Department of Medical Informatics, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands; Methodology, Amsterdam Public Health, Amsterdam, Netherlands.
Department of Medical Informatics, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands; Digital Health, Amsterdam Public Health, Amsterdam, Netherlands.
Lancet. 2024 Feb 3;403(10425):439-449. doi: 10.1016/S0140-6736(23)02465-0. Epub 2024 Jan 20.
Drug-drug interactions (DDIs) can harm patients admitted to the intensive care unit (ICU). Yet, clinical decision support systems (CDSSs) aimed at helping physicians prevent DDIs are plagued by low-yield alerts, causing alert fatigue and compromising patient safety. The aim of this multicentre study was to evaluate the effect of tailoring potential DDI alerts to the ICU setting on the frequency of administered high-risk drug combinations.
We implemented a cluster randomised stepped-wedge trial in nine ICUs in the Netherlands. Five ICUs already used potential DDI alerts. Patients aged 18 years or older admitted to the ICU with at least two drugs administered were included. Our intervention was an adapted CDSS, only providing alerts for potential DDIs considered as high risk. The intervention was delivered at the ICU level and targeted physicians. We hypothesised that showing only relevant alerts would improve CDSS effectiveness and lead to a decreased number of administered high-risk drug combinations. The order in which the intervention was implemented in the ICUs was randomised by an independent researcher. The primary outcome was the number of administered high-risk drug combinations per 1000 drug administrations per patient and was assessed in all included patients. This trial was registered in the Netherlands Trial Register (identifier NL6762) on Nov 26, 2018, and is now closed.
In total, 10 423 patients admitted to the ICU between Sept 1, 2018, and Sept 1, 2019, were assessed and 9887 patients were included. The mean number of administered high-risk drug combinations per 1000 drug administrations per patient was 26·2 (SD 53·4) in the intervention group (n=5534), compared with 35·6 (65·0) in the control group (n=4353). Tailoring potential DDI alerts to the ICU led to a 12% decrease (95% CI 5-18%; p=0·0008) in the number of administered high-risk drug combinations per 1000 drug administrations per patient, after adjusting for clustering and prognostic factors.
This cluster randomised stepped-wedge trial showed that tailoring potential DDI alerts to the ICU setting significantly reduced the number of administered high-risk drug combinations. Our list of high-risk drug combinations can be used in other ICUs, and our strategy of tailoring alerts based on clinical relevance could be applied to other clinical settings.
ZonMw.
药物-药物相互作用(DDI)会对入住重症监护病房(ICU)的患者造成伤害。然而,旨在帮助医生预防 DDI 的临床决策支持系统(CDSS)因低产量警报而受到困扰,导致警报疲劳并危及患者安全。本多中心研究的目的是评估针对 ICU 环境调整潜在 DDI 警报对给予高危药物组合的频率的影响。
我们在荷兰的 9 家 ICU 中实施了一项集群随机分步式试验。5 家 ICU 已经使用了潜在的 DDI 警报。纳入年龄在 18 岁或以上、入住 ICU 且至少给予两种药物的患者。我们的干预措施是一种经过调整的 CDSS,仅为被认为是高危的潜在 DDI 提供警报。该干预措施在 ICU 层面上进行,并针对医生。我们假设仅显示相关警报将提高 CDSS 的有效性,并减少给予的高危药物组合数量。干预在 ICU 中的实施顺序由一名独立研究员随机分配。主要结局是每位患者每 1000 次药物给药中给予的高危药物组合数量,并对所有纳入的患者进行评估。该试验于 2018 年 11 月 26 日在荷兰试验注册处(标识符 NL6762)注册,现已关闭。
共有 10423 名患者于 2018 年 9 月 1 日至 2019 年 9 月 1 日入住 ICU,其中 9887 名患者被纳入研究。在干预组(n=5534),每位患者每 1000 次药物给药中给予的高危药物组合数量的平均值为 26.2(SD 53.4),而在对照组(n=4353)中为 35.6(65.0)。针对 ICU 调整潜在 DDI 警报导致每位患者每 1000 次药物给药中给予的高危药物组合数量减少 12%(95%CI 5-18%;p=0.0008),调整聚类和预后因素后。
这项集群随机分步式试验表明,针对 ICU 环境调整潜在的 DDI 警报显著减少了给予的高危药物组合数量。我们的高危药物组合列表可用于其他 ICU,我们基于临床相关性调整警报的策略可应用于其他临床环境。
ZonMw。