摘要
目的 基于LDA主题模型对2023年我国医疗健康领域的52份政策文本进行内容主题挖掘,并分析政策的特征和重点.方法 基于对52份医疗健康政策的阅读,并采用LDA主题模型对文献英文摘要进行无监督机器学习,以寻找文本的潜在主题并进行归类.结果 政策主要集中在5个主题上,分别为质控监管管理、中医药专科建设管理、执法数字化管理、城乡公卫管理和护理与绩效考核管理.这些主题涵盖了医保基金监管、医疗质量控制、中医药发展、数字化转型和公共卫生服务等方面.政策较多侧重于互联互通、医保基金监管、城乡医疗健康均衡方面.然而,政策在不同领域间存在不均衡的问题,如数字化和质量管理方面相对薄弱.结论 政策制定应注重平衡和解决内部矛盾,推动医疗健康事业全面、均衡发展,并提出政策评估机制的必要性.
Abstract
Objective Based on the LDA topic model,conducting content topic mining on 52 policy texts in the field of healthcare in China in 2023,and analysing the features and focus of the policies.Methods Using the reading of 52 healthcare policies and unsupervised machine learning of the English summaries of the literature using the LDA topic model in order to find and categorise the potential themes of the texts.Results It was found that the policies focused on five themes:quality control and regulation management,Chinese medicine speciality construction management,law enforcement digitalisation management,urban and rural public health management,and nursing and performance appraisal management.These themes covered the regulation of health insurance funds,quality control of healthcare,development of Chinese medicine,digital transformation and public health services.Policies were more concerned with connectivity,health insurance fund regulation,and urban-rural healthcare balance.However,policies were uneven across different areas,such as relative weakness in digitalisation and quality control.Conclusion It points out that policy making should focus on balancing and resolving internal contradictions in order to promote comprehensive and balanced development of healthcare,and suggests the need for a policy evaluation mechanism.
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万方数据