Medication Clusters at Hospital Discharge and Risk of Adverse Drug Events at 30-days Post-Discharge: A Population-based Cohort Study of Older Adults

Author:

Weir Daniala L.,Ma Xiaomeng,McCarthy Lisa,Tang Terence,Lapointe-Shaw Lauren,Wodchis Walter P.,Fernandes Olavo,McDonald Emily G.

Abstract

ABSTRACTBackground:Certain combinations of medications can be harmful and may lead to serious drug-drug interactions. Identifying potentially problematic medication clusters could help guide prescribing decisions in hospital.Objectives:To characterize medication prescribing patterns at hospital discharge and determine which medication clusters are associated with an increased risk of adverse drug events (ADEs) in the 30-days post hospital discharge.Methods:All residents of the province of Ontario in Canada aged 66 years or older admitted to hospital between March 2016-February 2017 were included. Identification of medication prescribing clusters at hospital discharge was conducted using latent class analysis. Cluster identification was based on medications dispensed 30-days post-hospitalization. Multivariable logistic regression was used to assess the potential association between membership to a particular medication cluster and ADEs post-discharge, while also evaluating other patient characteristics.Results:188,354 patients were included in the study cohort. Median age (IQR) was 77 (71-84) and patients had a median (IQR) of 9 (6-13) medications dispensed in the year prior to admission. The study population consisted of 6 separate clusters of dispensing patterns post discharge: Cardiovascular (14%), respiratory (26%), complex care needs (12%), cardiovascular and metabolic (15%), infection (10%) and surgical (24%). Overall, 12,680 (7%) patients had an ADE in the 30-days following discharge. After considering other patient characteristics, those in the respiratory cluster had the highest risk of ADEs (aOR: 1.12, 95% CI: 1.08-1.17) compared to all the other clusters, while those in the neurocognitive & complex care needs cluster had the lowest risk (aOR:0.82, 95% CI: 0.77-0.87).Conclusion:This study suggests that ADEs post hospital discharge are linked to identifiable clusters of medications, in addition to non-modifiable patient characteristics, such as age and certain comorbidities. This information may help clinicians and researchers better understand what patient populations and which types of interventions may benefit patients, to reduce their risk of experiencing an ADE.KEY POINTSThis study suggests that ADEs post hospital discharge are linked to identifiable clusters of medications, in addition to non-modifiable patient characteristics, such as age and certain comorbidities. This information may help clinicians and researchers better understand what patient populations and which types of interventions may benefit patients, to reduce their risk of experiencing an ADE.PLAIN LANGUAGE SUMMARYCertain combinations of medications prescribed to patients when they are being discharged from hospital can increase the risk of adverse events after hospital discharge.

Publisher

Cold Spring Harbor Laboratory

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3