Impact of hospital complaint handling on promoting high-quality development of hospitals via an emotional language analysis model: a case study of a tertiary hospital service center in Quanzhou city, Fujian province.

IF 2.7 Q3 HEALTH CARE SCIENCES & SERVICES
Frontiers in health services Pub Date : 2025-08-26 eCollection Date: 2025-01-01 DOI:10.3389/frhs.2025.1610004
Caijiao Zheng, Yi Zhang, Xiaolong Lian, Jinxiu Ke, Hongxia Chen, Yiwen Chen
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Abstract

Background: In the healthcare service industry, patient complaints serve not only as a critical metric for assessing hospital service quality but also as a fundamental driver of high-quality hospital development. Through a systematic analysis of patients' perceptions, opinions, and emotional responses to hospital management within the complaint-handling process.

Methods: Therefore, this paper aims to develop a hospital complaint-handling analysis model to enhance public satisfaction with greater precision. First, complaint data from hospitals spanning January to December 2022-2024 was preprocessed using data cleaning, mechanical compression, word segmentation, and stop-word filtering techniques. Second, the DISC behavioral language model was employed to analyze key indicators, including hospital compensation frequency, total compensation amounts, patient appeal rates, complainants' satisfaction with the resolution process, and their overall satisfaction with complaint outcomes. Finally, a sentiment analysis model and an improved KANN-DBSCAN clustering model were applied to complaint data to precisely identify sentiment-related keywords and assess the intensity of negative emotions, providing hospitals with targeted improvement recommendations.

Results: This study applied the DISC behavioral model to medical complaints. DISC-based text analysis enabled tailored responses. Among 334 intervention and 341 control cases, satisfaction 93.39%, was higher in the intervention group 83.24%, indicating improved complaint resolution through behavior-informed communication strategies.

Conclusions: By analyzing patients' psychological needs and expectations, this study aims to minimize financial compensation and reduce patient appeals while enhancing overall complaint resolution satisfaction, which provides medical institutions with a more comprehensive, effective, and personalized complaint-handling strategy while simultaneously improving patients' healthcare experiences.

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基于情感语言分析模型的医院投诉处理对促进医院高质量发展的影响——以福建省泉州市某三级医院服务中心为例
背景:在医疗服务行业中,患者投诉不仅是评估医院服务质量的重要指标,也是医院高质量发展的根本动力。通过系统分析患者在投诉处理过程中对医院管理的看法、意见和情绪反应。方法:为此,本文旨在建立医院投诉处理分析模型,以提高公众满意度。首先,使用数据清洗、机械压缩、分词和停止词过滤技术对2022-2024年1月至12月的医院投诉数据进行预处理。其次,采用DISC行为语言模型分析关键指标,包括医院补偿频率、总补偿金额、患者申诉率、投诉人对解决过程的满意度以及对投诉结果的总体满意度。最后,将情绪分析模型和改进的KANN-DBSCAN聚类模型应用于投诉数据,精确识别与情绪相关的关键词,评估负面情绪的强度,为医院提供有针对性的改善建议。结果:本研究将DISC行为模型应用于医疗投诉。基于光盘的文本分析支持定制响应。在334例干预和341例对照中,干预组满意率为93.39%,干预组满意率为83.24%,表明行为知情沟通策略改善了投诉解决。结论:本研究旨在通过分析患者的心理需求和期望,在提高整体投诉解决满意度的同时,最大限度地减少患者的经济补偿和申诉,为医疗机构提供更全面、有效和个性化的投诉处理策略,同时改善患者的医疗体验。
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