Public attitudes and concerns regarding “medical insurance reimbursement”：an analysis based on text mining of Weibo comments
- VernacularTitle:基于微博评论文本挖掘分析公众对“医保报销”的态度和关注点
- Author:
Jinshi LIU
1
;
Pingping OUYANG
2
;
Xiaoxia CHEN
1
;
Haojuan CHANG
1
;
Liping XIAO
2
Author Information
1. School of Humanities and Management，Yunnan University of Chinese Medicine，Kunming 650500，China
2. Library of Yunnan University of Chinese Medicine，Kunming 650500，China
- Publication Type:Journal Article
- Keywords:
medical insurance reimbursement;
text mining;
social media platform;
natural language processing;
sentiment analysis;
semantic network analysis;
LDA topic model
- From:
China Pharmacy
2026;37(13):1667-1672
- CountryChina
- Language:Chinese
-
Abstract:
OBJECTIVE Based on comment texts from the Weibo platform， this study adopts the text mining method to systematically analyze the public’s emotional attitudes and core concerns of “medical insurance reimbursement”， and explore the public’s real experiences and feedback in the implementation of the current system. METHODS With “medical insurance reimbursement” as the keyword， Python web crawler technology was used to collect Weibo comment texts from December 2023 to April 2025. Word frequency analysis， sentiment analysis， semantic network analysis and Latent Dirichlet Allocation （LDA） topic models were adopted to mine the in-depth features of comment texts and investigate the public’s concerns and emotional attitudes toward “medical insurance reimbursement”. RESULTS A total of 3 645 valid comment texts were obtained. The overall emotional of the public toward “medical insurance reimbursement” was weakly positive： 66.4% of the comments contained positive emotions， and 32.4% contained negative emotions. Semantic network analysis indicated that positive public emotions mainly centered on the achievements of medical insurance reform and the improvement of security level， while negative emotions mainly focused on reimbursement rules， economic burden and the implementation of medical insurance policies. The LDA model identified eight core themes， mainly including access of new drugs to medical insurance catalogs， medical insurance support for traditional Chinese medicine and biomedicine， disputes over medical insurance coverage of specific medical items， cross-regional medical treatment and medical insurance settlement， medical insurance reimbursement and medical burden， as well as the approval of innovative drugs and medical insurance payment. CONCLUSIONS The public generally holds a positive attitude toward “medical insurance reimbursement”， yet still has many expectations in terms of policy implementation. On the premise of guaranteeing the sustainability of medical insurance funds， it is suggested to further improve the transparency and fairness of the reimbursement process， and promote the scientific， standardized and efficient development of the medical insurance system. Meanwhile， attention should be paid to public opinion feedback on social media， and the policy communication mechanism should be strengthened， so as to enhance the public’s sense of gain and trust in the medical insurance system.
