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使用临床决策支持软件和扩展的操作相互作用分类系统(苏黎世相互作用系统)评估 484 例神经科住院患者的药物相互作用和剂量。

Evaluation of drug interactions and dosing in 484 neurological inpatients using clinical decision support software and an extended operational interaction classification system (Zurich Interaction System).

机构信息

Department of Clinical Pharmacology and Toxicology, University Hospital Zurich, Zurich, Switzerland.

出版信息

Pharmacoepidemiol Drug Saf. 2011 Sep;20(9):930-8. doi: 10.1002/pds.2197. Epub 2011 Jul 20.

Abstract

PURPOSE

The current study aimed at identifying and quantifying critical drug interactions in neurological inpatients using clinical decision support software (CDSS). Reclassification of interactions with a focus on clinical management aimed to support the development of CDSS with higher efficacy to reduce overalerting and improve medication safety in clinical practice.

METHODS

We conducted a cross-sectional study in consecutive patients admitted to the neurology ward of a tertiary care hospital. We developed a customized interface for mass analysis with the CDSS MediQ, which we used for automated retrospective identification of drug interactions during the first day of hospitalization. Interactions were reclassified according to the Zurich Interaction System (ZHIAS), which incorporates the Operational Classification of Drug Interactions (ORCA). Dose adjustments for renal impairment were also evaluated.

RESULTS

In 484 patients with 2812 prescriptions, MediQ generated 8 "high danger," 518 "average danger," and 1233 "low danger" interaction alerts. According to ZHIAS, 6 alerts involved contraindicated and 33 alerts involved provisionally contraindicated combinations, and 327 alerts involved a conditional and 1393 alerts involved a minimal risk of adverse outcomes. Thirty-five patients (6.2%) had at least one combination that was at least provisionally contraindicated. ZHIAS also provides categorical information on expected adverse outcomes and management recommendations, which are presented in detail. We identified 13 prescriptions without recommended dose adjustment for impaired renal function.

CONCLUSIONS

MediQ detected a large number of drug interactions with variable clinical relevance in neurological inpatients. ZHIAS supports the selection of those interactions that require active management, and the effects of its implementation into CDSS on medication safety should be evaluated in future prospective studies.

摘要

目的

本研究旨在使用临床决策支持软件(CDSS)识别和量化神经内科住院患者的关键药物相互作用,并对其进行分类,重点关注临床管理,以支持开发更有效的 CDSS,减少过度警示,并提高临床实践中的药物安全性。

方法

我们在一家三级护理医院的神经内科连续收治的患者中进行了一项横断面研究。我们为 MediQ CDSS 开发了一个定制的批量分析接口,用于在住院的第一天自动识别药物相互作用。根据包含操作分类药物相互作用(ORCA)的苏黎世药物相互作用系统(ZHIAS)对相互作用进行重新分类,并评估了因肾功能损害而进行的剂量调整。

结果

在 484 名患者的 2812 份处方中,MediQ 生成了 8 个“高危险”、518 个“中危险”和 1233 个“低危险”的相互作用警报。根据 ZHIAS,有 6 个警报涉及禁忌组合,33 个警报涉及临时禁忌组合,327 个警报涉及有条件的风险,1393 个警报涉及最小的不良后果风险。35 名患者(6.2%)至少有一种组合至少是临时禁忌的。ZHIAS 还提供了关于预期不良后果和管理建议的分类信息,这些信息将详细呈现。我们发现 13 份处方没有建议调整肾功能损害患者的剂量。

结论

MediQ 在神经内科住院患者中检测到大量具有不同临床相关性的药物相互作用。ZHIAS 支持选择需要积极管理的相互作用,未来应在前瞻性研究中评估其在 CDSS 中的实施对药物安全性的影响。

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