Development and validation of search filters to retrieve medication discontinuation articles in Medline and Embase

IF 2.2 4区医学 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE

Health Information and Libraries Journal Pub Date : 2023-11-27 DOI:10.1111/hir.12516

Thomas Morel MD, MSc, Jérôme Nguyen-Soenen MD, MSc, Wade Thompson PharmD, PhD, Jean-Pascal Fournier MD, PhD

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引用次数: 0

Abstract

Background

Medication discontinuation studies explore the outcomes of stopping a medication compared to continuing it. Comprehensively identifying medication discontinuation articles in bibliographic databases remains challenging due to variability in terminology.

Objectives

To develop and validate search filters to retrieve medication discontinuation articles in Medline and Embase.

Methods

We identified medication discontinuation articles in a convenience sample of systematic reviews. We used primary articles to create two reference sets for Medline and Embase, respectively. The reference sets were equally divided by randomization in development sets and validation sets. Terms relevant for discontinuation were identified by term frequency analysis in development sets and combined to develop two search filters that maximized relative recalls. The filters were validated against validation sets. Relative recalls were calculated with their 95% confidences intervals (95% CI).

Results

We included 316 articles for Medline and 407 articles for Embase, from 15 systematic reviews. The Medline optimized search filter combined 7 terms. The Embase optimized search filter combined 8 terms. The relative recalls were respectively 92% (95% CI: 87–96) and 91% (95% CI: 86–94).

Conclusions

We developed two search filters for retrieving medication discontinuation articles in Medline and Embase. Further research is needed to estimate precision and specificity of the filters.

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在Medline和Embase中检索药物停用文章的搜索过滤器的开发和验证。

背景:药物停药研究探讨停药与继续用药的结果。由于术语的变化，在书目数据库中全面识别药物停药文章仍然具有挑战性。目的:开发并验证在Medline和Embase中检索停药文章的搜索过滤器。方法:我们在系统评价的方便样本中确定药物停药文章。我们使用主要文章分别为Medline和Embase创建了两个参考集。参考集被随机分为开发集和验证集。通过开发集中的术语频率分析确定与终止相关的术语，并结合开发两个搜索过滤器，最大限度地提高相对召回率。根据验证集对过滤器进行了验证。相对召回用其95%置信区间(95% CI)计算。结果:我们从15篇系统综述中纳入Medline的316篇文章和Embase的407篇文章。Medline优化的搜索过滤器包含7个术语。Embase优化的搜索过滤器组合了8个术语。相对召回率分别为92% (95% CI: 87-96)和91% (95% CI: 86-94)。结论:我们在Medline和Embase中开发了两种用于检索停药文章的搜索过滤器。需要进一步的研究来估计滤波器的精度和特异性。

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来源期刊

Health Information and Libraries Journal INFORMATION SCIENCE & LIBRARY SCIENCE-

CiteScore

6.70

自引率

10.50%

发文量

期刊介绍： Health Information and Libraries Journal (HILJ) provides practitioners, researchers, and students in library and health professions an international and interdisciplinary forum. Its objectives are to encourage discussion and to disseminate developments at the frontiers of information management and libraries. A major focus is communicating practices that are evidence based both in managing information and in supporting health care. The Journal encompasses: - Identifying health information needs and uses - Managing programmes and services in the changing health environment - Information technology and applications in health - Educating and training health information professionals - Outreach to health user groups