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Evaluation of an optimized context-aware clinical decision support system for drug-drug interaction screening

机译:评估药物 - 药物相互作用筛选的优化背景感知临床决策支持系统

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Objective: Evaluation of the effect of six optimization strategies in a clinical decision support system (CDSS) for drug-drug interaction (DDI) screening on alert burden and alert acceptance and description of clinical pharmacist intervention acceptance.Methods: Optimizations in the new CDSS were the customization of the knowledge base (with addition of 67 extra DDIs and changes in severity classification), a new alert design, required override reasons for the most serious alerts, the creation of DDI-specific screening intervals, patient-specific alerting, and a real-time follow-up system of all alerts by clinical pharmacists with interventions by telephone was introduced. The alert acceptance was evaluated both at the prescription level (i.e. prescription acceptance, was the DDI prescribed?) and at the administration level (i.e. administration acceptance, did the DDI actually take place?). Finally, the new follow-up system was evaluated by assessing the acceptance of clinical pharmacist's interventions.Results: In the pre-intervention period, 1087 alerts (92.0 % level 1 alerts) were triggered, accounting for 19 different DDIs. In the post-intervention period, 2630 alerts (38.4 % level 1 alerts) were triggered, representing 86 different DDIs. The relative risk forprescription acceptance in the post-intervention period compared to the preintervention period was 4.02 (95 % confidence interval (CI) 3.17-5.10; 25.5 % versus 6.3 %). The relative risk for administration acceptance was 1.16 (95 % CI 1.08-1.25; 54.4 % versus 46.7 %). Finally, 86.9 % of the clinical pharmacist interventions were accepted.Conclusion: Six concurrently implemented CDSS optimization strategies resulted in a high alert acceptance and clinical pharmacist intervention acceptance. Administration acceptance was remarkably higher than prescription acceptance.
机译:目的:评价六种优化策略在临床决策支持系统(CDSS)中的效果,用于对药物 - 药物相互作用(DDI)筛选出现警报负担和警报验收和临床药剂师干预验收的描述。方法:新CDS中的优化是知识库的自定义(通过增加67个额外的DDI和严重分类的变化),一个新的警报设计,所需的覆盖原因最严重的警报,创建DDI特定的筛选间隔,患者特定的警报和一个介绍了通过电话干预的临床药剂师所有警报的实时跟进系统。警报验收在处方级别(即处方接受,是DDI规定的DDI)和行政水平(即,行政审查,DDI实际发生了吗?)。最后,通过评估临床药剂师的干预措施的接受来评估新的后续系统。结果:在预干预期间,触发了1087个警报(92.0%的1级警报),占19个不同的DDIS。在后期后期,触发2630个警报(38.4%的1级警报),代表86个不同的DDI。与优先抗体期相比,干预后期的相对风险持续验收是4.02(95%置信区间(CI)3.17-5.10; 25.5%对6.3%)。管理验收的相对风险为1.16(95%CI 1.08-1.25; 54.4%对46.7%)。最后,接受了86.9%的临床药剂干预措施。结论:六同时实施的CDSSSS优化策略导致了高度警报验收和临床药剂师干预验收。管理接受比处方接受值得注目。

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