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Building Bridges Across Electronic Health Record Systems Through Inferred Phenotypic Topics

机译:通过推断的表型主题跨电子病历系统搭建桥梁

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摘要

ObjectiveData in electronic health records (EHRs) is being increasingly leveraged for secondary uses, ranging from biomedical association studies to comparative effectiveness. To perform studies at scale and transfer knowledge from one institution to another in a meaningful way, we need to harmonize the phenotypes in such systems. Traditionally, this has been accomplished through expert specification of phenotypes via standardized terminologies, such as billing codes. However, this approach may be biased by the experience and expectations of the experts, as well as the vocabulary used to describe such patients. The goal of this work is to develop a data-driven strategy to 1) infer phenotypic topics within patient populations and 2) assess the degree to which such topics facilitate a mapping across populations in disparate healthcare systems.
机译:电子健康记录(EHR)中的ObjectiveData被越来越多地用于次要用途,从生物医学关联研究到比较有效性。为了进行大规模研究并以一种有意义的方式将知识从一个机构转移到另一个机构,我们需要协调这种系统中的表型。传统上,这是通过诸如计费代码之类的标准化术语通过表型的专家规范来完成的。但是,这种方法可能会因专家的经验和期望以及用于描述此类患者的词汇而有偏差。这项工作的目标是开发一种数据驱动的策略,以:1)推断患者人群中的表型主题,以及2)评估此类主题在不同医疗系统中促进跨人群映射的程度。

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