Pengetnze Yolande, Sundaram Venkatraghavan, Tamer Yusuf, Karam Albert, Rather Lance, Adejumobi Olayide, Wainwright Leslie, Miff Steve
Parkland Center for Clinical Innovation (PCCI), Dallas, TX 75247, United States.
Formerly Parkland Center for Clinical Innovation (PCCI), Dallas, TX 75247, United States.
JAMIA Open. 2025 Jul 4;8(4):ooaf059. doi: 10.1093/jamiaopen/ooaf059. eCollection 2025 Aug.
To determine whether a novel digital tool, the Community Vulnerability Compass (CVC), built using large datasets, can accurately measure neighborhood- and individual-level social determinants of health (SDOH) at scale. Existing SDOH indexes fall short of this dual requirement.
: A cross-sectional study by Parkland Health (Parkland) and Parkland Center for Clinical Innovation (PCCI) to design, build, deploy, and validate CVC in Dallas County/across Texas (2018-2024). : Parkland Electronic Health Records; population-level data from diverse national datasets. CVC's Community Vulnerability Index (CVI), and 4 subindexes were used to classify all 18 638 Texas census-block groups as Very-High, High, Moderate, Low, and Very-Low social vulnerability. Individuals were assigned the vulnerability of their home address census-block group. CVC's classifications were compared against 3 existing SDOH neighborhood tools (Area Deprivation Index [ADI], Social Vulnerability Index [SVI], or Environmental Justice Index [EJI]) and validated against individual-level SDOH screening tools or Z-code documentation. Spearman rank correlation was used for neighborhood-level comparisons and precision/recall, for individual-level comparisons.
Neighborhood-level CVI measurement of social vulnerability strongly correlated with EJI (r = 0.83), SVI (r = 0.82), and ADI (r = 0.79). Individual-level CVI measurement had higher recall than ADI (68% vs 39%, respectively; < .001) and high recall across self-reported SDOH (77%-79.6%). Precision was highest for food needs (75.1%); lowest for safety needs (1.2%).
CVC measured a cross-cutting range of neighborhood social vulnerabilities and accurately approximated individual-level SDOH, outperforming existing indexes.
CVC can be leveraged as an accurate and scalable SDOH digital measurement tool
确定一种使用大型数据集构建的新型数字工具——社区脆弱性指南针（CVC），能否大规模准确测量社区和个体层面的健康社会决定因素（SDOH）。现有的SDOH指数无法满足这一双重要求。
由帕克兰健康中心（Parkland）和帕克兰临床创新中心（PCCI）进行的一项横断面研究，旨在达拉斯县/德克萨斯州各地设计、构建、部署和验证CVC（2018 - 2024年）。使用帕克兰电子健康记录；来自不同国家数据集的人口层面数据。CVC的社区脆弱性指数（CVI）和4个子指数用于将德克萨斯州所有18638个人口普查街区组分类为极高、高、中、低和极低社会脆弱性。个体被赋予其家庭住址普查街区组的脆弱性。将CVC的分类与3种现有的SDOH社区工具（地区贫困指数[ADI]、社会脆弱性指数[SVI]或环境正义指数[EJI]）进行比较，并针对个体层面的SDOH筛查工具或Z代码文档进行验证。在社区层面比较中使用斯皮尔曼等级相关性，在个体层面比较中使用精确率/召回率。
社区层面CVI对社会脆弱性的测量与EJI（r = 0.83）、SVI（r = 0.82）和ADI（r = 0.79）高度相关。个体层面CVI测量的召回率高于ADI（分别为68%和39%；P < 0.001），并且在自我报告的SDOH中召回率较高（77% - 79.6%）。精确率在食物需求方面最高（75.1%）；在安全需求方面最低（1.2%）。
CVC测量了一系列社区社会脆弱性，并且准确地近似了个体层面的SDOH，优于现有指数。
CVC可作为一种准确且可扩展的SDOH数字测量工具加以利用。
