Effectiveness of computerised alerts to reduce drug-drug interactions (DDIs) and DDI-related harm in hospitalised patients: a quasi-experimental controlled pre-post study.

IF 5.6 1区 医学 Q1 HEALTH CARE SCIENCES & SERVICES
Melissa Therese Baysari, Sarah Nicole Hilmer, Richard O Day, Bethany Annemarie Van Dort, Wu Yi Zheng, Renee Quirk, Danielle Deidun, Maria Moran, Kristian Stanceski, Nanda Aryal, Ahmed Abo Salem, Lauren Farrow, Jannah Baker, Andrew Hargreaves, James Grant, Paula Doherty, Karma Zarif Sourial Mekhail, Johanna I Westbrook, Ling Li
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引用次数: 0

Abstract

Background: Drug-drug interaction (DDI) alerts target the co-prescription of two potentially interacting medications and are a frequent feature of electronic medical records (EMRs). There have been few controlled studies evaluating the effectiveness of DDI alerts. This study aimed to determine the impact of DDI alerts on rates of DDIs and on associated patient harms.

Methods: Quasi-experimental controlled pre-post study in five Australian hospitals. Three hospitals acted as control hospitals (EMR with no DDI alerts) and two as intervention (EMR with DDI alerts). Only DDI alerts at the highest severity level (defined as 'major contraindicated') were switched on at intervention hospitals. These alerts were not tailored to clinical context (ie, patient, drug). A total of 2078 patients were randomly selected from all patients (adult and paediatric) admitted to hospitals 6 months before and 6 months after EMR implementation. A retrospective chart review was performed by study pharmacists. The primary outcome was the proportion of admissions with a clinically relevant DDI. Secondary outcomes included the proportions of admissions with a potential DDI and with DDI-related harm.

Results: Potential DDIs were identified in the majority of admissions (n=1574, 74.7%) and clinically relevant DDIs identified in half (n=1026, 48.7%). DDI alerts were associated with a reduction in the proportion of admissions with potential DDIs (adjusted OR (AOR)=0.38 (0.19, 0.78)) but no change in clinically relevant DDIs (AOR=1.12 (0.68, 1.84)) or in DDI-related harm (AOR=2.42 (0.47,12.31)). 199 DDIs (76 at control and 123 at intervention hospitals) for 35 patient admissions were associated with patient harm, and 2 patients experienced severe DDI-related harm pre-EMR implementation.

Discussion: Implementation of DDI alerts, without tailoring alerts to clinical context, is unlikely to reduce patient harms from DDIs. Organisations should reconsider implementation of DDI alerts in EMRs where significant tailoring of alerts is not possible. Future research should focus on identifying safe, efficient and cost-effective ways of refining DDI alerts, so expected clinical benefits are achieved, and negative consequences of excessive alerting are minimised.

减少住院病人药物-药物相互作用(ddi)和ddi相关伤害的计算机警报的有效性:一项准实验控制的前后研究
背景:药物-药物相互作用(DDI)警报针对两种可能相互作用的药物的共同处方,是电子医疗记录(emr)的常见特征。很少有对照研究评估DDI警报的有效性。本研究旨在确定DDI警报对DDI发生率和相关患者危害的影响。方法:在澳大利亚五家医院进行准实验对照前后研究。三家医院作为对照医院(无DDI警报的EMR),两家作为干预医院(有DDI警报的EMR)。在干预医院,只有最高严重级别(定义为“主要禁忌症”)的DDI警报才被打开。这些警报不是针对临床情况(即患者、药物)量身定制的。从实施电子病历前6个月和实施电子病历后6个月入院的所有患者(成人和儿科)中随机选择了2078名患者。由研究药师进行回顾性图表回顾。主要结局是与临床相关的DDI的入院比例。次要结局包括有潜在DDI和DDI相关危害的入院比例。结果:大多数入院患者(n=1574, 74.7%)发现了潜在的ddi,半数患者(n=1026, 48.7%)发现了临床相关的ddi。DDI警报与潜在DDI入院比例的降低相关(调整后的OR (AOR)=0.38(0.19, 0.78)),但与临床相关的DDI (AOR=1.12(0.68, 1.84))或与DDI相关的危害(AOR=2.42(0.47,12.31))没有变化。35例入院患者中199例ddi(对照组76例,干预医院123例)与患者伤害相关,2例患者在实施emr之前经历了严重的ddi相关伤害。讨论:实施DDI警报,而不根据临床情况调整警报,不太可能减少DDI对患者的伤害。组织应该重新考虑在不可能大量定制警报的emr中实施DDI警报。未来的研究应侧重于确定安全、有效和具有成本效益的改进DDI警报的方法,从而实现预期的临床效益,并将过度警报的负面后果降至最低。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
BMJ Quality & Safety
BMJ Quality & Safety HEALTH CARE SCIENCES & SERVICES-
CiteScore
9.80
自引率
7.40%
发文量
104
审稿时长
4-8 weeks
期刊介绍: BMJ Quality & Safety (previously Quality & Safety in Health Care) is an international peer review publication providing research, opinions, debates and reviews for academics, clinicians and healthcare managers focused on the quality and safety of health care and the science of improvement. The journal receives approximately 1000 manuscripts a year and has an acceptance rate for original research of 12%. Time from submission to first decision averages 22 days and accepted articles are typically published online within 20 days. Its current impact factor is 3.281.
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