文章摘要
李杨.门诊西药房退药情况分析与改进措施探讨[J].中国药事,2019,33(8):959-964
门诊西药房退药情况分析与改进措施探讨
Analysis of the Reasons for the Drug Returns in Outpatient Pharmacy and the Improvement Measures
投稿时间:2019-04-16  
DOI:10.16153/j.1002-7777.2019.08.018
中文关键词: 门诊  退药  原因分析  措施
英文关键词: outpatient  the drug returns  analysis of the reasons  measures
基金项目:
作者单位
李杨 陆军特色医学中心, 重庆 400042 
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中文摘要:
      目的:了解我院门诊西药房退药情况,探索降低门诊退药率的管理措施,促进患者安全合理用药。方法:对我院门诊西药房2017年8月-2018年8月的所有处方进行收集和统计,对所有退药处方的退药情况以及退药原因经Excel软件进行退药数据处理,进行帕累托图分析,按分类项目统计频数,计算累计频率,制作退药原因统计分类表并绘制帕累托图,同时分析退药原因的主要、次要、一般因素。结果:总量有1324760份处方,其中有1500份为退药处方,占比为1.13‰;退药的原因根据积累频率分三类因素,第一类为主要因素,即A类,一般其累积频率在30%~80%之间;第二类为次要因素,即B类,一般其累积频率在80%~90%之间;第三类为一般因素,即C类,一般其累积频率在90%~100%之间。对药物退换的原因进行分析,发现退药最多的原因是医务人员录入错误的药物信息,共为292次,占所有退换药物原因的19.47%;结论:应该建立健全药物处方的各种管理制度,制定相应的措施,严格监督和控制主要药物退换的科室以及药物退换的品种,最大程度上降低药物退换率。
英文摘要:
      Objective:To analyze the situation of the drug returns in the outpatient pharmacy in our hospital and to explore the management measures to reduce the rate of the drug returns so as to ensure safe and rational drug use of patients. Methods:All prescriptions in the outpatient pharmacy from August 2017 to August 2018 were collected and analyzed. The data of the drug returns and the reasons for the drug returns were processed by Excel software and the Pareto chart analysis was carried out. The cumulative frequency was calculated according to the statistical frequency of classification items. The statistical classification table of the drug returns was made and the Pareto chart was drawn. At the same time, the main, minor and general factors for the drug returns were analyzed. Results:A total of 1324,760 prescriptions were collected, of which 1,500 were the drug returns prescriptions, accounting for 1.13‰. The reasons for the drug returns were divided into three kinds of categories according to the accumulation frequency. The first category was the main factors, namely class A, whose cumulative frequency was generally between 30% and 80%.The second category was the minor factors, namely class B, whose cumulative frequency was generally between 80% and 90%. The third category was the general factors, namely class C, whose cumulative frequency was generally between 90% and 100%. The reasons for the drug returns were analyzed and the most common reason for the drug returns was due to the wrong drug information input by the staff. According to the statistics, there were 292 times of input mistakes in total, accounting for 19.47% of all reasons for the drug returns. Conclusion:It is necessary to establish various management systems for improving the prescriptions and come up with the improvement measures to strictly supervise and control the departments of the drug returns, and the types of drug return in order to reduce the rate of the drug returns at the most.
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