Exploring the Online Doctor-Patient Interaction on Patient Satisfaction Based on Text Mining and Empirical Analysis

被引:134
|
作者
Chen, Shuqing [1 ]
Guo, Xitong [1 ]
Wu, Tianshi [1 ]
Ju, Xiaofeng [1 ]
机构
[1] Harbin Inst Technol, Sch Management, Harbin, Peoples R China
基金
中国国家自然科学基金;
关键词
Online doctor-patient interaction; text mining and econometrics; informational support; emotional support; HEALTH-CARE; SOCIAL SUPPORT; CO-CREATION; COMMUNICATION; IMPACT; QUALITY; PARTICIPATION; COMMUNITIES; INFORMATION; ENGAGEMENT;
D O I
10.1016/j.ipm.2020.102253
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In the online health community, the doctor-patient interaction is one of the most important functional modules. A large volume of unstructured text data has been generated in the doctor-patient interaction process. This development is worth exploring. In this paper, we mainly explore the influences of online doctor-patient interaction content on patient satisfaction. We collected the online doctor-patient interaction text data from a big online health community (http://haodf.com) in China from January 2015 to December 2016, followed by the use of text mining and econometrics to test our hypotheses. The results indicate that the patient's activeness has a positive effect on a doctor's informational and emotional support. Furthermore, both a doctor's informational and emotional support are known to have a positive effect on patient satisfaction. More significantly, the effect of emotional support on patient satisfaction is more significant than that of informational support. In addition, the patient's disease severity strengthens the link between a doctor's informational and emotional support and that of patient satisfaction. This study has far-reaching significance for a better understanding of the doctor-patient interaction mechanism.
引用
收藏
页数:16
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