the generalizability of findings and supporting large-scale studies on glaucoma epidemiology, treatment outcomes, and practice patterns. The All of Us Research Program, with a special emphasis on diversity and inclusivity, presents a unique opportunity for glaucoma research by including underrepresented populations and offering comprehensive health data even beyond the EHR. Challenges persist, such as data access restrictions and standardization issues, but may be addressed through continued collaborative efforts between researchers, institutions, and regulatory bodies. Standardized data formats and improved data linkage methods, especially for ophthalmic imaging and testing, would further enhance the utility of EHR datasets for ophthalmic research, ultimately advancing our understanding and treatment of glaucoma and other ocular diseases on a global scale.</p>","PeriodicalId":44978,"journal":{"name":"Taiwan Journal of Ophthalmology","volume":"14 3","pages":"352-359"},"PeriodicalIF":1.0000,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11488813/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Taiwan Journal of Ophthalmology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4103/tjo.TJO-D-24-00055","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/7/1 0:00:00","PubModel":"eCollection","JCR":"Q4","JCRName":"OPHTHALMOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

The digitization of health records through electronic health records (EHRs) has transformed the landscape of ophthalmic research, particularly in the study of glaucoma. EHRs offer a wealth of structured and unstructured data, allowing for comprehensive analyses of patient characteristics, treatment histories, and outcomes. This review comprehensively discusses different EHR data sources, their strengths, limitations, and applicability towards glaucoma research. Institutional EHR repositories provide detailed multimodal clinical data, enabling in-depth investigations into conditions such as glaucoma and facilitating the development of artificial intelligence applications. Multicenter initiatives such as the Sight Outcomes Research Collaborative and the Intelligent Research In Sight registry offer larger, more diverse datasets, enhancing the generalizability of findings and supporting large-scale studies on glaucoma epidemiology, treatment outcomes, and practice patterns. The All of Us Research Program, with a special emphasis on diversity and inclusivity, presents a unique opportunity for glaucoma research by including underrepresented populations and offering comprehensive health data even beyond the EHR. Challenges persist, such as data access restrictions and standardization issues, but may be addressed through continued collaborative efforts between researchers, institutions, and regulatory bodies. Standardized data formats and improved data linkage methods, especially for ophthalmic imaging and testing, would further enhance the utility of EHR datasets for ophthalmic research, ultimately advancing our understanding and treatment of glaucoma and other ocular diseases on a global scale.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
用于青光眼研究的大数据和电子健康记录。
通过电子病历(EHR)实现的健康记录数字化改变了眼科研究的面貌,尤其是在青光眼研究方面。电子病历提供了大量结构化和非结构化数据,可对患者特征、治疗史和治疗结果进行全面分析。本综述全面讨论了不同的电子病历数据来源、其优势、局限性以及对青光眼研究的适用性。机构电子病历库提供详细的多模态临床数据,有助于对青光眼等疾病进行深入研究,并促进人工智能应用的开发。视力结果研究合作组织(Sight Outcomes Research Collaborative)和视力智能研究登记处(Intelligent Research In Sight registry)等多中心计划提供了更大、更多样化的数据集,提高了研究结果的可推广性,并为有关青光眼流行病学、治疗结果和实践模式的大规模研究提供了支持。我们所有人研究计划特别强调多样性和包容性,通过纳入代表性不足的人群和提供电子病历以外的全面健康数据,为青光眼研究提供了一个独特的机会。挑战依然存在,如数据访问限制和标准化问题,但可以通过研究人员、机构和监管机构之间的持续合作来解决。标准化的数据格式和改进的数据链接方法,尤其是眼科成像和检测方面的数据链接方法,将进一步提高电子病历数据集在眼科研究中的实用性,最终在全球范围内促进我们对青光眼和其他眼科疾病的了解和治疗。
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
CiteScore
1.80
自引率
9.10%
发文量
68
审稿时长
19 weeks
期刊最新文献
Advancing glaucoma care with big data and artificial intelligence innovations. Application of artificial intelligence in glaucoma care: An updated review. Artificial intelligence and big data integration in anterior segment imaging for glaucoma. Big data and electronic health records for glaucoma research. Big data for imaging assessment in glaucoma.
×
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