Pharmacovigilance processes in low- and middle-income countries: moving from data collection to data analysis and interpretation.

IF 3.4 3区 医学 Q2 PHARMACOLOGY & PHARMACY
Therapeutic Advances in Drug Safety Pub Date : 2025-06-11 eCollection Date: 2025-01-01 DOI:10.1177/20420986241300006
Olga Menang, Peter van Eeuwijk, Karen Maigetter, Andy Stergachis, Christian Burri
{"title":"Pharmacovigilance processes in low- and middle-income countries: moving from data collection to data analysis and interpretation.","authors":"Olga Menang, Peter van Eeuwijk, Karen Maigetter, Andy Stergachis, Christian Burri","doi":"10.1177/20420986241300006","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>The analysis and interpretation of pharmacovigilance data is an essential component of the continuous benefit-risk assessment of authorised medicinal products. Effective pharmacovigilance data analysis starts with data collection and involves critical activities, such as signal detection, that enable the generation of new information on marketed products, and inform safety-related regulatory actions. This real-time pharmacovigilance data analysis, which requires efficient collaboration and exchange of information between the key pharmacovigilance stakeholders, represents a challenge for many low- and middle-income countries (LMIC).<b>Objectives::</b> To assess the capacity for analysis of pharmacovigilance data in LMIC and to identify mechanisms to strengthen data analysis, interpretation and evidence-based pharmacovigilance decision-making.</p><p><strong>Design: </strong>We used a convergent parallel mixed-methods study design consisting of qualitative and quantitative methods.</p><p><strong>Methods: </strong>Qualitative and quantitative methods consisted of semi-structured interviews and an online survey, respectively. Quantitative research was complemented by cross-sectional analyses of the number of adverse event reports from LMIC in VigiBase<sup>®</sup> from 2019 to 2023.</p><p><strong>Results: </strong>Nine key informants from eight countries were interviewed and 50 respondents from 34 countries completed the online survey. Four major themes emerged from the data and are proposed as transformative actions to strengthen pharmacovigilance data analysis and interpretation in LMIC: build on existing pharmacovigilance data analysis capacity rather than create new or parallel mechanisms; implement standardised procedures to enable efficient data analysis; augment the work of the safety committees by assigning pharmacovigilance staff to data analysis; and implement mechanisms that allow benefit-risk evaluation and decision-making.</p><p><strong>Conclusions: </strong>Findings from this research revealed that many LMIC have implemented procedures for reporting and collecting suspected adverse events, but a considerable proportion of the data collected is not analysed in-country due to a lack of requisite knowledge, processes and structures to support such analysis. Establishing the four essential elements proposed by this research will equip LMIC for efficient data analysis, thereby supporting consistent decision-making through pharmacovigilance.</p>","PeriodicalId":23012,"journal":{"name":"Therapeutic Advances in Drug Safety","volume":"16 ","pages":"20420986241300006"},"PeriodicalIF":3.4000,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12159475/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Therapeutic Advances in Drug Safety","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/20420986241300006","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"PHARMACOLOGY & PHARMACY","Score":null,"Total":0}
引用次数: 0

Abstract

Background: The analysis and interpretation of pharmacovigilance data is an essential component of the continuous benefit-risk assessment of authorised medicinal products. Effective pharmacovigilance data analysis starts with data collection and involves critical activities, such as signal detection, that enable the generation of new information on marketed products, and inform safety-related regulatory actions. This real-time pharmacovigilance data analysis, which requires efficient collaboration and exchange of information between the key pharmacovigilance stakeholders, represents a challenge for many low- and middle-income countries (LMIC).Objectives:: To assess the capacity for analysis of pharmacovigilance data in LMIC and to identify mechanisms to strengthen data analysis, interpretation and evidence-based pharmacovigilance decision-making.

Design: We used a convergent parallel mixed-methods study design consisting of qualitative and quantitative methods.

Methods: Qualitative and quantitative methods consisted of semi-structured interviews and an online survey, respectively. Quantitative research was complemented by cross-sectional analyses of the number of adverse event reports from LMIC in VigiBase® from 2019 to 2023.

Results: Nine key informants from eight countries were interviewed and 50 respondents from 34 countries completed the online survey. Four major themes emerged from the data and are proposed as transformative actions to strengthen pharmacovigilance data analysis and interpretation in LMIC: build on existing pharmacovigilance data analysis capacity rather than create new or parallel mechanisms; implement standardised procedures to enable efficient data analysis; augment the work of the safety committees by assigning pharmacovigilance staff to data analysis; and implement mechanisms that allow benefit-risk evaluation and decision-making.

Conclusions: Findings from this research revealed that many LMIC have implemented procedures for reporting and collecting suspected adverse events, but a considerable proportion of the data collected is not analysed in-country due to a lack of requisite knowledge, processes and structures to support such analysis. Establishing the four essential elements proposed by this research will equip LMIC for efficient data analysis, thereby supporting consistent decision-making through pharmacovigilance.

低收入和中等收入国家的药物警戒过程:从数据收集转向数据分析和解释。
背景:药物警戒数据的分析和解释是批准药品持续获益-风险评估的重要组成部分。有效的药物警戒数据分析始于数据收集,并涉及关键活动,如信号检测,从而能够生成有关已上市产品的新信息,并为与安全相关的监管行动提供信息。这种实时药物警戒数据分析需要关键药物警戒利益攸关方之间的有效协作和信息交流,这对许多低收入和中等收入国家构成了挑战。目标:评估低收入和中等收入国家药物警戒数据分析能力,确定加强数据分析、解释和循证药物警戒决策的机制。设计:我们采用融合平行混合方法研究设计,包括定性和定量方法。方法:定性方法采用半结构化访谈法,定量方法采用在线调查法。定量研究通过对2019年至2023年VigiBase®中LMIC不良事件报告数量的横断面分析进行补充。结果:来自8个国家的9名关键信息提供者接受了采访,来自34个国家的50名受访者完成了在线调查。从数据中产生了四个主要主题,并被提议作为变革性行动,以加强中低收入国家的药物警戒数据分析和解释:建立现有的药物警戒数据分析能力,而不是建立新的或平行的机制;实施标准化程序,以进行有效的数据分析;通过指派药物警戒工作人员进行数据分析,加强安全委员会的工作;实施利益风险评估和决策机制。结论:本研究的结果表明,许多低收入和中等收入国家已经实施了报告和收集疑似不良事件的程序,但由于缺乏支持此类分析的必要知识、流程和结构,收集的数据中有相当大一部分没有在国内进行分析。确立本研究提出的四个基本要素将使LMIC能够进行有效的数据分析,从而通过药物警戒支持一致的决策。
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
Therapeutic Advances in Drug Safety
Therapeutic Advances in Drug Safety Medicine-Pharmacology (medical)
CiteScore
6.70
自引率
4.50%
发文量
31
审稿时长
9 weeks
期刊介绍: Therapeutic Advances in Drug Safety delivers the highest quality peer-reviewed articles, reviews, and scholarly comment on pioneering efforts and innovative studies pertaining to the safe use of drugs in patients. The journal has a strong clinical and pharmacological focus and is aimed at clinicians and researchers in drug safety, providing a forum in print and online for publishing the highest quality articles in this area. The editors welcome articles of current interest on research across all areas of drug safety, including therapeutic drug monitoring, pharmacoepidemiology, adverse drug reactions, drug interactions, pharmacokinetics, pharmacovigilance, medication/prescribing errors, risk management, ethics and regulation.
×
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:604180095
Book学术官方微信