| 引用本文: | 兰娅菲,陈颖,韩朦,褚淑贞.中国药品监管政策网络演化和发展研究[J].中国现代应用药学,2023,40(17):2346-2353. |
| LAN Yafei,CHEN Ying,HAN Meng,CHU Shuzhen.Research on the Evolution and Development of Chinese Drug Regulatory Policy Network[J].Chin J Mod Appl Pharm(中国现代应用药学),2023,40(17):2346-2353. |
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| 摘要: |
| 目的 对中国药政侧重点的演化历程进行分析，以提高中国药品监管效力。方法 通过词频与社会网络分析，针对中国药品监管政策的演化过程进行词云与网络图的可视化呈现，并运用图密度、聚类系数、中介中心性、度中心性等指标，分析政策内容的不同演化特征。结果 不同时期网络特征存在明显差异，整体网络联系趋于紧密，结构趋于优化，且个体网络子群间联系逐步复杂化。但2018—2022年子群数量有所减少，核心节点转移。结论 在当下后疫情时期，要拓宽专项政策领域，加强政策关注点间的协同交叉。 |
| 关键词: 药品监管政策 演化 社会网络分析 词云 |
| DOI：10.13748/j.cnki.issn1007-7693.20221665 |
| 分类号:R95 |
| 基金项目:国家社会科学基金(15ZDB167) |
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| Research on the Evolution and Development of Chinese Drug Regulatory Policy Network |
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LAN Yafei, CHEN Ying, HAN Meng, CHU Shuzhen
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Research Center of National Drug Policy & Ecosystem, China Pharmaceutical University, Nanjing 211100, China
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| Abstract: |
| OBJECTIVE To analyze the evolution of the focus of Chinese pharmaceutical administration, so as to improving the effectiveness of drug regulation. METHODS Through word frequency and social network analysis, the word cloud and network graph were visualized for the evolution process of Chinese drug regulatory policies, and the different evolutionary characteristic of policies content were analyzed using graph density, clustering coefficient, betweenness centrality, degree centrality and other indicators. RESULTS There were differences in network characteristics in different periods, the overall network connection tended to be tight, the structure tended to be optimized, and the connection between individual network subgroups was gradually complicated. However, the number of subgroups decreased in 2018—2022, and the core nodes were transferred. CONCLUSION In the current special period of “epidemic economy”, it is necessary to broaden the special policy areas and strengthen the coordination and intersection of policy concerns. |
| Key words: drug regulatory policy evolution social network analysis word cloud |
