Searching Embase and MEDLINE by using only major descriptors or title and abstract fields: a prospective exploratory study

Abstract

Background

Researchers performing systematic reviews (SRs) must carefully consider the relevance of thousands of citations retrieved from bibliographic database searches, the majority of which will be excluded later on close inspection. Well-developed bibliographic searches are generally created with thesaurus or index terms in combination with keywords found in the title and/or abstract fields of citation records. Records in the bibliographic database Embase contain many more thesaurus terms than MEDLINE. Here, we aim to examine how limiting searches to major thesaurus terms (in MEDLINE called focus terms) in Embase and MEDLINE as well as limiting to words in the title and abstract fields of those databases affects the overall recall of SR searches.

Methods

To examine the impact of using search techniques aimed at higher precision, we analyzed previously completed SRs and focused our original searches to major thesaurus terms or terms in title and/or abstract only in Embase.com or in Embase.com and MEDLINE (Ovid) combined. We examined the total number of search results in both Embase and MEDLINE and checked whether included references were retrieved by these more focused approaches.

Results

For 73 SRs, we limited Embase searches to major terms only while keeping the search in MEDLINE and other databases such as Web of Science as they were. The overall search yield (or total number of search results) was reduced by 8%. Six reviews (9%) lost more than 5% of the relevant references. Limiting Embase and MEDLINE to major thesaurus terms, the number of references was 13% lower. For 15% of the reviews, the loss of relevant references was more than 5%. Searching Embase for title and abstract caused a loss of more than 5% in 16 reviews (22%), while limiting Embase and MEDLINE that way this happened in 24 reviews (33%).

Conclusions

Of the four search options, two options substantially reduced the overall search yield. However, this also resulted in a greater chance of losing relevant references, even though many references were still found in other databases such as Web of Science.