School of Pharmacy, College of Medical & Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK.
School of Pharmacy, Zarqa University, PO Box 132222, Zarqa, 13132, Jordan.
Int J Clin Pharm. 2020 Apr;42(2):765-771. doi: 10.1007/s11096-020-01022-3. Epub 2020 Apr 11.
Background Antimicrobial resistance is correlated with the inappropriate use of antibiotics. Computerised decision support systems may help practitioners to make evidence-based decisions when prescribing antibiotics. Objective This study aimed to evaluate the impact of computerized decision support systems on the volume of antibiotics used. Setting A very large 1200-bed teaching hospital in Birmingham, England. Main outcome measure The primary outcome measure was the defined daily doses/1000 occupied bed-days. Method A retrospective longitudinal study was conducted to examine the impact of computerised decision support systems on the volume of antibiotic use. The study compared two periods: one with computerised decision support systems, which lasted for 2 years versus one without which lasted for 2 years after the withdrawal of computerised decision support systems. Antibiotic use data from June 2012 to June 2016 were analysed (comprising 2 years with computerised decision support systems immediately followed by 2 years where computerised decision support systems had been withdrawn). Regression analysis was applied to assess the change in antibiotic consumption through the period of the study. Result From June 2012 to June 2016, total antibiotic usage increased by 13.1% from 1436 to 1625 defined daily doses/1000 bed-days: this trend of increased antibiotic prescribing was more pronounced following the withdrawal of structured prescribing (computerised decision support systems). There was a difference of means of - 110.14 defined daily doses/1000 bed days of the total usage of antibiotics in the period with and without structured prescribing, and this was statistically significant (p = 0.026). From June 2012 to June 2016, the dominant antibiotic class used was penicillins. The trends for the total consumption of all antibiotics demonstrated an increase of use for all antibiotic classes except for tetracyclines, quinolones, and anti-mycobacterial drugs, whereas aminoglycoside usage remained stable. Conclusion The implementation of computerised decision support systems appears to influence the use of antibiotics by reducing their consumption. Further research is required to determine the specific features of computerised decision support systems, which influence increased higher adoption and uptake of this technology.
抗菌药物的不合理使用与抗菌药物耐药性相关。计算机化决策支持系统可以帮助临床医生在开具抗生素时做出基于证据的决策。目的：本研究旨在评估计算机化决策支持系统对抗生素使用量的影响。地点：英国伯明翰一家拥有 1200 张床位的大型教学医院。主要结局指标：主要结局指标为限定日剂量/1000 占用床日数。方法：采用回顾性纵向研究方法，考察计算机化决策支持系统对抗生素使用量的影响。本研究比较了两个时期：一个时期是使用计算机化决策支持系统的 2 年，另一个时期是停用计算机化决策支持系统后的 2 年。分析了 2012 年 6 月至 2016 年 6 月的抗生素使用数据（包括使用计算机化决策支持系统的 2 年，以及停用计算机化决策支持系统后的 2 年）。应用回归分析评估研究期间抗生素使用量的变化。结果：2012 年 6 月至 2016 年 6 月，总抗生素用量从 1436 增至 1625 定义日剂量/1000 床日，增长了 13.1%：在停用结构化处方（计算机化决策支持系统）后，抗生素处方开具呈上升趋势。有统计学意义（p=0.026）。在有和没有结构化处方的时期，抗生素总使用量的均值相差-110.14 定义日剂量/1000 床日。2012 年 6 月至 2016 年 6 月，使用最多的抗生素类别是青霉素。所有抗生素总用量的变化趋势表明，除了四环素类、喹诺酮类和抗分枝杆菌药物外，所有抗生素类别的使用量都有所增加，而氨基糖苷类药物的使用量保持稳定。结论：计算机化决策支持系统的实施似乎通过减少抗生素的使用来影响抗生素的使用。需要进一步研究确定影响该技术更高采用率和接受率的计算机化决策支持系统的具体特征。
