Schappe Tyler, McElroy Lisa M, Ogundolie Moronke, Matsouaka Roland, Rogers Ursula, Bhavsar Nrupen A
Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, North Carolina, United States of America.
Department of Population Health Sciences, Duke University School of Medicine, Durham, North Carolina, United States of America.
PLoS One. 2025 Jan 31;20(1):e0317215. doi: 10.1371/journal.pone.0317215. eCollection 2025.
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.
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.
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).
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.
将社区层面和患者层面的数据相联系，能够提供有关健康的上游社会决定因素（SDOH）影响的宝贵信息。然而，在不同卫生系统间共享这些数据存在挑战。我们着手开发一个管道，用于跨多个卫生系统获取、去识别并共享社区层面的SDOH数据。
我们创建了一个以多站点研究的去中心化地理标记评估（DeGAUSS）为核心的管道，该管道利用容器化技术对患者地址进行地理编码，并获取社区层面的SDOH变量。我们使用2016年1月1日至2022年12月31日期间因腹部移植而转诊的成年患者队列，将DeGAUSS与杜克健康提供的第三方供应商地理编码工具进行比较。我们计算了人口普查街区组和普查区层面以及按地区贫困指数、城市化程度和年份划分的科恩卡帕系数和不一致百分比。
该管道成功为97.8%的地址生成了SDOH数据。在人口普查街区组（0.93）和普查区层面（0.95），DeGAUSS与供应商工具之间具有高度一致性。在街区组层面，不一致比例因年份和城市化程度而异，农村类别中的不一致比例高于微型都市和大都市类别（分别为13%、7%、6.2%）。
我们描述了一种新型管道，它可以在不共享受保护健康信息（PHI）的情况下，促进社区层面SDOH数据的安全获取和共享。该管道可以扩展以纳入更多社会、气候和环境变量，并且可以扩展到无限数量的卫生系统。
