National Infrastructure for Standardized and Portable EHR Phenotyping Algorithms

项目总结 随着由于有意义的使用而迅速采用患者电子健康记录系统(EHR)， 以及将电子病历与研究生物信息库联系起来，评估电子病历数据对临床和 翻译研究正变得越来越重要，对基因组和观察学都有影响 研究、临床试验和比较效果研究。用于确定患者队列的关键组件 在电子病历中，定义纳入和排除标准，根据算法选择患者组 存储的临床数据。这一过程通常被称为“EHR驱动的表型”是耗时的 由于缺乏被广泛接受的、基于标准的正式信息模型来定义 表型算法。为了应对这一总体挑战，拟议的项目将设计、建造和推广 开放访问的社区基础设施，用于基于标准的开发和表型共享 算法，并为调查人员、研究人员及其信息学支持提供工具和资源 工作人员在原生EHR数据上实施和执行算法。

PROJECT SUMMARY With the rapidly growing adoption of patient electronic health record systems (EHRs) due to Meaningful Use, and linkage of EHRs to research biorepositories, evaluating the suitability of EHR data for clinical and translational research is becoming ever more important, with ramifications for genomic and observational research, clinical trials, and comparative effectiveness studies. A key component for identifying patient cohorts in the EHR is to define inclusion and exclusion criteria that algorithmically select sets of patients based on stored clinical data. This process is commonly referred to, as “EHR-driven phenotyping” is time-consuming and tedious due to the lack of a widely accepted and standards-based formal information model for defining phenotyping algorithms. To address this overall challenge, the proposed project will design, build and promote an open-access community infrastructure for standards-based development and sharing of phenotyping algorithms, as well as provide tools and resources for investigators, researchers and their informatics support staff to implement and execute the algorithms on native EHR data.