The Community Vulnerability Compass: a novel, scalable approach for measuring and visualizing social determinants of...

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.

Setting: 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). Data Sources: Parkland Electronic Health Records; population-level data from diverse national datasets. Statistical Analysis: 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; P < .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.