HILJ Club: This edition of HILJ club has been prepared by:  Tom Roper, Clinical Librarian, General Surgery and Digestive Diseases, Urology, Acute and Emergency Medicine, Critical Care, Trauma and Orthopaedics, Brighton and Sussex NHS Library and Knowledge Service  @tomroper

HILJ Club is a simple way for people to do CPD around with articles published in Health Information and Libraries Journal (HILJ).  HILJ is the journal of the Health Libraries Group of CILIP and all members have access.  Working with Wiley, the article under discussion is made freely available for a month around the discussion.

We select an article for discussion from each issue of HILJ. The organising group (Alan Fricker, Catherine McLaren, Morag Clarkson, Lisa Burscheidt, Tom Roper) have picked articles thus far but in future people would be welcome to volunteer to host.  We now have a permanent home on this WordPress site. Generally the host will offer some questions as prompts and then the discussion can go where interest takes it.

The paper for discussion is Ayiku L, Levay P, Hudson T, Craven J, Finnegan A, Adams R, Barrett E. The Embase UK filter: validation of a geographic search filter to retrieve research about the UK from OVID Embase. Health Info Libr J. 2019 Jun;36(2):121-133. doi:10.1111/hir.12252.


The authors developed a validated geographic search filter to retrieve research about the United Kingdom (UK) from OVID Embase. It was created to be used alongside their previously published OVID MEDLINE UK filter in systematic literature searches for context‐sensitive topics.


To develop a validated geographic search filter to retrieve research about the UK from OVID Embase.


The Embase UK filter was translated from the MEDLINE UK filter. A gold standard set of references was generated using the relative recall method. The set contained references to publications about the UK that had informed National Institute for Health and Care Excellence (NICE) guidance and it was used to validate the filter. Recall, precision and number‐needed‐to‐read (NNR) were calculated using a case study.


The validated Embase UK filter demonstrated 99.8% recall against the references with UK identifiers in the gold standard set. In the case study, the Embase UK filter demonstrated 98.5% recall, 7.6% precision and a NNR of 13.


The Embase UK filter can be used alongside the MEDLINE UK filter. The filters have the potential to save time and associated resource costs when they are used for context‐sensitive topics that require research about UK settings.

Questions for discussion

What? What do you think of this article? What do you think of the research methods? Is there something else that you would have liked to have seen included in the article?

So what? Would you use this filter in practice? Would you use the same methods to develop filters for other searches?

Now what?  Will you change your practice as a result of reading this article? If so, how? If not, why not?


What? This is a carefully conducted piece of work, but it’s a little hard to understand the methods for search filter development without referring to the authors’ previous work on a MEDLINE filter. This filter is a translation of the MEDLINE one but importantly, is independently validated.

The authors outline the need for UK specific filters and explain the development of the EMBASE one, the creation of a Gold Standard set against which to test the filter, and the calculation of recall, precision and NNR (Number Needed to Read). It is interesting that 38 of the 599 papers in the Gold standard set were not retrievable as UK papers in EMBASE, as they contained no UK identifiers in searchable fields. Does this matter?

The authors found that the both the Gold Standard and the filter missed two papers (one from each) which had a UK identifier field in the record. In both cases this was due to an Embase indexing error: one paper had been given a United States geographic term, although it was set in Manchester, the other had been assigned the terms Bangladesh and Central America, as it  discussed populations that, generations ago, originated from those parts of the world. The authors warn that it is impossible to know how many other Embase records are similarly affected

So what? I have not yet used this filter in any of my searches, though it might be more useful for those conducting searches for public health departments.  I consider it to be well constructed and reliable, so would certainly experiment with  it under the right circumstances

Now what? It would be helpful if this filter, and the MEDLINE one, could be made available as a filter option in the various search interfaces we use. The incorrect indexing is alarming, and I wonder if the quality of database indexing needs attention, particularly as database providers seem to be automating their processes to greater or lesser extents.

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