Medication Adherence and Stroke Prevention: What Real World Data Tells Us.

Q3 Medicine
Acta neurologica Taiwanica Pub Date : 2019-12-15
Cheng-Yang Hsieh
{"title":"Medication Adherence and Stroke Prevention: What Real World Data Tells Us.","authors":"Cheng-Yang Hsieh","doi":"","DOIUrl":null,"url":null,"abstract":"<p><p>Medication adherence, by definition,(2) is \"the extent to which a patient acts in accordance with the prescribed interval and dose of a dosing regimen.\" Poor medication adherence can interfere with the ability to treat many diseases, leading to greater complications and a lower quality of life.(3) In this issue of Acta Neurologica Taiwanica, Chen et al.(4) presented the inverse association between adherence of antithrombotic agents and poor outcomes after a first-ever ischemic stroke. The findings were consistent with Sung, et al.(5) that medication nonadherence are prevalent in young adults with a firstever stroke. The results by Chen, et al.(4) highlighted the importance of developing strategies to improve antithrombotic adherence. Besides, the risk-benefit profile of medication treatment must be considered and monitored for optimizing prescription in secondary stroke prevention. For those purposes, real-world data (RWD) derived from administrative claims database is becoming an efficient source of information.(6) The US Food and Drug Administration has also recognized the use of RWD to monitor post-marketing safety and adverse events and to make regulatory decisions of medicinal products.(7) Nonetheless, deriving RWD from administrative claims database should be held to an even higher scientific standard because of the greater potential for bias.(6) For example, the ascertainment of cases, coding for comorbidities, and handling of unmeasured confounders (e.g. disease severity) should follow those previously wellvalidated methods.(8-10) Besides, we should note that the adherence measured using claims data is the proportion of days covered with filled prescription. It might not be exactly equal to the real medication adherence behavior of the patients, as mentioned by Chen, et al.(4) Linking administrative claims database with other validated clinical databases (e.g. stroke registry) may improve the validity of a RWD study.(11) In the era of data science and artificial intelligence, we neurologists should endeavor to make the best use of all available electronic healthcare datasets, creating more useful RWD for our patients with strokes, as well as other neurological diseases.</p>","PeriodicalId":7102,"journal":{"name":"Acta neurologica Taiwanica","volume":"28(4) ","pages":"86-87"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Acta neurologica Taiwanica","FirstCategoryId":"1085","ListUrlMain":"","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 0

Abstract

Medication adherence, by definition,(2) is "the extent to which a patient acts in accordance with the prescribed interval and dose of a dosing regimen." Poor medication adherence can interfere with the ability to treat many diseases, leading to greater complications and a lower quality of life.(3) In this issue of Acta Neurologica Taiwanica, Chen et al.(4) presented the inverse association between adherence of antithrombotic agents and poor outcomes after a first-ever ischemic stroke. The findings were consistent with Sung, et al.(5) that medication nonadherence are prevalent in young adults with a firstever stroke. The results by Chen, et al.(4) highlighted the importance of developing strategies to improve antithrombotic adherence. Besides, the risk-benefit profile of medication treatment must be considered and monitored for optimizing prescription in secondary stroke prevention. For those purposes, real-world data (RWD) derived from administrative claims database is becoming an efficient source of information.(6) The US Food and Drug Administration has also recognized the use of RWD to monitor post-marketing safety and adverse events and to make regulatory decisions of medicinal products.(7) Nonetheless, deriving RWD from administrative claims database should be held to an even higher scientific standard because of the greater potential for bias.(6) For example, the ascertainment of cases, coding for comorbidities, and handling of unmeasured confounders (e.g. disease severity) should follow those previously wellvalidated methods.(8-10) Besides, we should note that the adherence measured using claims data is the proportion of days covered with filled prescription. It might not be exactly equal to the real medication adherence behavior of the patients, as mentioned by Chen, et al.(4) Linking administrative claims database with other validated clinical databases (e.g. stroke registry) may improve the validity of a RWD study.(11) In the era of data science and artificial intelligence, we neurologists should endeavor to make the best use of all available electronic healthcare datasets, creating more useful RWD for our patients with strokes, as well as other neurological diseases.

药物依从性和中风预防:真实世界数据告诉我们的。
根据定义,服药依从性(2)是“患者按照规定的间隔时间和剂量服药的程度”。不良的药物依从性会干扰治疗许多疾病的能力,导致更大的并发症和更低的生活质量。(3)在这一期的《台湾神经学报》上,Chen等人(4)提出了首次缺血性卒中后抗栓药物依从性与不良预后之间的负相关。这一发现与Sung等人(5)的观点一致,即首次中风的年轻人普遍不遵医嘱服药。Chen等人(4)的研究结果强调了制定提高抗血栓依从性策略的重要性。此外,必须考虑和监测药物治疗的风险-收益概况,以优化二级卒中预防处方。出于这些目的,来自行政声明数据库的真实世界数据(RWD)正在成为一种有效的信息来源。(6)美国食品和药物管理局也承认使用RWD来监测上市后安全性和不良事件,并制定药品的监管决策。(7)尽管如此,从行政声明数据库中提取RWD应该保持更高的科学标准,因为存在更大的偏见可能性。(6)例如,病例的确定、合并症的编码和未测量混杂因素(如疾病严重程度)的处理应遵循先前经过充分验证的方法。(8-10)此外,我们应该注意到,使用索赔数据测量的依从性是使用处方的天数比例。(4)将行政索赔数据库与其他经过验证的临床数据库(如卒中登记)联系起来,可能会提高RWD研究的有效性。(11)在数据科学和人工智能时代,我们神经学家应该努力充分利用所有可用的电子医疗数据集,为我们的中风患者创建更有用的RWD。还有其他神经系统疾病。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Acta neurologica Taiwanica
Acta neurologica Taiwanica Medicine-Neurology (clinical)
CiteScore
1.30
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信