...
首页> 外文期刊>Journal of infection and public health. >Effect of a computer network-based feedback program on antibiotic prescription rates of primary care physicians: A cluster randomized crossover-controlled trial
【24h】

Effect of a computer network-based feedback program on antibiotic prescription rates of primary care physicians: A cluster randomized crossover-controlled trial

机译:基于计算机网络的反馈计划对初级保健医生抗生素处方率的影响:一组随机交叉控制试验

获取原文
           

摘要

Objective Antibiotic overuse is one of the major prescription problems in rural China and a major risk factor for antibiotic resistance. Low antibiotic prescription rates can effectively reduce the risk of antibiotic resistance. We hypothesized that under a paperless, computer-based feedback system the rates of antibiotic prescriptions among primary care physicians can be reduced. Methods A cluster randomized crossover open controlled trial was conducted in 31 hospitals. These hospitals were randomly allocated to two groups to receive the intervention for three months followed by no intervention for three months in a random sequence. The feedback intervention information, which displayed the physicians’ antibiotic prescription rates and ranking, was updated every 10 days. The primary outcome was the 10-day antibiotic prescription rate of the physicians. Results There were 82 physicians in group 1 (intervention first followed by control) and 81 in group 2 (control first followed by intervention). Baseline comparison showed no significant difference in antibiotic prescription rate between the two groups (30.8% vs 35.2%, P -value?=?0.07). At the crossover point, the relative reduction in antibiotic prescription rate was significantly higher among physicians in the intervention group than in the control group (33.1% vs 20.3%, P -value??0.001). After a further 3 months, the rate of decline in antibiotic prescriptions was also significantly greater in the intervention group compared to the control group (14.2% vs 4.6%, P -value??0.001). The characteristics of physicians did not significantly determine the change in rate of antibiotic prescriptions. Conclusion A computer network-based feedback intervention can significantly reduce the antibiotic prescription rates of primary care outpatient physicians and continuously affected their prescription behavior for up to six months.
机译:客观的抗生素过度使用是中国农村主要处方问题和抗生素抗性的主要危险因素之一。低抗生素处方率可以有效降低抗生素抗性的风险。我们假设在无纸化的计算机的反馈系统下,可以减少初级保健医师之间的抗生素处方的抗生素处方率。方法在31家医院进行集群随机交叉开放式对照试验。这些医院随机分配给两组,以获得三个月的干预,然后在随机序列中没有干预三个月。显示医生抗生素处方率和排名的反馈干预信息每10天更新一次。主要结果是医生的10天抗生素处方率。结果第1组中有82名医生(首先进行干预后,第2组中的81名(第一次控制后,干预后)。基线比较显示两组之间的抗生素处方率没有显着差异(30.8%与35.2%,P-value?= 0.07)。在交叉点,干预组的医生在抗对照组中的相对降低显着高于对照组(33.1%Vs 20.3%,P-value?<0.001)。经过3个月后,与对照组相比,干预组的抗生素处方的下降率也明显更大(14.2%Vs 4.6%,P-value?<0.001)。医生的特征没有显着确定抗生素处方率的变化。结论基于计算机网络的反馈干预可以显着降低初级保健门诊医生的抗生素处方率,并不断影响其处方行为长达六个月。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号