SEED: A novel web-based data visualization platform to visualize, communicate, and explore social, environmental, and equity drivers of health.

IF 2.1 Q3 MEDICINE, RESEARCH & EXPERIMENTAL Journal of Clinical and Translational Science Pub Date : 2024-09-16 eCollection Date: 2024-01-01 DOI:10.1017/cts.2024.569
Nrupen A Bhavsar, Jessica Sperling, Raquel Ruiz, Dinushika Mohottige, Perusi Muhigaba, Mina Silberberg, Anthony Leiro, Pamela Maxson, Michelle Lyn, L Ebony Boulware
{"title":"SEED: A novel web-based data visualization platform to visualize, communicate, and explore social, environmental, and equity drivers of health.","authors":"Nrupen A Bhavsar, Jessica Sperling, Raquel Ruiz, Dinushika Mohottige, Perusi Muhigaba, Mina Silberberg, Anthony Leiro, Pamela Maxson, Michelle Lyn, L Ebony Boulware","doi":"10.1017/cts.2024.569","DOIUrl":null,"url":null,"abstract":"<p><p>Multisector stakeholders, including, community-based organizations, health systems, researchers, policymakers, and commerce, increasingly seek to address health inequities that persist due to structural racism. They require accessible tools to visualize and quantify the prevalence of social drivers of health (SDOH) and correlate them with health to facilitate dialog and action. We developed and deployed a web-based data visualization platform to make health and SDOH data available to the community. We conducted interviews and focus groups among end users of the platform to establish needs and desired platform functionality. The platform displays curated SDOH and de-identified and aggregated local electronic health record data. The resulting Social, Environmental, and Equity Drivers (SEED) Health Atlas integrates SDOH data across multiple constructs, including socioeconomic status, environmental pollution, and built environment. Aggregated health prevalence data on multiple conditions can be visualized in interactive maps. Data can be visualized and downloaded without coding knowledge. Visualizations facilitate an understanding of community health priorities and local health inequities. SEED could facilitate future discussions on improving community health and health equity. SEED provides a promising tool that members of the community and researchers may use in their efforts to improve health equity.</p>","PeriodicalId":15529,"journal":{"name":"Journal of Clinical and Translational Science","volume":"8 1","pages":"e121"},"PeriodicalIF":2.1000,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11428061/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Clinical and Translational Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1017/cts.2024.569","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q3","JCRName":"MEDICINE, RESEARCH & EXPERIMENTAL","Score":null,"Total":0}
引用次数: 0

Abstract

Multisector stakeholders, including, community-based organizations, health systems, researchers, policymakers, and commerce, increasingly seek to address health inequities that persist due to structural racism. They require accessible tools to visualize and quantify the prevalence of social drivers of health (SDOH) and correlate them with health to facilitate dialog and action. We developed and deployed a web-based data visualization platform to make health and SDOH data available to the community. We conducted interviews and focus groups among end users of the platform to establish needs and desired platform functionality. The platform displays curated SDOH and de-identified and aggregated local electronic health record data. The resulting Social, Environmental, and Equity Drivers (SEED) Health Atlas integrates SDOH data across multiple constructs, including socioeconomic status, environmental pollution, and built environment. Aggregated health prevalence data on multiple conditions can be visualized in interactive maps. Data can be visualized and downloaded without coding knowledge. Visualizations facilitate an understanding of community health priorities and local health inequities. SEED could facilitate future discussions on improving community health and health equity. SEED provides a promising tool that members of the community and researchers may use in their efforts to improve health equity.

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
SEED:一个新颖的网络数据可视化平台,用于可视化、交流和探索健康的社会、环境和公平驱动因素。
多部门利益相关者,包括社区组织、卫生系统、研究人员、决策者和商业界,越来越多地寻求解决因结构性种族主义而持续存在的健康不平等问题。他们需要便于使用的工具来可视化和量化影响健康的社会因素(SDOH),并将其与健康联系起来,以促进对话和行动。我们开发并部署了一个基于网络的数据可视化平台,向社区提供健康和 SDOH 数据。我们对平台的最终用户进行了访谈和焦点小组讨论,以确定需求和所需的平台功能。该平台可显示经整理的 SDOH 数据以及去标识化和汇总的本地电子健康记录数据。由此产生的社会、环境和公平驱动因素(SEED)健康地图集整合了多个方面的 SDOH 数据,包括社会经济状况、环境污染和建筑环境。有关多种情况的汇总健康流行率数据可在交互式地图中直观显示。无需编码知识即可直观显示和下载数据。可视化有助于了解社区健康优先事项和当地的健康不公平现象。SEED 可促进未来有关改善社区健康和健康公平的讨论。SEED 提供了一个很有前途的工具,社区成员和研究人员可以利用它来改善健康公平状况。
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
Journal of Clinical and Translational Science
Journal of Clinical and Translational Science MEDICINE, RESEARCH & EXPERIMENTAL-
CiteScore
2.80
自引率
26.90%
发文量
437
审稿时长
18 weeks
期刊最新文献
Overview of ACTIV trial-specific lessons learned. Preparing better: Accelerating COVID-19 Therapeutic Interventions and Vaccines (ACTIV) therapeutics trials lessons learned: A call to the future. The future is now: Using the lessons learned from the ACTIV COVID-19 therapeutics trials to create an inclusive and efficient clinical trials enterprise. ACTIV trials: Lessons learned in trial design in the setting of an emergent pandemic. Lessons learned from COVID-19 to overcome challenges in conducting outpatient clinical trials to find safe and effective therapeutics for the next infectious pandemic.
×
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