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我国医疗机构中药制剂新药转化政策的量化评价
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| 篇名： | 我国医疗机构中药制剂新药转化政策的量化评价 |
| TITLE： | Quantitative evaluation of policies for the commercialization of traditional Chinese medicine preparations in medical institutions into new drugs in China |
| 摘要： | 目的 对国内医疗机构中药制剂新药转化政策进行量化评价，为完善和优化我国医疗机构中药制剂新药转化政策体系提供参考。方法检索北大法宝数据库及相关部门官方网站，收集和筛选相关政策文件，运用ROST-CM6.0软件对政策文本进行文本挖掘，结合政策工具分析及相关文献构建PMC评价指标体系，通过二元赋值计算PMC指数并划分评价等级，利用MATLABR2024a软件绘制PMC曲面图，以揭示政策体系的结构特征与薄弱环节，并提出优化建议。结果与结论共纳入44份医疗机构中药制剂新药转化相关政策，构建出包含10个一级变量、44个二级变量的PMC指数模型。44份政策的PMC指数均值为6.07，评价等级为可接受水平。一级变量中“，政策性质“”政策方式“”政策评价”得分较高“，政策工具“”政策对象”等得分较低，主要表现为资金、人才及知识产权转化支持措施不够充分，政策对象覆盖有待拓展，转化支持系统性相对不足。建议相关部门在出台政策时，可强化资金、人才、知识产权支撑，增强地方特色适配性，扩大主体覆盖范围，制定专项支持政策，以推动更多临床价值高、特色优势明显的医疗机构中药制剂转化为新药。 |
| ABSTRACT： | OBJECTIVE To quantitatively evaluate the policies for the commercialization of traditional Chinese medicine preparations in medical institutions into new drugs， and to provide a reference for improving and optimizing China’s policy system for the commercialization of such preparations into new drugs.METHODS Relevant policy documents were retrieved from the PKULaw database and official websites of relevant departments. After collection and screening， the policy texts were text-mined with ROST-CM 6.0 software. A policy modeling consistency （PMC） evaluation index system was constructed by combining the analysis of policy instruments with relevant literature. The PMC indices were calculated through binary assignment， and the evaluation grades were classified. MATLAB R2024a software was used to draw PMC surface maps， so as to reveal the structural characteristics and weak links of the policy system and put forward optimization suggestions. RESULTS &CONCLUSIONS A total of 44 policies related to the commercialization of traditional Chinese medicine preparations in medical institutions into new drugs were included， and a PMC index model containing 10 first-level variables and 44 second-level variables was constructed. The mean PMC index of the 44 policies was 6.07， and the overall evaluation grade was acceptable. Among the first-level variables， “policy nature”“policy approach”“policy evaluation” scored relatively high， whereas “policy instruments”“policy targets” scored relatively low. These findings were mainly reflected in insufficient support measures for funding， professionals and intellectual property rights transformation， limited coverage of policy targets， and relatively inadequate systematic support for commercialization. It is recommended that relevant departments strengthen financial， talent and intellectual property support， enhance local adaptability， expand the coverage of target entities， and formulate special support policies， so as to promote the commercialization of more traditional Chinese medicine preparations with high clinical value and distinctive advantages into new drugs. |
| 期刊： | 2026年第37卷第20期 |
| 作者： | 高茜；陈宁；何照楠；范杰；张玉新；陈静佳；刘伟 |
| AUTHORS： | GAO Qian，CHEN Ning，HE Zhaonan，FAN Jie，ZHANG Yuxin，CHEN Jingjia，LIU Wei |
| 关键字： | 医疗机构中药制剂;中药新药;PMC指数模型;转化;量化分析 |
| KEYWORDS： | traditional Chinese medicine formulations in medical institutions;new traditional Chinese medicine drugs;PMC index model;commercialization;quantitative analysis |
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