Data Mining of the Reviews from Online Private Doctors
Data Mining of the Reviews from Online Private Doctors
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DOI：
10.1089/tmj.2019.0159
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发表时间：
2019-11-01
影响因子：
4.7
通讯作者：
Zhou, Yingyi
中科院分区：
文献类型：
--
作者：
Liu, Jingfang;Zhang, Wei;Zhou, Yingyi
背景资料：在线健康社区（OHC）中共享的用户生成内容正在成为研究人员了解患者健康管理决策行为的宝贵资源。许多研究都集中在如何从OHC的在线评论中获取有用的信息。简介：本研究的重点是一个远程医疗服务称为在线私人医生（OPD），这是由领先的中国医生评论网站（PRW）提供。OPD审查没有得到太多关注。通过对这些评论进行数据挖掘，我们的目标是确定患者在使用OPD服务时正在谈论什么，以及他们是否对服务满意。材料与方法：我们使用Python网络爬虫收集了在中国PRW（haodf.com）上提供OPD服务的所有5，645名医生的41，029条评论和84，510条简短评论（标签）。混合方法（即，文献综述、主题发现、注释和情感分析）用于确定OPD综述意在表达的信息。结果如下：我们发现，OPD审查可以分为四个主题：能力（35.1%），沟通（29.4%），治疗（26.0%）和方便（9.5%）。在之前发现的主题方面，我们发现能力，沟通和治疗之前已经讨论过，但便利性是一个新兴的主题。情感分析表明，93.67%的评论表示积极的情绪，受试者工作特征（ROC）曲线下面积为0.64。此外，标签显示，只有0.72%（603/84，570）的评论对OPD服务持负面态度。标签的受试者根据能力（34.7%）、沟通（23.8%）、治疗（33.5%）和便利性（8.0%）进行分布。讨论：我们的研究结果表明，曾经使用过门诊的患者对服务相当满意。从他们的评论中，我们发现OPD有其独特的特点和方便。然而，它仍然有一些缺点，例如，电话连接的质量。无论是平台还是医生方面，都应该做出更多努力，让门诊更好、更规范。结论：门诊是一种新兴的远程医疗服务，仍然需要更多的时间和空间来发展。对于患者来说，它有助于减少调度和排队等问题。因此，它给人们的日常生活带来了更多的便利。今后应更加重视这项服务，因为它有助于减少医疗资源分配不均。
Background: User-generated content shared in the online health communities (OHCs) is becoming a valuable resource for researchers to understand patients' decision-making behaviors in the management of their health. Many studies have focused on how to obtain useful information from online reviews in OHCs. Introduction: This study focuses on a telemedicine service called Online Private Doctor (OPD), which is offered by a leading Chinese physician review website (PRW). OPD reviews have not received much attention. By data mining the reviews, our goal is to determine what patients are talking about when they use the OPD service and whether they are satisfied with the service or not. Materials and Methods: We used a Python web crawler to collect 41,029 reviews and 84,510 short reviews (labels) of all 5,645 physicians who offered the OPD service on a PRW (haodf.com) in China. Mixed methods (i.e., a literature review, topic discovery, annotation, and a sentiment analysis) were used to determine the information that the OPD reviews are meant to express. Results: We discovered that the OPD reviews can be categorized into four subjects: competence (35.1%), communication (29.4%), treatment (26.0%), and convenience (9.5%). In terms of previously discovered topics, we found that competence, communication, and treatment have been discussed before, but convenience is an emerging subject. The sentiment analysis indicated that 93.67% of the reviews indicated positive emotions, and the area under the receiver operating characteristic (ROC) curve is 0.64. Furthermore, the labels indicated that only 0.72% (603/84,570) of reviews were negative toward the OPD service. The subjects of the labels were distributed according to competence (34.7%), communication (23.8%), treatment (33.5%), and convenience (8.0%). Discussion: The findings of our study suggest that patients who ever used OPD have been quite satisfied with the service. From their reviews, we discovered that OPD has its special characteristics and is convenient. However, it still has some shortcomings, for example, the quality of the phone connection. In terms of both the platform and the doctors, more efforts should be made to make the OPD better and more regulated. Conclusion: OPD is an emerging telemedicine service that still needs more time and space to evolve. For patients, it helps reduce problems such as scheduling and queuing. Therefore, it brings more convenience to people's daily lives. In the future, more attention should be paid to this service, as it is helpful in reducing the uneven distribution of medical resources.