Evaluation of the portability of computable phenotypes with natural language processing in the eMERGE network.
Evaluation of the portability of computable phenotypes with natural language processing in the eMERGE network.
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DOI：
10.1038/s41598-023-27481-y
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发表时间：
2023-02-03
影响因子：
4.6
通讯作者：
中科院分区：
文献类型：
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作者：
电子医疗记录和基因组学（eMERGE）网络评估了部署基于规则的便携式表型算法的可行性，其中添加了自然语言处理（NLP）组件，以提高使用电子健康记录（EHR）的现有算法的性能。基于科学价值和预测的难度，eMERGE选择了六种现有的表型来增强NLP。我们评估了性能、可移植性和易用性。我们总结了以下方面的经验教训：（1）挑战;（2）基于现有证据和/或eMERGE经验应对挑战的最佳实践;（3）未来研究的机会。添加NLP导致了除了一个算法之外的所有算法的精度和/或召回率的提高或相同。便携性、表型分型工作流程/过程和技术是主要主题。使用NLP，开发和验证需要更长的时间。除了NLP技术的可移植性和算法的可复制性外，确保成功的因素还包括隐私保护、技术基础设施设置、知识产权协议和高效沟通。工作流程改进可以改善沟通并缩短实施时间。NLP性能的变化主要是由于临床文档的异质性;因此，我们建议使用半结构化的笔记，全面的文档和自定义选项。NLP可移植性是可能的，具有改进的表型算法性能，但仔细规划和算法架构对于支持本地定制至关重要。
The electronic Medical Records and Genomics (eMERGE) Network assessed the feasibility of deploying portable phenotype rule-based algorithms with natural language processing (NLP) components added to improve performance of existing algorithms using electronic health records (EHRs). Based on scientific merit and predicted difficulty, eMERGE selected six existing phenotypes to enhance with NLP. We assessed performance, portability, and ease of use. We summarized lessons learned by: (1) challenges; (2) best practices to address challenges based on existing evidence and/or eMERGE experience; and (3) opportunities for future research. Adding NLP resulted in improved, or the same, precision and/or recall for all but one algorithm. Portability, phenotyping workflow/process, and technology were major themes. With NLP, development and validation took longer. Besides portability of NLP technology and algorithm replicability, factors to ensure success include privacy protection, technical infrastructure setup, intellectual property agreement, and efficient communication. Workflow improvements can improve communication and reduce implementation time. NLP performance varied mainly due to clinical document heterogeneity; therefore, we suggest using semi-structured notes, comprehensive documentation, and customization options. NLP portability is possible with improved phenotype algorithm performance, but careful planning and architecture of the algorithms is essential to support local customizations.
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影响因子：
4.6
作者：
Chu SH;Wan ES;Cho MH;Goryachev S;Gainer V;Linneman J;Scotty EJ;Hebbring SJ;Murphy S;Lasky-Su J;Weiss ST;Smoller JW;Karlson E
通讯作者：
Karlson E
DOI：
10.1146/annurev-biodatasci-080917-013315
发表时间：
2018-01-01
期刊：
ANNUAL REVIEW OF BIOMEDICAL DATA SCIENCE, VOL 1
影响因子：
--
作者：
Banda, Juan M.;Seneviratne, Martin;Shah, Nigam H.
通讯作者：
Shah, Nigam H.
影响因子：
4.5
作者：
Harkema H;Dowling JN;Thornblade T;Chapman WW
通讯作者：
Chapman WW
影响因子：
9.5
作者：
Luo, Yuan;Uzuner, Ozlem;Szolovits, Peter
通讯作者：
Szolovits, Peter
影响因子：
8.3
作者：
Khaleghi, Mahyar;Isseh, Iyad N.;Kullo, Iftikhar J.
通讯作者：
Kullo, Iftikhar J.