A Comprehensive Search Filter to Identify Randomized Controlled Trials

OBJECTIVES: The synthesis of evidence in healthcare relies on the efficient identification of research evidence, particularly evidence from randomized controlled trials (RCTs). The purpose of this study was to create and evaluate a comprehensive and sensitive search filter for identifying RCTs when running systematic literature reviews (SLRs) in Medline and Embase databases by OVID platform.

METHODS: The filter was formulated through a comprehensive analysis and synthesis of keywords derived from search filters for RCTs sourced from six reputable entities. These sources include the National Institute for Health and Care Excellence, Canadian Agency for Drugs and Technologies in Health, Cochrane Scottish Intercollegiate Guidelines Network, British Medical Journal Knowledge Center, OVID expert searches, and the search strategy endorsed by Cochrane Information Specialist. Subsequently, the efficacy of the filters was assessed using ten Cochrane SLRs as a benchmark.

RESULTS: The coverage of available data was ranging from 83% to 100%. In seven out of ten tested SLRs, all relevant RCTs were identified. In the remaining cases, studies were omitted mainly due to lack of keywords like ‘’randomization’’ in abstracts. In eight cases, the use of our filter resulted in a reduction of the number of records to be analyzed (from 7% to 77%), in comparison to Cochrane SLRs.

CONCLUSIONS: The formulation of a sensitive and specific search strategy stands as a pivotal stage in the process of evidence synthesis. The incorporation of filters pertinent to study design not only holds the potential to substantially mitigate resource utilization and costs but also supports attaining specificity through careful exclusions. Nevertheless, it should be noted that the effectiveness of database retrieval is impacted by both: the quality of indexing and the quality of abstracts.