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评价一种优化的上下文感知临床决策支持系统在药物-药物相互作用筛选中的应用。

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

机构信息

Research Group Clinical Pharmacology & Clinical Pharmacy (KFAR), Faculty of Medicine and Pharmacy, Vrije Universiteit Brussel, Brussels, Laarbeeklaan 103, 1090 Brussels, Belgium.

Department of Medical Informatics, UZ Brussel, Laarbeeklaan 101, 1090 Brussels, Belgium.

出版信息

Int J Med Inform. 2021 Apr;148:104393. doi: 10.1016/j.ijmedinf.2021.104393. Epub 2021 Jan 15.

Abstract

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 pre-intervention 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.

摘要

目的

评估临床决策支持系统(CDSS)中 6 种药物相互作用(DDI)筛选优化策略对报警负担和报警接受的影响,并描述临床药师干预接受情况。

方法

新 CDSS 的优化包括知识库的定制(增加 67 种额外的 DDI 并改变严重程度分类)、新的报警设计、最严重报警需要覆盖原因、DDI 特定的筛选间隔、患者特定的报警、以及临床药师实时跟进所有报警并通过电话进行干预。在处方级别(即是否开出 DDI?)和给药级别(即是否实际给药?)评估报警接受情况。最后,通过评估临床药师干预的接受情况来评估新的随访系统。

结果

在干预前阶段,触发了 1087 次报警(92.0%为 1 级报警),涉及 19 种不同的 DDI。在干预后阶段,触发了 2630 次报警(38.4%为 1 级报警),涉及 86 种不同的 DDI。与干预前相比,干预后处方接受的相对风险为 4.02(95%置信区间 3.17-5.10;25.5%对 6.3%)。给药接受的相对风险为 1.16(95%置信区间 1.08-1.25;54.4%对 46.7%)。最终,86.9%的临床药师干预被接受。

结论

同时实施的 6 种 CDSS 优化策略导致高报警接受率和临床药师干预接受率。给药接受率明显高于处方接受率。

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