基于LDA和情绪分析的医疗服务质量评估:七种慢性疾病的例子
1Faculty of Management and Economics, Kunming University of Science and Technology, Kunming, Yunnan, China.
Digital health
|March 11, 2024
概括
这项研究分析了患者评论,以确定慢性非传染性疾病 (CND) 患者医疗服务的障碍. 改善住院和注册流程是提高患者满意度和医院效率的关键.
科学领域:
- 医疗保健管理的管理
- 患者体验研究 研究研究
- 数据科学在医学中的数据科学
背景情况:
- 慢性非传染性疾病 (CNDs) 对医疗保健系统构成重大负担.
- 评估患者对医疗服务的看法对于质量改善至关重要.
- 了解CND患者获得和提供医疗保健的障碍至关重要.
研究的目的:
- 调查慢性非传染性疾病患者如何评估医疗服务.
- 确定CND患者在医疗服务过程中遇到的关键障碍.
- 为医院提供可操作的见解,以提高效率和患者满意度.
主要方法:
- 分析了来自7个选定的CND的Haodaifu网站的15,682份医疗服务评论.
- 隐藏的迪里克莱特分配 (LDA) 的应用用于主题分析.
- 使用二进制长短期记忆 (LSTM) 进行情绪分析.
- 采用值,TOPSIS和灰色相关性模型进行质量评估.
- 实施了障碍模型,以确定医疗服务的限制因素.
主要成果:
- 高血压患者表现出良好的灰色相关性接近性;支气管炎患者表现出低相关性.
- 确定的主要障碍是住院流程和注册服务,约占问题的30%.
- 对于其他CND,观察到中级的相关性.
结论:
- 医院应优先优化住院过程和注册服务,以提高效率.
- 解决这些关键障碍,可以显著改善患者满意度.
- 医疗服务的根本优化是必要的,以有效地满足CND患者的需求.
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