Innovative information visualization of electronic health record data: a systematic review.
Innovative information visualization of electronic health record data: a systematic review.
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电子健康记录数据的创新信息可视化：系统评价。
DOI：
10.1136/amiajnl-2014-002955
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发表时间：
2015-03
期刊：
影响因子：
--
通讯作者：
Hammond WE
中科院分区：
文献类型：
--
作者：
West VL;Borland D;Hammond WE
目的 本研究调查 1996 年至 2013 年间报告的可视化技术的使用情况，并评估用于知识发现的电子健康记录 (EHR) 数据信息可视化的创新方法。方法 2013 年 5 月至 7 月，使用 MEDLINE 和 Web of Knowledge 进行电子文献检索，并辅以引文检索、灰色文献检索和参考文献列表评审。使用一般搜索术语来确保全面的文档搜索。结果从891篇文章开始，通过消除191篇重复文章减少了文章数量。开发了一个矩阵，用于对所有摘要进行分类，并帮助确定那些被排除在审查之外的摘要。最终分析纳入18篇文章。讨论 几种可视化技术已被广泛研究。最成熟的系统是 LifeLines 及其应用程序，如 LifeLines2、EventFlow 和 LifeFlow。最初，研究重点是单个患者的记录以及与一名患者相关的复杂数据的可视化。自 2010 年以来，正在研究的技术用于处理大量患者记录和事件。大多数是线性的，允许通过缩放和缩放来调整大小进行交互。颜色、密度和过滤技术通常用于可视化。结论 随着电子医疗数据量的迅速增加，如果以创新和有效的方式管理数据，知识发现的潜力将是巨大的。我们确定了之前 EHR 可视化研究发现的挑战，这将帮助寻求设计和改进可视化技术的研究人员。
Objective This study investigates the use of visualization techniques reported between 1996 and 2013 and evaluates innovative approaches to information visualization of electronic health record (EHR) data for knowledge discovery. Methods An electronic literature search was conducted May–July 2013 using MEDLINE and Web of Knowledge, supplemented by citation searching, gray literature searching, and reference list reviews. General search terms were used to assure a comprehensive document search. Results Beginning with 891 articles, the number of articles was reduced by eliminating 191 duplicates. A matrix was developed for categorizing all abstracts and to assist with determining those to be excluded for review. Eighteen articles were included in the final analysis. Discussion Several visualization techniques have been extensively researched. The most mature system is LifeLines and its applications as LifeLines2, EventFlow, and LifeFlow. Initially, research focused on records from a single patient and visualization of the complex data related to one patient. Since 2010, the techniques under investigation are for use with large numbers of patient records and events. Most are linear and allow interaction through scaling and zooming to resize. Color, density, and filter techniques are commonly used for visualization. Conclusions With the burgeoning increase in the amount of electronic healthcare data, the potential for knowledge discovery is significant if data are managed in innovative and effective ways. We identify challenges discovered by previous EHR visualization research, which will help researchers who seek to design and improve visualization techniques.
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DOI：
10.1136/bmj.b2535
发表时间：
2009-07-21
期刊：
BMJ (Clinical research ed.)
影响因子：
--
作者：
Moher D;Liberati A;Tetzlaff J;Altman DG;PRISMA Group
通讯作者：
PRISMA Group
影响因子：
2.8
作者：
Shahar, Y;Cheng, C
通讯作者：
Cheng, C
影响因子：
7.5
作者：
Martins, Susana B.;Shahar, Yuval;Goldstein, Mary K.
通讯作者：
Goldstein, Mary K.
影响因子：
5.5
作者：
Bashyam, Vijayaraghavan;Hsu, William;Taira, Ricky K.
通讯作者：
Taira, Ricky K.
影响因子：
7.5
作者：
Klimov, Denis;Shahar, Yuval;Taieb-Maimon, Meirav
通讯作者：
Taieb-Maimon, Meirav