基于药品企业质量风险大数据的现场监管策略优化研究

漆亮; 王琪; 刘雅慧; 夏雪琴; 郭文琼

doi:10.6039/j.issn.1001-0408.2024.01.02

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基于药品企业质量风险大数据的现场监管策略优化研究

药事管理 | 更新时间：2024-01-11

- 基于药品企业质量风险大数据的现场监管策略优化研究
- Optimization of on-site supervision strategy based on big data of quality risk in drug enterprises
- 中国药房 2024年35卷第1期页码：10-14
- 作者机构：
  
  1.江西省药品认证审评中心，南昌　330006
  2.太极计算机股份有限公司江西分公司，南昌　330096
- 作者简介：
  
  副主任药师。研究方向：药事管理。电话：0791-86207357。E-mail：759198268@qq.com
- 基金信息：
  
  江西省药品监督管理局科研项目(2022GL16)
- DOI：10.6039/j.issn.1001-0408.2024.01.02
  中图分类号： R95
- 纸质出版日期：2024-01-15，
  
  收稿日期：2023-06-20，
  
  修回日期：2023-11-22，
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漆亮,王琪,刘雅慧等.基于药品企业质量风险大数据的现场监管策略优化研究 ^Δ[J].中国药房,2024,35(01):10-14.

QI Liang,WANG Qi,LIU Yahui,et al.Optimization of on-site supervision strategy based on big data of quality risk in drug enterprises[J].ZHONGGUO YAOFANG,2024,35(01):10-14.
漆亮,王琪,刘雅慧等.基于药品企业质量风险大数据的现场监管策略优化研究 ^Δ[J].中国药房,2024,35(01):10-14. DOI： 10.6039/j.issn.1001-0408.2024.01.02.

QI Liang,WANG Qi,LIU Yahui,et al.Optimization of on-site supervision strategy based on big data of quality risk in drug enterprises[J].ZHONGGUO YAOFANG,2024,35(01):10-14. DOI： 10.6039/j.issn.1001-0408.2024.01.02.

摘要

药品现场监管是一种以风险为本的监管体系，要求针对药品企业质量风险和隐患科学地制定监管计划，并结合其风险水平合理配置监管资源，实施分类监管措施。本研究通过分析药品现场监管工作的难点，建立了药品企业质量风险专题库、药品企业质量风险监测指标体系，以此构建药品企业质量风险监测业务支撑体系，并依托该支撑体系建立了质量风险分类方法、差异化抽查策略和业务辅助可视化系统，运用该支撑体系获知药品企业风险等级，从而创新了药品现场监管方法，优化了监管策略。以江西省为例，验证了该支撑体系可引导对样本药品企业的风险评估，可在药品现场监管的技术审评、方案编制、现场执行及综合评估过程中提升检查的靶向性，有效提高监管质量和效率。

Abstract

On-site supervision is a risk-based regulatory system that requires the scientific development of supervision plans for quality risks and hidden dangers in pharmaceutical enterprises， the rational allocation of supervision resources based on their risk levels， and the implementation of classified supervision measures. In this study， the quality risk monitoring business support system is set up for pharmaceutical enterprises by establishing the quality risk expert database and quality risk monitoring index system for pharmaceutical enterprises based on the difficulty analysis of on-site drug supervision. Based on this support system， the quality risk classification method， the differentiated spot check strategy and business auxiliary visualization system are established. This support system is used to learn the risk level of pharmaceutical enterprises， so as to innovate supervision methods and optimize monitoring strategies. Taking Jiangxi Province as an example， it is verified that the support system can guide the risk assessment of sample enterprises， can improve the targeting of on-site drug supervision in the process of technical review， scheme editing， on-site implementation and comprehensive evaluation， and can effectively improve the quality and efficiency of supervision.

关键词

药品企业药品监管质量风险大数据现场监管策略优化

Keywords

drug supervisionquality riskbig dataon-site supervisionstrategy optimization

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