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将区域贫困指数数据与 OMOP 通用数据模型关联的可行性。

Feasibility of Linking Area Deprivation Index Data to the OMOP Common Data Model.

机构信息

Columbia University Irvine Medical Center, New York, NY.

Tufts Medical Center, Boston, MA.

出版信息

AMIA Annu Symp Proc. 2023 Apr 29;2022:587-595. eCollection 2022.

Abstract

Linking Area Deprivation Index (ADI) scores to observational data offers the opportunity to characterize healthcare treatment and outcomes that are driven by socioeconomic deprivation. The current study aims to assess the feasibility of creating an analysis package to link ADI rankings to multiple patient-level EHR datasets transformed into the OMOP CDM. Patients within two cancer cohorts (breast cancer and multiple myeloma) were identified within two OMOP datasets and their records were linked with ADI scores using address information in the OMOP location table. With ADI linked to patient addresses, we generated visualizations showing the geographic distribution of each cohort based on ADI scores. Additionally, further assessment showed that over 89% of patient addresses could successfully be linked with ADI rankings. In conducting this assessment, we have demonstrated that developing a package to link ADI scores with multiple OMOP datasets is feasible.

摘要

将区域贫困指数(ADI)得分与观察数据相关联,为描述由社会经济贫困驱动的医疗保健治疗和结果提供了机会。本研究旨在评估创建一个分析包的可行性,该分析包将 ADI 排名与多个转化为 OMOP CDM 的患者级 EHR 数据集相关联。在两个 OMOP 数据集内确定了两个癌症队列(乳腺癌和多发性骨髓瘤)中的患者,并使用 OMOP 位置表中的地址信息将他们的记录与 ADI 得分相关联。通过将 ADI 与患者地址相关联,我们生成了可视化效果,根据 ADI 得分显示每个队列的地理分布。此外,进一步评估表明,超过 89%的患者地址可以成功与 ADI 排名相关联。在进行此评估时,我们已经证明开发一个将 ADI 得分与多个 OMOP 数据集相关联的包是可行的。

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