Feasibility of real-time satisfaction surveys through automated analysis of patients' unstructured comments and sentiments.
Feasibility of real-time satisfaction surveys through automated analysis of patients' unstructured comments and sentiments.
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DOI：
10.1097/qmh.0b013e3182417fc4
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发表时间：
2012-01-01
影响因子：
1.2
通讯作者：
Aron, David C
中科院分区：
文献类型：
--
作者：
Alemi, Farrokh;Torii, Manabu;Aron, David C
这篇文章展示了如何使用情感分析（一种对文本中表达的意见进行分类的人工智能程序）来设计实时满意度调查。为了提高参与度，实时调查必须非常简短。最简短的调查就是一张评论卡。患者的评论可以在为临床护理评级而组织的网站上、电子邮件中、医院投诉登记处或通过简化的满意度调查（如“分钟调查”）找到。情感分析使用词语之间的模式将评论分类为抱怨或赞扬。它进一步将投诉分类为不满意的具体原因，类似于在较长时间的调查中发现的广泛类别，如消费者对医疗保健提供者和系统的评估。通过这种方式，情感分析允许人们从评论列表中重新创建对较长满意度调查的响应。为了证明这一点，本文提供了对RateMDs.com网站上995条在线评论中表达的情绪的分析。我们关注的是哥伦比亚特区、马里兰州和弗吉尼亚州的儿科医生和妇产科医生。我们能够对患者不满意的原因进行分类，分析提供了如何改善他们的护理的信息。本文报告了评论分类的准确性。准确性将随着收到的评论数量的增加而提高。此外，我们使用下一次投诉的时间概念对医生进行排名。时间间隔控制图用于评估下一次投诉的时间是否超过历史模式，从而表明偏离规范。这些发现表明：(1)患者的评论很容易获得，(2)情绪分析可以将这些评论分类为抱怨/赞扬，(3)下一次投诉时间可以将这些分类转化为数字基准，可以追踪改善的影响。文中描述的程序表明，实时满意度调查是可能的。
This article shows how sentiment analysis (an artificial intelligence procedure that classifies opinions expressed within the text) can be used to design real-time satisfaction surveys. To improve participation, real-time surveys must be radically short. The shortest possible survey is a comment card. Patients' comments can be found online at sites organized for rating clinical care, within e-mails, in hospital complaint registries, or through simplified satisfaction surveys such as "Minute Survey." Sentiment analysis uses patterns among words to classify a comment into a complaint, or praise. It further classifies complaints into specific reasons for dissatisfaction, similar to broad categories found in longer surveys such as Consumer Assessment of Healthcare Providers and Systems. In this manner, sentiment analysis allows one to re-create responses to longer satisfaction surveys from a list of comments. To demonstrate, this article provides an analysis of sentiments expressed in 995 online comments made at the RateMDs.com Web site. We focused on pediatrician and obstetrician/gynecologist physicians in District of Columbia, Maryland, and Virginia. We were able to classify patients' reasons for dissatisfaction and the analysis provided information on how practices can improve their care. This article reports the accuracy of classifications of comments. Accuracy will improve as the number of comments received increases. In addition, we ranked physicians using the concept of time-to-next complaint. A time-between control chart was used to assess whether time-to-next complaint exceeded historical patterns and therefore suggested a departure from norms. These findings suggest that (1) patients' comments are easily available, (2) sentiment analysis can classify these comments into complaints/praise, and (3) time-to-next complaint can turn these classifications into numerical benchmarks that can trace impact of improvements over time. The procedures described in the article show that real-time satisfaction surveys are possible.