Background: An analysis of searches conducted for the NICE guideline surveillance programme indicated that only about 3% of studies are included following sifting. Currently, population only searches are used with the aim of retrieving all relevant articles. This can result in a high number of results with low precision. Although machine-learning techniques may offer a mechanism for improving precision of surveillance searches in the future, they are not commonplace currently. An alternative approach involves utilising search techniques to increase the precision of the searches used for surveillance, without losing the recall of the search.

Objectives: To conduct a retrospective analysis comparing the impact of a modified search approach on the surveillance decision.

Methods: Five guidelines were selected for inclusion in this retrospective analysis using the following criteria:
• Surveillance decision was to update the guideline
• Large database of results from the search strategy (>3000 studies)
• Low number of included studies summarised (