Yu Xiaofan, Huang Huanhuan, Lin Kexin, Wang Huan, Zheng Shuangjiang, Ran Xu, Liu Yang, Wu Hao
Department of Medical Affairs Administration, The Southwest Hospital of Army Medical University, Chongqing 400038, China.
The Design Academy, Sichuan Fine Arts Institute, Chongqing 400053, China.
J Nurs Manag. 2025 Jul 11;2025:8183250. doi: 10.1155/jonm/8183250. eCollection 2025.
As the healthcare landscape progressively adopts a patient-centered paradigm, the imperative to enhance patient experience has become more pronounced. Efforts to improve patient experience have yielded modest results, partly due to limited understanding of the key factors influencing patient expectations. To explore the determinants of patient experiences through analyzing patient feedbacks, assisting healthcare institutions in prioritizing service improvements. A digital topic modeling approach was employed. Data were derived from a secondary analysis of the National Patient Experience Base, incorporating patient feedback from 226 hospitals. Initially, the feedback text data underwent a cleansing process, and the sentiment intensity within the text was quantified using the SnowNLP algorithm, and XGBoost classifier was utilized to categorize sentiments as positive or negative. Subsequently, the feedbacks were subjected to topic clustering using the BERT model and X-means clustering algorithm. Third, TextRank was applied to extract significant keywords from each cluster, and these keywords were analyzed to identify the determinants that impact patient experience. A total of 4689 patients' feedbacks were collected, comprising 2918 outpatients and 1771 inpatients from 165 tertiary and 61 secondary hospitals across 24 provinces. Through cluster analysis, 10 main clusters emerged (two of which were positive response and eight were negative response). By qualitatively synthesizing, patient experiences were distilled into five determinants: treatment, service, environment, economic, and process. The findings underscore the importance of a holistic approach to patient experience enhancement, where healthcare providers must address not only the clinical aspects of care but also the service delivery, environmental conditions, economic considerations, and procedural efficiency. By identifying and prioritizing the improvement of these determinants, healthcare organizations can tailor their services to better meet patient expectations and enhance overall satisfaction.
随着医疗保健领域逐渐采用以患者为中心的模式,提升患者体验的紧迫性变得更加明显。改善患者体验的努力取得了一定成效,但部分原因是对影响患者期望的关键因素理解有限。通过分析患者反馈来探索患者体验的决定因素,以协助医疗机构确定服务改进的优先顺序。采用了一种数字主题建模方法。数据来自对国家患者体验库的二次分析,纳入了226家医院的患者反馈。首先,对反馈文本数据进行清洗,使用SnowNLP算法量化文本中的情感强度,并利用XGBoost分类器将情感分类为积极或消极。随后,使用BERT模型和X-means聚类算法对反馈进行主题聚类。第三,应用TextRank从每个聚类中提取重要关键词,并对这些关键词进行分析以确定影响患者体验的决定因素。共收集了4689份患者反馈,包括来自24个省份165家三级医院和61家二级医院的2918名门诊患者和1771名住院患者。通过聚类分析,出现了10个主要聚类(其中两个是积极反馈聚类,八个是消极反馈聚类)。通过定性综合,患者体验被提炼为五个决定因素:治疗、服务、环境、经济和流程。研究结果强调了采用整体方法提升患者体验的重要性,医疗服务提供者不仅必须解决护理的临床方面问题,还必须关注服务提供、环境条件、经济因素和程序效率。通过识别并确定这些决定因素改进的优先顺序,医疗组织可以调整其服务以更好地满足患者期望并提高总体满意度。