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中国管理科学 ›› 2020, Vol. 28 ›› Issue (5): 122-135.doi: 10.16381/j.cnki.issn1003-207x.2020.05.012

• 论文 • 上一篇    下一篇

“互联网+医疗健康”背景下考虑患者反馈机制的药品质量监管策略研究

朱立龙1,2, 荣俊美2   

  1. 1. 山东大学管理学院, 山东 济南 250100;
    2. 山东师范大学商学院, 山东 济南 250014
  • 收稿日期:2019-08-30 修回日期:2020-03-08 出版日期:2020-05-30 发布日期:2020-05-30
  • 通讯作者: 朱立龙(1983-),男(汉族),山东日照人,山东大学管理学院,博士后,山东师范大学商学院,教授,研究生导师,同济大学管理科学与工程专业,博士,研究方向:供应链管理与质量管理,E-mail:zhulilong2008@126.com. E-mail:zhulilong2008@126.com
  • 基金资助:
    教育部人文社科基金规划项目(17YJA630147);山东省自然科学基金面上资助项目(ZR2019MG017);国家社会科学基金重点资助项目(13AGL012)

Drug Quality Supervision Strategy Considering Patient Feedback Mechanism under the Background of “Internet+Medical Health”

ZHU Li-long1,2, RONG Jun-mei2   

  1. 1. School of Management, Shandong University, Ji'nan 250100, China;
    2. School of Business, Shandong Normal University, Ji'nan 250014, China
  • Received:2019-08-30 Revised:2020-03-08 Online:2020-05-30 Published:2020-05-30

摘要: 药品质量关乎公众生命健康、国民经济发展、社会稳定和国家安全,一直以来都是政府和全社会关注的热点问题之一。"互联网+医疗健康"背景下药品流通速度加快使得药品安全问题影响范围扩大,因此,建立患者反馈机制是促进互联网药品质量监管的有效方式。考虑患者反馈机制下如何设计互联网药品质量监管策略的问题,基于演化博弈理论,构建了政府部门、药品生产商、医药电商和患者参与的药品质量监管四方演化博弈模型,通过分析各博弈主体策略选择的稳定性,并基于Lyapunov第一法则对复制动态系统十六种均衡点进行稳定性分析,研究了促进药品生产商提供高质量药品的政府监管策略和患者反馈机制,并利用Matlab 2017仿真分析了各关键要素对策略演化的影响。研究结果表明:1)患者倾向于失真评价或投诉率较低时,医药电商更倾向于选择药品质量不检测,不利于互联网药品质量安全;2)患者失真评价下,不存在药品生产商提供高质量药品的稳定策略组合,而真实评价下有效的反馈机制和监管机制可使互联网药品质量安全具有稳定性;3)提高患者评价(正面评价或负面评价)带给医药电商和药品生产商的声誉价值增加或声誉损失,将会使药品生产商选择提供高质量药品做为稳定策略;4)降低患者失真评价和投诉维权行为的增加,均可增强药品生产商提供高质量药品的稳健性。最后,结合演化博弈模型和仿真分析结果,为完善药品质量监管机制提出了对策与建议。

关键词: 互联网+医疗健康, 患者反馈机制, 药品质量监管, 演化博弈, 仿真分析

Abstract: Drug quality is related to public life and health, national economic development, social stability and national security, and has always been one of the hot issues concerned by the government and the whole society. Accelerating circulation of medicines in the context of "Internet + medical health" has expanded the scope of drug safety issues, therefore, establishing a patient feedback mechanism is an effective way to promote Internet drug quality supervision. Considering how to design an Internet drug quality supervision strategy under the patient feedback mechanism, based on the evolutionary game theory, a four-party evolutionary game model of drug quality supervision is constructed by drug manufacturers, medical e-commerce companies, government regulatory authorities and patients. The government regulation strategy and patient feedback mechanism to promote the supply of high-quality drugs by drug manufacturers are explored by analyzing the stability of the each player's strategy selection and the stability of 16 equilibrium points of replication dynamic system based on Lyapunov first rule. And the impact of each element on the evolution of various strategies is performed simulation analysis using Matlab 2017. The results show that: 1) The more likely patients are to have a distorted evaluation or a lower complaint rate, the more likely medical e-commerce companies are to choose not to test the quality of drugs, which is not conducive to the quality and safety of drugs on the Internet; 2) Under the evaluation of patient distortion, there is no stable strategy combination for drug manufacturers to provide high-quality drugs, and the effective feedback mechanism and supervision mechanism under real evaluation can make the quality of Internet drugs stable; 3) Improving the reputation added or reputation loss brought by patients' evaluation for pharmaceutical e-commerce companies and pharmaceutical manufacturers will make drug manufacturers choose to provide high-quality drugs as a stable strategy; 4) Reducing the rate of distorted comment of patients and increasing the behavior of complaining to defend rights both can enhance the stability of drug manufacturers in providing high-quality drugs. Finally, combined with evolutionary game model and simulation analysis results, the countermeasures and suggestions for improving the drug quality supervision mechanism are proposed.

Key words: "Internet + medical health", patient feedback mechanism, drug quality supervision, evolutionary game, simulation analysis

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