What patients like or dislike in physicians: Analyzing drivers of patient satisfaction and dissatisfaction using a digital topic modeling approach
作者：
Highlights：
• The current research proposed a text mining approach to investigate the drivers of patient satisfaction and dissatisfaction across different types of diseases.
• Drawing on Herzberg's two-factor theory, this research identified the key topics of patient satisfaction and dissatisfaction expressed in online doctor reviews.
• The text mining method based on combining Sentinet and LDA was applied to disclose the semantics of patients’ healthcare experiences.
• The classification results reveal that the proposed model that analyzes patients’ opinions toward different aspects of care outperformed other state-of-the-art models.
摘要
•The current research proposed a text mining approach to investigate the drivers of patient satisfaction and dissatisfaction across different types of diseases.•Drawing on Herzberg's two-factor theory, this research identified the key topics of patient satisfaction and dissatisfaction expressed in online doctor reviews.•The text mining method based on combining Sentinet and LDA was applied to disclose the semantics of patients’ healthcare experiences.•The classification results reveal that the proposed model that analyzes patients’ opinions toward different aspects of care outperformed other state-of-the-art models.
论文关键词：Patient satisfaction,Patient dissatisfaction,Text mining,Topic modeling,LDA,Sentiment analysis
论文评审过程：Received 29 July 2020, Revised 4 December 2020, Accepted 11 January 2021, Available online 22 January 2021, Version of Record 22 January 2021.
论文官网地址：https://doi.org/10.1016/j.ipm.2021.102516
