Mining and exploring care pathways from electronic medical records with visual analytics
Mining and exploring care pathways from electronic medical records with visual analytics
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DOI：
10.1016/j.jbi.2015.06.020
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发表时间：
2015-08-01
影响因子：
4.5
通讯作者：
Hu, Jianying
中科院分区：
文献类型：
--
作者：
Perer, Adam;Wang, Fei;Hu, Jianying
目的：为了获得数据驱动的见解，我们开发了Care Pathway Explorer，这是一个从患者EMR数据中挖掘和可视化一组频繁事件序列的系统。我们的目标是利用历史EMR数据提取常见的序列的医疗事件，如诊断和治疗，并调查这些序列如何与患者outcome.Materials和方法：护理路径资源管理器使用频繁的序列挖掘算法，适用于处理真实世界的属性的EMR数据，包括处理事件并发性，多层次的细节，时间的背景下，和结果。挖掘的模式，然后在一个交互式的用户界面，包括新的概述和流visualizations.Results可视化：我们使用该系统来分析诊断和治疗的高血压和糖尿病的先决条件的高血压患者的队列，并展示了从EMR数据挖掘模式的临床相关性。被确定的模式，对应于临床和出版的知识，其中一些未知的医生在discovery.Conclusion：护理路径浏览器，它结合了频繁的序列挖掘技术与先进的可视化支持数据驱动的见解集成到护理路径发现。(C)2015 Elsevier Inc. All rights reserved.
Objective: In order to derive data-driven insights, we develop Care Pathway Explorer, a system that mines and visualizes a set of frequent event sequences from patient EMR data. The goal is to utilize historical EMR data to extract common sequences of medical events such as diagnoses and treatments, and investigate how these sequences correlate with patient outcome.Materials and methods: The Care Pathway Explorer uses a frequent sequence mining algorithm adapted to handle the real-world properties of EMR data, including techniques for handling event concurrency, multiple levels-of-detail, temporal context, and outcome. The mined patterns are then visualized in an interactive user interface consisting of novel overview and flow visualizations.Results: We use the proposed system to analyze the diagnoses and treatments of a cohort of hyperlipidemic patients with hypertension and diabetes pre-conditions, and demonstrate the clinical relevance of patterns mined from EMR data. The patterns that were identified corresponded to clinical and published knowledge, some of it unknown to the physician at the time of discovery.Conclusion: Care Pathway Explorer, which combines frequent sequence mining techniques with advanced visualizations supports the integration of data-driven insights into care pathway discovery. (C) 2015 Elsevier Inc. All rights reserved.