Improving the specificity of drug-drug interaction alerts: Can it be done?
Improving the specificity of drug-drug interaction alerts: Can it be done?
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DOI：
10.1093/ajhp/zxac045
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发表时间：
2022-02-08
影响因子：
2.7
通讯作者：
Malone, Daniel
中科院分区：
文献类型：
--
作者：
Reese, Thomas;Wright, Adam;Malone, Daniel
目的：不准确和非特异性的药物警报会导致高覆盖率、警报疲劳，并最终对患者造成伤害。药物相互作用（DDI）警报通常无法解释可能降低风险的因素;此外，触发警报的药物通常不一致地分组为值集。为了提高DDI警报的特异性，本研究的目的是（1）强调触发DDI警报的药物值集的不一致性，以及（2）证明可用于修改DDI伤害风险的因素分类方法。方法这是一项概念验证研究，重点是15个著名的DDI。使用3个药物相互作用参考，我们提取了2个药物值集和每个DDI的任何可用的订单和患者相关因素。Fleiss' kappa用于测量参考文献之间值集的一致性。将风险修正因素分类为顺序参数（例如，给药途径和剂量）或患者特征（例如，合并症和实验室结果）。结果17个值集（56%）的一致性不显著。其余13个数值集之间的一致性平均中等。在15个DDI中的14个（93%）中确定了33个可以降低风险的因素。大多数风险修正因子（67%）被归类为顺序参数。结论本研究证明了提高触发DDI警报的药物值集一致性的重要性，以及如何通过从药物参考中获得的风险修正因子提高警报的特异性和有用性。可能难以操作某些因素以减少不必要的警报;但是，可以使用这些因素通过提供上下文信息来支持决策。
Purpose Inaccurate and nonspecific medication alerts contribute to high override rates, alert fatigue, and ultimately patient harm. Drug-drug interaction (DDI) alerts often fail to account for factors that could reduce risk; further, drugs that trigger alerts are often inconsistently grouped into value sets. Toward improving the specificity of DDI alerts, the objectives of this study were to (1) highlight the inconsistency of drug value sets for triggering DDI alerts and (2) demonstrate a method of classifying factors that can be used to modify the risk of harm from a DDI. Methods This was a proof-of-concept study focused on 15 well-known DDIs. Using 3 drug interaction references, we extracted 2 drug value sets and any available order- and patient-related factors for each DDI. Fleiss' kappa was used to measure the consistency of value sets among references. Risk-modifying factors were classified as order parameters (eg, route and dose) or patient characteristics (eg, comorbidities and laboratory results). Results Seventeen value sets (56%) had nonsignificant agreement. Agreement among the remaining 13 value sets was on average moderate. Thirty-three factors that could reduce risk in 14 of 15 DDIs (93%) were identified. Most risk-modifying factors (67%) were classified as order parameters. Conclusion This study demonstrates the importance of increasing the consistency of drug value sets that trigger DDI alerts and how alert specificity and usefulness can be improved with risk-modifying factors obtained from drug references. It may be difficult to operationalize certain factors to reduce unnecessary alerts; however, factors can be used to support decisions by providing contextual information.