The Embase <scp>UK</scp> filter: validation of a geographic search filter to retrieve research about the <scp>UK</scp> from <scp>OVID</scp> Embase

Ayiku, Lynda; Levay, Paul; Hudson, Tom; Craven, Jenny; Finnegan, Amy; Adams, Rachel; Barrett, Elizabeth

doi:10.1111/hir.12252

Cited by 26 publications

(37 citation statements)

References 14 publications

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“…Location is also important in relation to Ayiku et al. 's () work in validating a geographic search filter to retrieve research about the UK from OVID Embase. Using the relative recall method, Ayiku et al.…”

Section: In This Issue…mentioning

confidence: 99%

“…Using the relative recall method, Ayiku et al. () developed a gold standard set of UK‐related references, which had previously informed the work of the National Institute for Health and Care Excellence. The validated UK search filter presented achieved 99.8% recall; 98.5% recall, 7.6% precision and a number‐needed‐to‐read of 13 in the associated case study.…”

Section: In This Issue…mentioning

confidence: 99%

“…Ayiku et al. () note the potential to save time and associated resource costs following the targeted retrieval their search filter facilitates.…”

Section: In This Issue…mentioning

confidence: 99%

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Grant¹

2019

Health Info Libraries J

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Health library and information workers no longer find themselves restricted to presenting at purely local or national health‐related library events, a diversity evidenced by the two conferences supported by CILIP's Health Libraries Group this month, June 2019. The Health Libraries Group is an official sponsor of #EBLIP10, the 10th international Evidence Based Library and Information Practice conference, which encourages us to think about the evidence we collect and use to inform practice. The Health Libraries Group also strengthens its links with EAHIL: The European Association of Health Information and Libraries by aligning the content of this year's Virtual Issue of the Health Information and Libraries Journal with EAHIL 2019s themes of evidence‐based practice, impact & assessment, and technology uptake, available at: https://bit.ly/2PAZw2X.

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Section: In This Issue…mentioning

confidence: 99%

Section: In This Issue…mentioning

confidence: 99%

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Conference season

Grant¹

2019

Health Info Libraries J

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“…The National Institute for Health and Care Excellence's (NICE) United Kingdom (UK) geographic search filters for MEDLINE and Embase (OVID) were developed and validated in 2016. 4,5 The MEDLINE filter achieved 99.5% recall and the Embase filter achieved 99.8% recall for references with UK identifiers in the searched fields during validation. 4,5 The NICE UK filters are available in Appendix S1.…”

Section: Introductionmentioning

confidence: 99%

“…The MEDLINE filter achieved 100% recall of 79 UK references from one of the reviews and the Embase filter achieved 98.5% recall (62 out of 63 UK references) from the other review. 4,5 The search strategies for each of the systematic reviews were recreated and run to assess their precision and NNR in retrieving the included UK references. The NICE UK filters were then applied to the search strategies to compare the results.…”

Section: Introductionmentioning

confidence: 99%

The NICE UK geographic search filters for MEDLINE and Embase (Ovid): Post‐development study to further evaluate precision and number‐needed‐to‐read when retrieving UK evidence

Ayiku

Levay

Hudson

et al. 2020

Research Synthesis Methods

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Background The National Institute for Health and Care Excellence's (NICE) United Kingdom (UK) geographic search filters for MEDLINE and Embase (OVID) retrieve evidence in literature searches for UK‐focused research topics with high recall. Their precision and number‐needed‐to‐read (NNR) was examined previously in case studies using a single review. This paper details a larger post‐development study that was conducted to test the NICE UK filters' precision and NNR more extensively. Methods The filters' recall of included UK references from 100 reviews was calculated. As reproducible search strategies were not available for every review, the MEDLINE filter's precision and NNR were calculated using strategies from 25 reviews. Strategies from nine reviews were used for the Embase filter. Results The MEDLINE filter achieved an average of 96.4% recall for the included UK references from the 100 reviews and the Embase filter achieved an average of 97.4% recall. Compared to not using a filter, the MEDLINE filter achieved an average of 98.9% recall for the 25 reviews. Precision was increased by an average of 7.8 times, reducing the NNR from 357 to 46. The Embase filter achieved an average of 97.1% recall for the nine reviews. Precision was increased by an average of 5.1 times, reducing the NNR from 746 to 146. Conclusion There is more evidence to demonstrate that the NICE UK filters retrieve the majority of UK evidence from MEDLINE and Embase while increasing precision and reducing NNR. The filters can save time spent on selecting evidence for UK‐focused research topics.

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The ScHARR LMIC filter: Adapting a low‐ and middle‐income countries geographic search filter to identify studies on preterm birth prevention and management

Sutton

Campbell

2022

Research Synthesis Methods

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Search filters are used to find evidence on specific subjects. Performance of filters can be varied and may need adapting to meet the needs of research topics. There are limited geographic search filters available, and only one pertaining to low‐ and middle‐income countries (LMICs). When searching for literature on preterm birth prevention and management in LMICs for a research project at the School of Health and Related Research (ScHARR), we made use of the Cochrane Effective Practice and Organisation of Care (EPOC) LMIC geographic search filter for the databases; Ovid MEDLINE, Ovid Embase, Cochrane Library. During screening following a broad scoping search in Ovid MEDLINE, it was found that the EPOC LMIC filter did not identify a relevant study. Adaptations were made to the LMIC geographic search filter to maximise retrieval and identify the missing study. Institution was included as a search field, and the search terms high burden or countdown countries were added. The filter was translated for the databases; Ovid Embase, Cochrane Library, Ovid PsycINFO, and CINAHL via EBSCO. The adapted ScHARR LMIC filter is a non‐validated 1st generation filter which increases the sensitivity of the EPOC LMIC search filter. Validating the filter would confirm its retrieval performance and benefit information professionals, researchers, and health professionals. We recommend that the ScHARR LMIC filter is used to improve sensitivity of the Cochrane EPOC LMIC filter and reduce the risk of missing relevant studies.

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The Embase UK filter: validation of a geographic search filter to retrieve research about the UK from OVID Embase

Cited by 26 publications

References 14 publications

Conference season

Conference season

The NICE UK geographic search filters for MEDLINE and Embase (Ovid): Post‐development study to further evaluate precision and number‐needed‐to‐read when retrieving UK evidence

The ScHARR LMIC filter: Adapting a low‐ and middle‐income countries geographic search filter to identify studies on preterm birth prevention and management

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