Evidence map›Paper›PMID 34858087›Full record

ArticleJournal of the Medical Library Association : JMLA2021

The NICE OECD countries' geographic search filters: Part 2-validation of the MEDLINE and Embase (Ovid) filters.

Lynda Ayiku, Thomas Hudson, Ceri Williams, Paul Levay, Catherine Jacob

Abstract read
In one paragraph

Article in Journal of the Medical Library Association : JMLA, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Removing records on animals and nonhumans in Ovid Embase: a comparison of 11 filters.Journal of the Medical Library Association : JMLA · 2026
    Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Lynda Ayikulynda.ayiku@nice.org.uk, Information Specialist, NICE Information Services team, National Institute for Health and Care Excellence, Manchester, UK.ORCID https://orcid.org/0000-0002-8055-3873
Thomas Hudsonthomas.hudson@nice.org.uk, Information Specialist, NICE Information Services team, National Institute for Health and Care Excellence, Manchester, UK.ORCID https://orcid.org/0000-0003-0748-3116
Ceri Williamsceri.williams@nice.org.uk, Information Specialist, NICE Information Services team, National Institute for Health and Care Excellence, Manchester, UK.
Paul Levaypaul.levay@nice.org.uk, Information Specialist, NICE Information Services team, National Institute for Health and Care Excellence, Manchester, UK.ORCID https://orcid.org/0000-0003-1784-3314
Catherine Jacobcatherine.jacob@nice.org.uk, Information Specialist, NICE Information Services team, National Institute for Health and Care Excellence, Manchester, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveWe previously developed draft MEDLINE and Embase (Ovid) geographic search filters for Organisation for Economic Co-operation and Development (OECD) countries to assess their feasibility for finding evidence about the countries. Here, we describe the validation of these search filters.

methodsWe identified OECD country references from thirty National Institute for Health and Care Excellence (NICE) guidelines to generate gold standard sets for MEDLINE (n=2,065) and Embase (n=2,023). We validated the filters by calculating their recall against these sets. We then applied the filters to existing search strategies for three OECD-focused NICE guideline reviews (NG103 on flu vaccination, NG140 on abortion care, and NG146 on workplace health) to calculate the filters' impact on the number needed to read (NNR) of the searches.

resultsThe filters both achieved 99.95% recall against the gold standard sets. Both filters achieved 100% recall for the three NICE guideline reviews. The MEDLINE filter reduced NNR from 256 to 232 for the NG103 review, from 38 to 27 for the NG140 review, and from 631 to 591 for the NG146 review. The Embase filter reduced NNR from 373 to 341 for the NG103 review, from 101 to 76 for the NG140 review, and from 989 to 925 for the NG146 review.

conclusionThe NICE OECD countries' search filters are the first validated filters for the countries. They can save time for research topics about OECD countries by finding the majority of evidence about OECD countries while reducing search result volumes in comparison to no filter use.

Indexed as

Organisation for Economic Co-Operation and DevelopmentDatabases, BibliographicFemaleHumansMEDLINEPregnancygeographyliterature searchingsearch filter

Identifiers

PMID34858087
PMCPMC8608218

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.