Hao Haijing, Zhang Kunpeng, Wang Weiguang, Gao Gordon
Department of Management Science and Information Systems, College of Management, University of Massachusetts Boston, Boston, MA, USA.
Department of Decision, Operations and Information Technologies, Robert H. Smith School of Business, University of Maryland, College Park, MD, USA.
Int J Med Inform. 2017 Mar;99:37-44. doi: 10.1016/j.ijmedinf.2016.12.007. Epub 2017 Jan 5.
Worldwide, patients have posted millions of online reviews for their doctors. The rich textual information in the online reviews holds the potential to generate insights into how patients' experience with their doctors differ across nations and how should we use them to improve our health service.
We apply customized text mining techniques to compare online doctor reviews from China and the United States, in order to measure the systematic differences in patient reviews between the two countries, and assess the potential insights that can be derived from this large volume of online text data.
We compare the textual reviews of obstetrics and gynecology (OBGYN) doctors from the two most popular online doctor rating websites in the U.S. and China, respectively: RateMDs.com and Haodf.com. We apply a customized text mining technique, Latent Dirichlet Allocation (LDA) topic modeling to identify the major topics in positive and negative reviews of those two countries. We then compare their similarities and differences.
Among the positive reviews, both Chinese and American patients talked about medical treatment, bedside manner, and appreciation/recommendation, but Chinese patients commented more about medical treatment while American patients focused more on recommendation. Also, reviews about bedside manner from Chinese patients were more related to doctors while on the American side, they were more about staff. This reflects the difference between the two countries' health systems. Further, among the negative reviews, both countries' patients talked about medical treatment, bedside manner, and logistics. However, Chinese patients focus more on the registration process, while American patients are more related to the staff, wait time, and insurance, which further shows the differences between the two nations' health systems.
Online doctor reviews contain valuable information that can generate insights on the similarities and differences of patient experience across nations. They are useful assets to assist healthcare consumers, providers, and administrators in moving toward a patient-centered care. In this age of big data, online doctor reviews can be a valuable source for international perspectives on healthcare systems.
在全球范围内，患者已为他们的医生发布了数百万条在线评价。在线评价中丰富的文本信息有可能让我们深入了解不同国家患者与医生相处的体验差异，以及我们应如何利用这些信息来改善医疗服务。
我们应用定制的文本挖掘技术来比较来自中国和美国的在线医生评价，以衡量两国患者评价的系统性差异，并评估从这大量在线文本数据中可获得的潜在见解。
我们分别比较了美国和中国最受欢迎的两个在线医生评级网站（RateMDs.com和好大夫在线）上妇产科医生的文本评价。我们应用一种定制的文本挖掘技术——潜在狄利克雷分配（LDA）主题建模，来识别这两个国家正面和负面评价中的主要主题。然后我们比较它们的异同。
在正面评价中，中国和美国患者都谈到了医疗治疗、 bedside manner（此处未明确具体含义，可能是“医患沟通态度”之类）以及赞赏/推荐，但中国患者更多地评论医疗治疗，而美国患者更关注推荐。此外，中国患者对bedside manner的评价更多与医生相关，而在美国方面，更多是关于工作人员。这反映了两国医疗体系的差异。此外，在负面评价中，两国患者都谈到了医疗治疗、bedside manner和后勤。然而，中国患者更关注挂号流程，而美国患者更多涉及工作人员、等待时间和保险，这进一步显示了两国医疗体系的差异。
在线医生评价包含有价值的信息，能够让我们深入了解不同国家患者体验的异同。它们是有助于医疗消费者、提供者和管理人员迈向以患者为中心的医疗服务的有用资产。在这个大数据时代，在线医生评价可以成为获取医疗体系国际视角的宝贵来源。
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