Identifying Patients' Preference During Their Hospital Experience. A Sentiment and Topic Analysis of Patient-Experience Comments via Natural Language Techniques.

IF 2 3区 医学 Q2 MEDICINE, GENERAL & INTERNAL
Patient preference and adherence Pub Date : 2025-07-16 eCollection Date: 2025-01-01 DOI:10.2147/PPA.S526623
Jie Yuan, Xiao Chen, Chun Yang, JianYou Chen, PengFei Han, YuHong Zhang, YuXia Zhang
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引用次数: 0

Abstract

Background: Open-ended questions in patient experience surveys provide a valuable opportunity for people to express and discuss their authentic opinions. The analysis of free-text comments can add value to quantitative measures by offering information which matters most to patients and by providing detailed descriptions of the service issues that closed-ended items may not cover.

Objective: To extract useful information from large amounts of free-text patient experience comments and to explore differences in patient satisfaction and loyalty between patients who provided negative comments and those who did not.

Methods: We collected free-text comments on a broad, open-ended question in a cross-sectional patient satisfaction survey. We adopted a mixed-methods approach involving a literature review, human annotation, and natural language processing technique to analyze free-text comments. The associations of patient satisfaction and loyalty scores with the occurrence of certain patient comments were tested via logistic regression analysis.

Results: In total, 28054 free-text comments were collected (comment rate: 72.67%). The accuracy of the machine learning approach and the deep learning approach for topic modeling and sentiment analysis was 0.98 and 0.91 respectively, indicating a satisfactory prediction. Participants tended to leave positive comments (69.0%, 19356/28054). There were 22 patient experience themes discussed in the open-ended comments. The regression analysis showed that the occurrence of negative comments about "humanity of care", "information, communication, and education", "sense of responsibility of staff", "technical competence", "responding to requests", and "continuity of care" was significantly associated with a worse patient satisfaction and loyalty, while the occurrence of negative comments about other aspects of healthcare services had no impact on patient satisfaction and loyalty.

Conclusion: The results of this study highlight the interpersonal and functional aspects of care, especially the interpersonal aspects, which are often the "moment of truth" during a service encounter when patients critically evaluate hospital services.

确定患者在住院期间的偏好。基于自然语言技术的患者体验评论情感与话题分析。
背景:开放式问题在患者经验调查提供了一个宝贵的机会,人们表达和讨论他们的真实意见。对自由文本评论的分析可以通过提供对患者最重要的信息和提供封闭式项目可能无法涵盖的服务问题的详细描述来增加定量测量的价值。目的:从大量的自由文本患者体验评论中提取有用的信息,探讨提供负面评论和不提供负面评论的患者在患者满意度和忠诚度方面的差异。方法:在横断面患者满意度调查中,我们收集了一个广泛的开放式问题的自由文本评论。我们采用了一种混合方法,包括文献综述、人工注释和自然语言处理技术来分析自由文本评论。通过logistic回归分析检验患者满意度和忠诚度得分与某些患者评论发生的关系。结果:共收集到自由文本评论28054条,评论率72.67%。机器学习方法和深度学习方法在主题建模和情感分析方面的准确率分别为0.98和0.91,表明预测结果令人满意。参与者倾向于留下积极的评价(69.0%,19356/28054)。在开放式评论中讨论了22个患者体验主题。回归分析表明,“护理人性化”、“信息、沟通和教育”、“员工责任感”、“技术能力”、“响应要求”、“护理连续性”等负面评价的出现与患者满意度和忠诚度的下降显著相关,而其他方面的负面评价的出现对患者满意度和忠诚度没有影响。结论:本研究的结果突出了护理的人际关系和功能方面,特别是人际关系方面,这往往是在患者批判性地评估医院服务时遇到的“关键时刻”。
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来源期刊
Patient preference and adherence
Patient preference and adherence MEDICINE, GENERAL & INTERNAL-
CiteScore
3.60
自引率
4.50%
发文量
354
审稿时长
6-12 weeks
期刊介绍: Patient Preference and Adherence is an international, peer reviewed, open access journal that focuses on the growing importance of patient preference and adherence throughout the therapeutic continuum. The journal is characterized by the rapid reporting of reviews, original research, modeling and clinical studies across all therapeutic areas. Patient satisfaction, acceptability, quality of life, compliance, persistence and their role in developing new therapeutic modalities and compounds to optimize clinical outcomes for existing disease states are major areas of interest for the journal. As of 1st April 2019, Patient Preference and Adherence will no longer consider meta-analyses for publication.
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