Identifying medication harm in hospitalised patients: a bimodal, targeted approach.
作者信息
Falconer Nazanin, Spinewine Anne, Doogue Matthew P, Barras Michael
机构信息
Department of Pharmacy, Ground floor, Princess Alexandra Hospital, Woolloongabba, QLD. Centre for Health Services Research, Faculty of Medicine and School of Pharmacy, The University of Queensland, Brisbane, QLD, 4102, Australia.
Université catholique de Louvain, Louvain Drug Research Institute, Brussels, Belgium.
出版信息
Ther Adv Drug Saf. 2020 Nov 25;11:2042098620975516. doi: 10.1177/2042098620975516. eCollection 2020.
Abstract
摘要
相似文献
1
Identifying medication harm in hospitalised patients: a bimodal, targeted approach.识别住院患者的用药危害：一种双峰、靶向方法。
Ther Adv Drug Saf. 2020 Nov 25;11:2042098620975516. doi: 10.1177/2042098620975516. eCollection 2020.
2
Development, testing, and findings of a pediatric-focused trigger tool to identify medication-related harm in US children's hospitals.一种以儿科为重点的触发工具在美国儿童医院中识别与药物相关伤害的开发、测试及结果
Pediatrics. 2008 Apr;121(4):e927-35. doi: 10.1542/peds.2007-1779.
3
Utility of a trigger tool (TRIGGER-CHRON) to detect adverse events associated with high-alert medications in patients with multimorbidity.一种触发工具（TRIGGER-CHRON）在患有多种疾病的患者中检测与高警示药物相关的不良事件的效用。
Eur J Hosp Pharm. 2021 Nov;28(Suppl 2):e41-e46. doi: 10.1136/ejhpharm-2019-002126. Epub 2020 May 8.
4
Performance of the adverse drug event trigger tool and the global trigger tool for identifying adverse drug events: experience in a Belgian hospital.不良药物事件触发工具和全球触发工具在识别不良药物事件中的性能：比利时一家医院的经验。
Ann Pharmacother. 2013 Nov;47(11):1414-9. doi: 10.1177/1060028013500939.
5
Adverse drug event detection in pediatric oncology and hematology patients: using medication triggers to identify patient harm in a specialized pediatric patient population.儿科肿瘤学和血液学患者的药物不良事件检测：利用用药触发因素识别特殊儿科患者群体中的患者伤害。
J Pediatr. 2014 Sep;165(3):447-52.e4. doi: 10.1016/j.jpeds.2014.03.033. Epub 2014 Apr 25.
6
Multicenter Test of an Emergency Department Trigger Tool for Detecting Adverse Events.用于检测不良事件的急诊科触发工具的多中心测试
J Patient Saf. 2021 Dec 1;17(8):e843-e849. doi: 10.1097/PTS.0000000000000516.
7
Comparison of traditional trigger tool to data warehouse based screening for identifying hospital adverse events.传统触发工具与数据仓库筛查在识别医院不良事件中的比较。
BMJ Qual Saf. 2013 Feb;22(2):130-8. doi: 10.1136/bmjqs-2012-001102. Epub 2012 Oct 4.
8
Prevalence and severity of patient harm in a sample of UK-hospitalised children detected by the Paediatric Trigger Tool.通过儿科触发工具检测的英国住院儿童样本中患者伤害的发生率和严重程度。
BMJ Open. 2014 Jul 3;4(7):e005066. doi: 10.1136/bmjopen-2014-005066.
9
Development of a trigger tool to identify adverse events and harm in Emergency Medical Services.开发一种触发工具以识别紧急医疗服务中的不良事件和伤害。
Emerg Med J. 2017 Jun;34(6):391-397. doi: 10.1136/emermed-2016-205746. Epub 2017 Feb 2.
10
A targeted method for standardized assessment of adverse drug events in surgical patients.一种针对手术患者药物不良事件的标准化评估的靶向方法。
J Eval Clin Pract. 2013 Dec;19(6):1073-82. doi: 10.1111/jep.12033. Epub 2013 Apr 18.
引用本文的文献
1
Scoping Review of Studies Evaluating Frailty and Its Association with Medication Harm.评价衰弱及其与药物伤害相关性的研究的范围综述。
Drugs Aging. 2022 May;39(5):333-353. doi: 10.1007/s40266-022-00940-3. Epub 2022 May 22.
本文引用的文献
1
Development and validation of the Adverse Inpatient Medication Event model (AIME).不良住院药物事件模型（AIME）的开发与验证。
Br J Clin Pharmacol. 2021 Mar;87(3):1512-1524. doi: 10.1111/bcp.14560. Epub 2020 Nov 5.
2
A Clinician's Guide to Artificial Intelligence: How to Critically Appraise Machine Learning Studies.《临床医师人工智能指南：如何批判性地评价机器学习研究》
Transl Vis Sci Technol. 2020 Feb 12;9(2):7. doi: 10.1167/tvst.9.2.7.
3
Utility of a trigger tool (TRIGGER-CHRON) to detect adverse events associated with high-alert medications in patients with multimorbidity.一种触发工具（TRIGGER-CHRON）在患有多种疾病的患者中检测与高警示药物相关的不良事件的效用。
Eur J Hosp Pharm. 2021 Nov;28(Suppl 2):e41-e46. doi: 10.1136/ejhpharm-2019-002126. Epub 2020 May 8.
4
Medication-related harm in older adults following hospital discharge: development and validation of a prediction tool.老年人出院后与药物相关的伤害：预测工具的开发和验证。
BMJ Qual Saf. 2020 Feb;29(2):142-153. doi: 10.1136/bmjqs-2019-009587. Epub 2019 Sep 16.
5
Machine learning in clinical practice: prospects and pitfalls.临床实践中的机器学习：前景与陷阱。
Med J Aust. 2019 Sep;211(5):203-205.e1. doi: 10.5694/mja2.50294. Epub 2019 Aug 6.
6
The potential for artificial intelligence in healthcare.人工智能在医疗保健领域的潜力。
Future Healthc J. 2019 Jun;6(2):94-98. doi: 10.7861/futurehosp.6-2-94.
7
Development and performance evaluation of the Medicines Optimisation Assessment Tool (MOAT): a prognostic model to target hospital pharmacists' input to prevent medication-related problems.药物优化评估工具（MOAT）的开发和性能评估：一种预测模型，旨在针对医院药师的投入，以预防与药物相关的问题。
BMJ Qual Saf. 2019 Aug;28(8):645-656. doi: 10.1136/bmjqs-2018-008335. Epub 2019 Mar 7.
8
A Machine-Learning Algorithm to Optimise Automated Adverse Drug Reaction Detection from Clinical Coding.一种机器学习算法，用于优化从临床编码中自动检测药物不良反应。
Drug Saf. 2019 Jun;42(6):721-725. doi: 10.1007/s40264-018-00794-y.
9
Hope, hype and harms of Big Data.大数据的希望、炒作与危害。
Intern Med J. 2019 Jan;49(1):126-129. doi: 10.1111/imj.14172.
10
A classification framework for exploiting sparse multi-variate temporal features with application to adverse drug event detection in medical records.利用稀疏多元时间特征的分类框架及其在医疗记录中药物不良事件检测的应用。
BMC Med Inform Decis Mak. 2019 Jan 10;19(1):7. doi: 10.1186/s12911-018-0717-4.
Zotero 插件