想象母亲的健康旅程,以学习健康系统:混合方法,综合经验方法
Amanda L Joseph1,2,3, Bilikis Oladimeji4, Helen Monkman1
1School of Health Information Science, University of Victoria, PO Box 1700 STN CSC, Victoria, BC, V8W 2Y2, Canada, 1 250 721 8575.
Journal of participatory medicine
|February 19, 2026
概括
视觉化综合体验 (VCE) 图表通过将患者故事与数据整合起来,揭示了关键的孕产妇死亡率差异. 这种创新方法突出了传统可视化方法往往忽略的不平等现象,改善了对健康结果的理解.
科学领域:
- 公共卫生 公共卫生
- 医疗信息学 医疗信息学
- 数据可视化 数据可视化
背景情况:
- 美国正在经历一个严重的孕产妇死亡率危机,不成比例地影响黑人女性.
- 传统的数据可视化模糊了患者层面的体验,掩盖了关键的健康不平等.
研究的目的:
- 开发和应用一个创新的可视化综合体验 (VCE) 图表,以说明产妇死亡率的差异.
- 探索综合可视化技术如何揭示个体患者体验与人口水平健康结果之间的联系.
- 评估VCE图的潜力,以告知一个学习健康系统 (LHS).
主要方法:
- 一种混合方法的方法,使用来自CDC的定量数据和来自"失踪母亲"的定性数据.
- 通过七步的过程构建VCE图,包括复合人格,旅程图和桑基图.
- 整合定量死亡数据与定性患者叙述和"更密切的观察"插件以暴露隐藏的差异.
主要成果:
- VCE图表有效地说明了差异,显示黑人妇女的孕产妇死亡率为每1000例出生51.2%,而白人妇女的死亡率为16.8.
- 视觉化显示了诊断延迟和死亡率之间的联系,展示了汇总数据如何掩盖这些关键问题.
- VCE图表促进了对孕产妇健康结果的更有同情心和更有效的理解.
结论:
- VCE图表将微观水平的患者体验与宏观水平的数据相结合,增强服务评估和改善健康结果.
- 这种可复制的可视化框架突出显示了系统差异,这些差异通常隐藏在汇总数据中.
- VCE图表可以促进组织学习和在学习健康系统 (LHS) 中的持续改进.
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