Development and validation of search filters to identify articles on deprescribing in Medline and Embase

Morel, Thomas; Nguyen-Soenen, Jérôme; Thompson, Wade; Fournier, Jean‐Pascal

doi:10.1186/s12874-022-01515-x

Cited by 9 publications

(8 citation statements)

References 23 publications

(30 reference statements)

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“…Then, we studied the objectively developed deprescribing filters for MEDLINE and Embase 4 and the USDeN deprescribing filter for MEDLINE 5 (Table S1). One author (TM) implemented the deprescribing filters in each search strategy.…”

Section: Methodsmentioning

confidence: 99%

“…We recently developed two deprescribing search filters with maximised sensitivity in a hand search reference set of relevant deprescribing articles using objective methodology 4 . We validated a sensitivity of 92% (95% CI: 83–97) for MEDLINE (using the PubMed interface) and 91% (95% CI: 82–96) for Embase (using the Embase.com interface), respectively 4 . The efficiency gained by using these objectively developed deprescribing filters in systematic reviews search strategies remains unknown.…”

Section: Introductionmentioning

confidence: 99%

“…4 We validated a sensitivity of 92% (95% CI: 83-97) for MEDLINE (using the PubMed interface) and 91% (95% CI: 82-96) for Embase (using the Embase.com interface), respectively. 4 The efficiency gained by using these objectively developed deprescribing filters in systematic reviews search strategies remains unknown. Simultaneously, The US Deprescribing Network (USDeN) developed a deprescribing search strategy that included a deprescribing search filter for MEDLINE using the PubMed interface, but its performance has not been evaluated yet.…”

Section: Introductionmentioning

confidence: 99%

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Use of deprescribing search filters in systematic review search strategies: A case study

Morel

Heinrich

Zerah

et al. 2023

Basic Clin Pharma Tox

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Two deprescribing search filters for MEDLINE and one deprescribing search filter for Embase have been recently developed, including objectively developed search filters. The objective of this case study was to implement these three deprescribing search filters in systematic review (SR) search strategies and to assess their effect on performances. SR that independently developed original search strategies (OSS) were selected. The deprescribing filters were implemented in each OSS, generating two implemented search strategies (ISS1 and ISS2) in MEDLINE and one ISS (ISS3) in Embase. OSS were re‐run on the same date as ISS. The performances of ISS and OSS were calculated and compared. Two SR were included (SR1 and SR2). For MEDLINE, SR1 included 12 articles. The sensitivity was 50% for OSS, 58% for ISS1 and 42% for ISS2. SR2 included four articles. The sensitivity of OSS, ISS 1 and 2 was 25%. For Embase, SR1 included 12 articles. The sensitivity was 33% for OSS and 58% for ISS3. SR2 included four articles. None of the four included articles were retrieved with OSS or ISS3. While sensitivity of OSS was moderate, the objectively developed deprescribing filters maintained or slightly improved this sensitivity when implementing.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Use of deprescribing search filters in systematic review search strategies: A case study

Morel

Heinrich

Zerah

et al. 2023

Basic Clin Pharma Tox

Self Cite

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show abstract

“…We recently developed two deprescribing search filters with maximized sensitivity for MEDLINE (using PubMed interface) and for Embase (using Embase.com interface) with a sensitivity of 92% (95% CI: 83-97) and 91% (95% CI: 82-96) respectively 4 . The efficiency gained by using these maximized sensitivity filters in systematic reviews search strategies remains unknown.…”

Section: Introductionmentioning

confidence: 99%

Use of deprescribing search filters in systematic review search strategies: a case study

Morel¹,

Heinrich

Zerah

et al. 2023

Preprint

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Deprescribing search filters aiming at maximizing sensitivity for MEDLINE and for Embase were recently developed. Simultaneously, The US Deprescribing Network (USden) developed a deprescribing search strategy that included a deprescribing search filter for MEDLINE. The aim of this case study was to implement these deprescribing search filters in original search strategies from deprescribing related systematic reviews (SRs) and to calculate their performances. Two deprescribing SRs were included. Authors were asked to repeat the selection process described in SRs original methods. Performances of search strategies implemented with deprescribing search filters (ISS) were calculated and compared to original search strategies (OSS). In MEDLINE, sensitivity for SR 1 was 50% for OSS (Precision: 2.8%), 58% for ISS with maximised sensitivity filter (Precision: 1.7%) and 42% for ISS with USden filter (Precision: 5.1%). Sensitivity for SR 2 was 25% for all search strategies (Precision: 0.1%, 0.2% and 1,2% respectively). In Embase, sensitivity for SR 1 was 33% (Precision: 4,1%) for OSS and 58% for ISS (Precision 2.1%). No articles were included through Embase search strategies for SR 2. Using maximized sensitivity deprescribing filters may increase the exhaustivity of deprescribing SRs. Precision offered by the USDeN deprescribing filter is a convenient alternative for non-systematic reviews.

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“…These filters tend to maximize the efficiency of the literature search and provide a standardized approach to search for defined methods or topics (Lefebvre et al, 2017). Search filters to identify deprescribing articles have recently been developed (Morel et al, 2022). However, to the best of our knowledge, there are no such validated search filters for discontinuation.…”

Section: Introductionmentioning

confidence: 99%

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

Morel,

Nguyen‐Soenen,

Thompson

et al. 2023

Health Info Libraries J

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BackgroundMedication 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.ObjectivesTo develop and validate search filters to retrieve medication discontinuation articles in Medline and Embase.MethodsWe 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).ResultsWe 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).ConclusionsWe 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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Development and validation of search filters to identify articles on deprescribing in Medline and Embase

Cited by 9 publications

References 23 publications

Use of deprescribing search filters in systematic review search strategies: A case study

Use of deprescribing search filters in systematic review search strategies: A case study

Use of deprescribing search filters in systematic review search strategies: a case study

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

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