Note Highlights: Surfacing Relevant Concepts from Unstructured Notes for Health Professionals

2017 IEEE International Conference on Healthcare Informatics (ICHI) Pub Date : 2017-08-01 DOI:10.1109/ICHI.2017.28

Vanessa López, J. Bettencourt-Silva, G. McCarthy, N. Mulligan, Fabrizio Cucci, Stéphane Deparis, M. Sbodio, Pierpaolo Tommasi, J. Segrave-Daly, C. Cullen, Ciaran Hennessy, Beth McKeon, K. Kelly, R. Olsen, J. Dinsmore, A. Brady, Nagesh Yadav, S. Kotoulas

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引用次数: 1

Abstract

Health and social care professionals are under increasing pressure to assimilate the ever-growing volume of data from case notes and electronic medical records. In this paper, we propose and evaluate with domain experts a cognitive system for patient-centric care that leverages and combines natural language processing, semantics, and learning from users over time to support care professionals making informed and timely decisions while reducing the burden of interacting with large volumes of unstructured patient notes. We propose methods for highlighting the entities embedded in the unstructured data and providing a personalized view of an individual. We evaluate through a user study and show a consensus between what the domain experts and the system consider relevant and discuss early feedback on the value of our Note Highlights methods to domain experts.

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注释亮点:从卫生专业人员的非结构化笔记中浮现相关概念

卫生和社会保健专业人员承受着越来越大的压力，需要消化病例记录和电子医疗记录中不断增长的数据量。在本文中，我们与领域专家一起提出并评估了一个以患者为中心的护理认知系统，该系统利用并结合了自然语言处理、语义和用户的学习，以支持护理专业人员做出明智和及时的决策，同时减少了与大量非结构化患者笔记交互的负担。我们提出了一些方法来突出显示嵌入在非结构化数据中的实体，并提供个人的个性化视图。我们通过用户研究进行评估，并在领域专家和系统认为相关的内容之间达成共识，并讨论关于我们的Note Highlights方法对领域专家的价值的早期反馈。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2017 IEEE International Conference on Healthcare Informatics (ICHI)

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