A Study on Internet News for Patient Safety Campaigns: Focusing on Text Network Analysis and Topic Modeling

一项关于互联网新闻在患者安全宣传活动中的应用研究:以文本网络分析和主题建模为重点

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Abstract

Background/Objectives: This study aimed to identify the main issues related to public patient safety campaigns reflected in Korean online news. This study utilized a text-mining method to identify keywords and topics related to patient safety campaigns. Methods: The data collection period was from 1 January 2022 to 31 December 2023, and 4110 news articles were extracted. Through data preprocessing, 2661 duplicated news and 1213 unrelated news were removed, and 236 news were selected. Using the NetMiner program, keyword co-occurrence frequency calculation, keyword centrality analysis, and topic modeling analysis were performed. Results: The results showed that the most frequently mentioned keywords with high degree centrality, betweenness centrality, and closeness centrality in online news were "hospital", "medical", "medicine", "project", and "treatment". The topics of online news related to the patient safety campaign were "patient-centered care for medical safety", "health promotion projects at a regional institution", "hand hygiene education to prevent infection", "healthcare quality improvement through the Mint Festival", and "safe use of medicines". Conclusions: This study analyzed patient safety campaign news topics using text network analysis and topic modeling. It was confirmed that patient safety campaigns are essential for fostering a patient safety culture, improving medical quality, and encouraging patient participation in hospitals. Therefore, to build a safe medical environment, it is necessary to establish an effective patient safety campaign for not only medical staff providing medical care, but also patients and their caregivers, and for this, cooperation and participation from various professional occupations are necessary.

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