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. 2025 Jan 31;20(1):e0317215.
doi: 10.1371/journal.pone.0317215. eCollection 2025.

A data pipeline for secure extraction and sharing of social determinants of health

Affiliations

A data pipeline for secure extraction and sharing of social determinants of health

Tyler Schappe et al. PLoS One. .

Abstract

Objectives: Linking neighborhood- and patient-level data provides valuable information about the influence of upstream social determinants of health (SDOH). However, sharing of these data across health systems presents challenges. We set out to develop a pipeline to acquire, deidentify, and share neighborhood-level SDOH data across multiple health systems.

Methods: We created a pipeline centered around Decentralized Geomarker Assessment for Multi-Site Studies (DeGAUSS) that utilizes containerization to geocode patient addresses and obtain neighborhood-level SDOH variables. We compared DeGAUSS to a third-party vendor geocoding tool available at Duke Health using a cohort of adult patients referred for abdominal transplant from January 1, 2016, to December 31, 2022. We calculated Cohen's Kappa and percent disagreement at census block group and tract levels, and by Area Deprivation Index, urbanicity, and year.

Results: The pipeline successfully generated SDOH data for 97.8% of addresses. There was high concordance between DeGAUSS and the vendor tool at the census block group (0.93) and tract levels (0.95). At the block group level, disagreement proportion differed by year and urbanicity, with larger disagreement in the rural category than in micropolitan and metropolitan categories (13%, 7%, 6.2%, respectively).

Discussion and conclusion: We describe a novel pipeline that can facilitate the secure acquisition and sharing of neighborhood-level SDOH without sharing PHI. The pipeline can be scaled to include additional social, climate, and environmental variables, and can be extended to an unlimited number of health systems.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Conceptual diagram outlining the components of the generalized pipeline for geocoding patient addresses and obtaining de-identified social determinants of health (SDOH) data.
Fig 2
Fig 2
Pairwise comparisons of probability of disagreement of census unit assignments between DeGAUSS and vendor tool geocoding at the block group level among A) urban/rural categories and B) calendar year address was applicable.

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