| 引用本文：宋佳, 范成鑫, 王婉晨, 艾旭峰, 李秋莎, 尹文强, 马东平.利益相关者视角下我国药品集中带量采购政策研究——基于政策工具的文本分析[J].中国卫生政策研究,2022,15(2):11-17 |
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| 利益相关者视角下我国药品集中带量采购政策研究——基于政策工具的文本分析 |
| 投稿时间：2021-12-21 修订日期：2022-02-03 PDF全文浏览 HTML全文浏览 |
| 宋佳1,3,4, 范成鑫1,3,4, 王婉晨2,3,4, 艾旭峰1,3,4, 李秋莎2,3,4, 尹文强1,3,4, 马东平1,3,4 |
1. 潍坊医学院管理学院 山东潍坊 261053;
2. 潍坊医学院公共卫生学院 山东潍坊 261053;
3. "健康山东"重大社会风险预测与治理协同创新中心 山东潍坊 261053;
4. 健康相关重大社会风险预警协同创新中心 上海 200032 |
| 摘要:目的：通过对我国药品集中带量采购相关政策文本进行剖析，探讨现有政策侧重点及不足，以期为我国未来药品集中带量采购政策制定及优化提供参考依据。方法：采用内容分析法，选取16份药品集中带量采购相关政策为研究对象，基于政策工具及利益相关者两个维度进行分析。结果：政策工具维度共筛选出147个政策编码，其中命令与规制型工具占56.5%(83/147)、激励型工具占3.4%(5/147)、能力建设型工具占28.6%(42/147)、系统变革型工具占2.0%(3/147)、信息与劝诫型工具占9.5%(14/147)；利益相关者维度共筛选出323个政策编码，其中药品生产企业占20.7%(67/323)、药品流通企业占6.8%(22/323)、政府相关部门占34.1%(110/323)、医疗机构占29.1%(94/323)、患者占9.3%(30/323)。结论：政策工具结构不均衡，利益相关者格局不协调，政策工具与利益相关者耦合性不强，应结合药品集中带量采购政策特征及发展趋势优化各类政策工具使用比例；兼顾多方利益相关者，增强利益相关者凝聚力；推进政策工具与利益相关者有效结合，提高政策的靶向精准度。 |
| 关键词:药品集中带量采购 政策工具 利益相关者 政策分析 |
| 基金项目:山东省自然科学基金(ZR2019MG010) |
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| Study on Centralized Volume-based Drug Purchase Policy in China from the perspective of stakeholders: A textual analysis based on policy tools |
| SONG Jia1,3,4, FAN Cheng-xin1,3,4, WANG Wan-chen2,3,4, AI Xu-feng1,3,4, LI Qiu-sha2,3,4, YIN Wen-qiang1,3,4, MA Dong-ping1,3,4 |
1. School of Management, Weifang Medical University, Weifang Shandong 261053, China;
2. School of Public Health, Weifang Medical University, Weifang Shandong 261053, China;
3. "Health Shandong"Severe Social Risk Prevention and Management Synergy Innovation Center, Weifang Shandong 261053, China;
4. Collaborative Innovation Center of Social Risks Governance in Health, Shanghai 200032, China |
| Abstract:Objective: By analyzing the relevant policy texts of centralized volume-based drug purchase in China, this study discusses the key points and shortcomings of the existing policy tools, to provide a reference basis for the formulation and optimization of centralized drug procurement policy in China in the future. Methods: Using the content analysis method, 16 policies related to centralized quantity procurement of drugs were selected for the study and analyzed based on two dimensions of policy tools and stakeholders. Results: A total of 147 policy codes were selected from the dimension of policy tools, among which command and regulation tools accounted for 56.5% (83/147), incentive tools accounted for 3.4% (5/147), capacity-building tools accounted for 28.6% (42/147), system transformation tools accounted for 2.0% (3/147), information and persuasion tools accounted for 9.5% (14/147); A total of 323 policy codes were screened out from the stakeholder dimension, including 20.7% (67/323) drug manufacturers, 6.8% (22/323) drug distribution enterprises, 34.1% (110/323) government sectors, 29.1% (94/323) medical institutions, and 9.3% (30/323) patients. Conclusion: It was found in the analysis that the structure of policy tools is unbalanced, the pattern of stakeholders is not coordinated, and the coupling between policy tools and stakeholders is not strong. The use ratio of various policy tools should be optimized by taking into account the characteristics and development trend of centralized volume-based drug procurement policy, taking into account multiple stakeholders and enhancing the cohesiveness of stakeholders, promoting the effective combination of policy tools and stakeholders and raising the targeting accuracy of policies. |
| Key words:Centralized volume-based drug purchase Policy tools Stakeholder Policy analysis |
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