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National Infrastructure for Standardized and Portable EHR Phenotyping Algorithms

National Infrastructure for Standardized and Portable EHR Phenotyping Algorithms
标准化和便携式 EHR 表型算法的国家基础设施
批准号:
10021669
负责人:
YUAN LUO
金额:
$70.69万
依托单位国家:
美国
项目类别:
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-09-01 至 2022-08-31

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中文摘要
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英文摘要
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.
期刊论文(41)
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会议论文
DOI: 10.1186/s12955-015-0285-6
发表时间: 2015-07-03
期刊: Health and quality of life outcomes
影响因子: 3.6
作者: [Ryu E, Takahashi PY, Olson JE, Hathcock MA, Novotny PJ, Pathak J, Bielinski SJ, Cerhan JR, Sloan JA]
通讯作者: Sloan JA
DOI: 10.1038/gim.2013.121
发表时间: 2013-10
期刊: Genetics in medicine : official journal of the American College of Medical Genetics
影响因子: --
作者: []
通讯作者:
CQL4NLP: Development and Integration of FHIR NLP Extensions in Clinical Quality Language for EHR-driven Phenotyping.
CQL4NLP:在临床质量语言中开发和集成 FHIR NLP 扩展,以实现 EHR 驱动的表型分析。
DOI: --
发表时间: 2021
期刊: AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science
影响因子: --
作者: [Wen,Andrew, Rasmussen,LukeV, Stone,Daniel, Liu,Sijia, Kiefer,Rick, Adekkanattu,Prakash, Brandt,PascalS, Pacheco,JenniferA, Luo,Yuan, Wang,Fei, Pathak,Jyotishman, Liu,Hongfang, Jiang,Guoqian]
通讯作者: Jiang,Guoqian
Integration of NLP2FHIR Representation with Deep Learning Models for EHR Phenotyping: A Pilot Study on Obesity Datasets.
NLP2FHIR 表示与 EHR 表型深度学习模型的集成:肥胖数据集的试点研究。
DOI: --
发表时间: 2021
期刊: AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science
影响因子: --
作者: [Liu,Sijia, Luo,Yuan, Stone,Daniel, Zong,Nansu, Wen,Andrew, Yu,Yue, Rasmussen,LukeV, Wang,Fei, Pathak,Jyotishman, Liu,Hongfang, Jiang,Guoqian]
通讯作者: Jiang,Guoqian
31
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    Modeling the Incompleteness and Biases of Health Data
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