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首页> 外文期刊>JMIR Medical Informatics >Towards The Automated, Empirical Filtering of Drug-Drug Interaction Alerts in Clinical Decision Support Systems: Historical Cohort Study of Vitamin K Antagonists
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Towards The Automated, Empirical Filtering of Drug-Drug Interaction Alerts in Clinical Decision Support Systems: Historical Cohort Study of Vitamin K Antagonists

机译：朝向临床决策支持系统中的药物 - 药物相互作用警报的自动化，经验滤波：维生素K拮抗剂的历史队列研究

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Background Drug-drug interactions (DDIs) involving vitamin K antagonists (VKAs) constitute an important cause of in-hospital morbidity and mortality. However, the list of potential DDIs is long; the implementation of all these interactions in a clinical decision support system (CDSS) results in over-alerting and alert fatigue, limiting the benefits provided by the CDSS. Objective To estimate the probability of occurrence of international normalized ratio (INR) changes for each DDI rule, via the reuse of electronic health records. Methods An 8-year, exhaustive, population-based, historical cohort study including a French community hospital, a group of Danish community hospitals, and a Bulgarian hospital. The study database included 156,893 stays. After filtering against two criteria (at least one VKA administration and at least one INR laboratory result), the final analysis covered 4047 stays. Exposure to any of the 145 drugs known to interact with VKA was tracked and analyzed if at least 3 patients were concerned. The main outcomes are VKA potentiation (defined as an INR≥5) and VKA inhibition (defined as an INR≤1.5). Groups were compared using the Fisher exact test and logistic regression, and the results were expressed as an odds ratio (95% confidence limits). Results The drugs known to interact with VKAs either did not have a statistically significant association regarding the outcome (47 drug administrations and 14 discontinuations) or were associated with significant reduction in risk of its occurrence (odds ratio1 for 18 administrations and 21 discontinuations). Conclusions The probabilities of outcomes obtained were not those expected on the basis of our current body of pharmacological knowledge. The results do not cast doubt on our current pharmacological knowledge per se but do challenge the commonly accepted idea whereby this knowledge alone should be used to define when a DDI alert should be displayed. Real-life probabilities should also be considered during the filtration of DDI alerts by CDSSs, as proposed in SPC-CDSS (statistically prioritized and contextualized CDSS). However, these probabilities may differ from one hospital to another and so should probably be calculated locally.
机译：背景技术涉及维生素K拮抗剂（VKAS）的药物 - 药物相互作用（DDIS）构成了院内发病率和死亡率的重要原因。但是，潜在的DDIS列表很长;在临床决策支持系统（CDS）中的所有这些交互的实施导致过度警报和警报疲劳，限制了CDSS提供的福利。目的估计通过电子健康记录的重用，估计每个DDI规则的国际规范化比率（INR）变化的可能性。方法为8年，详尽的人口，历史队列研究，包括法国社区医院，一群丹麦社区医院和保加利亚医院。该研究数据库包括156,893次住宿。在过滤两种标准（至少一个VKA管理和至少一个INR实验室结果）后，最终分析覆盖了4047份。在至少3名患者担心，跟踪并分析已知的145种已知与VKA与VKA相互作用的药物中的任何一种。主要结果是VKA升级（定义为INR≥5）和VKA抑制（定义为INR≤1.5）。使用Fisher精确测试和逻辑回归进行比较组，结果表达为赔率比（95％的置信限制）。结果已知与VKA相互作用的药物无论是否存在关于结果（47药物和14个中断）的统计学上显着的关联，也没有与其发生风险的显着降低有关（18个助药和21个助手的差异率＆ 1次） 。结论所获得的结果的概率并不是在我们目前的药理学知识的基础上预期的概率。结果不会对我们目前的药理学知识进行疑问，但是确实挑战了普遍接受的想法，在那里，仅应该将这些知识用于何时显示DDI警报时。在SPC-CDS（统计上优先和上下文CDSS）中提出的CDSSS，也应考虑在DDI警报期间考虑现实寿命概率。但是，这些概率可能与一个医院不同于另一种医院，所以应该在本地计算。

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