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通过电子病历上的自然语言处理提高对临床路径的依从性。

Improving Adherence to Clinical Pathways Through Natural Language Processing on Electronic Medical Records.

作者信息

Cruz Noa P, Canales Lea, Muñoz Javier García, Pérez Bernardino, Arnott Ignacio

机构信息

Medsavana S.L., Madrid, Spain.

Servicio de Salud de Castilla-La Mancha, Castilla-La Mancha, Spain.

出版信息

Stud Health Technol Inform. 2019 Aug 21;264:561-565. doi: 10.3233/SHTI190285.

Abstract

This paper presents a pioneering and practical experience in the development and implementation of a clinical decision support system (CDSS) based on natural language processing (NLP) and artificial intelligence (AI) techniques. Our CDSS notifies primary care physicians in real time about recommendations regarding the healthcare process. This is, to the best of our knowledge, the first real-time CDSS implemented in the Spanish National Health System. We achieved adherence rate improvements in eight out of 18 practices. Moreover, the provider's feedback was very positive, describing the solution as fast, useful, and unintrusive. Our CDSS reduced clinical variability and revealed the usefulness of NLP and AI techniques for the evaluation and improvement of health care.

摘要

本文介绍了基于自然语言处理(NLP)和人工智能(AI)技术开发和实施临床决策支持系统(CDSS)的开创性实践经验。我们的CDSS会实时向初级保健医生通报有关医疗过程的建议。据我们所知,这是西班牙国家卫生系统中实施的首个实时CDSS。我们在18家医疗机构中的8家实现了依从率的提高。此外,医疗服务提供者的反馈非常积极,称该解决方案快速、有用且不会造成干扰。我们的CDSS减少了临床变异性,并揭示了NLP和AI技术在评估和改善医疗保健方面的有用性。

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