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SEnDAE:一个扩展社会和环境健康决定因素研究的资源。

SEnDAE: A resource for expanding research into social and environmental determinants of health.

机构信息

Keck School of Medicine, University of Southern California, 2250 Alcazar St CSC 212, Los Angeles CA 90033, USA.

Department of Pediatrics, Children's Hospital Los Angeles, Los Angeles CA USA.

出版信息

Comput Methods Programs Biomed. 2023 Aug;238:107542. doi: 10.1016/j.cmpb.2023.107542. Epub 2023 Apr 8.

Abstract

BACKGROUND AND OBJECTIVE

Social and Environmental Determinants of Health (SEDoH) are of increasing interest to researchers in personal and public health. Collecting SEDoH and associating them with patient medical record can be challenging, especially for environmental variables. We announce here the release of SEnDAE, the Social and Environmental Determinants Address Enhancement toolkit, and open-source resource for ingesting a range of environmental variables and measurements from a variety of sources and associated them with arbitrary addresses.

METHODS

SEnDAE includes optional components for geocoding addresses, in case an organization does not have independent capabilities in that area, and recipes for extending the OMOP CDM and the ontology of an i2b2 instance to display and compute over the SEnDAE variables within i2b2.

RESULTS

On a set of 5000 synthetic addresses, SEnDAE was able to geocode 83%. SEnDAE geocodes addresses to the same Census tract as ESRI 98.1% of the time.

CONCLUSION

Development of SEnDAE is ongoing, but we hope that teams will find it useful to increase their usage of environmental variables and increase the field's general understanding of these important determinants of health.

摘要

背景与目的

社会和环境健康决定因素(SEDoH)越来越受到个人和公共卫生研究人员的关注。收集 SEDoH 并将其与患者病历相关联可能具有挑战性,特别是对于环境变量而言。在这里,我们宣布发布 SEnDAE,这是一个社会和环境决定因素地址增强工具包,是一个开源资源,用于从各种来源摄取各种环境变量和测量值,并将它们与任意地址相关联。

方法

SEnDAE 包括可选的地址地理编码组件,如果组织在该领域没有独立的能力,并且有用于扩展 OMOP CDM 和 i2b2 实例的本体的配方,以在 i2b2 内显示和计算 SEnDAE 变量。

结果

在一组 5000 个合成地址中,SEnDAE 能够进行 83%的地理编码。SEnDAE 对地址进行地理编码的位置与 ESRI 相同的普查地段的次数为 98.1%。

结论

SEnDAE 的开发仍在进行中,但我们希望团队会发现它有助于增加对环境变量的使用,并提高人们对这些健康重要决定因素的总体认识。

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