| 任学毅,杨惠莲,李绪伦,邹江.药品监督管理中质量数据分析系统的应用研究[J].中国药事,2021,35(10):1087-1093 |
| 药品监督管理中质量数据分析系统的应用研究 |
| On Application of Quality Data Analysis System in Drug Supervision and Management |
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| DOI：10.16153/j.1002-7777.2021.10.001 |
| 中文关键词: 质量数据 分析系统 药品监管 应用 |
| 英文关键词: quality data analysis system drug supervision application |
| 基金项目:重庆市技术创新与应用示范专项“基于智慧监管下的全市药品质量大数据库建设与应用”(编号 cstc2018jscx-mszdX0119) |
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| 摘要点击次数: 621 |
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| 中文摘要: |
| 目的：探索药品安全风险“智慧监管”的有效途径，促进药品监管模式转变升级。方法：根据药品检验结果数据和不良反应信息等指标探索建立药品质量量化评价体系，在前期建立的药品质量数据库基础上，根据建立的药品质量量化评价体系构建药品质量数据分析系统，从质量信息报表功能和质量风险信息提示函功能等方面深度开发数据分析系统在药品监管方面的应用。结果与结论：药品质量量化评价体系能够对进入药品质量数据库的每批药品初步实现量化评价；药品质量数据分析系统的主要功能包括数据存储服务、数据模型服务、数据发布服务和数据应用；数据分析系统在药品监管中的应用主要包括生成药品质量信息报表和药品质量风险信息提示函等，能够及时筛出高危品种信息和发现问题趋势， 指导监管部门实施精准靶向干预和制定科学抽检方案，为药品监管部门践行药品智慧监管理念提供技术支持。 |
| 英文摘要: |
| Objective: To explore the effective ways of “smart supervision” on drug safety risks and promote the transformation and upgrading of drug supervision models. Methods: According to the data of drug test results and adverse reaction information, the quantitative evaluation system of drug quality was explored and established. The drug quality data analysis system was constructed on the basis of the drug quality database established in the early stage and the established drug quality quantitative evaluation system. The application of data analysis system in drug supervision was deeply developed from the functions of quality information report and quality risk information reminder, etc. Results and Conclusion: The quantitative evaluation system of drug quality could preliminarily finish the quantitative evaluation of each batch of drugs entering the drug quality database. The main functions of drug quality data analysis system included data storage service, data model service, data release service and data applications. Application of data analysis system in drug supervision mainly included the generation of drug quality information reports and drug quality risk information reminders. It could timely screen out the information of high-risk varieties, discover the problems, guide drug regulatory authorities to implement precisely targeted intervention, and make scientific sampling plans so as to provide technological support in practicing the concept of "smart drug supervision" for drug supervision departments. |
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