In an era of explosive growth in biomedical evidence, improving efficiency and precision of systematic review searches is critical. Text-mining tools (TMT) are a potentially powerful resource to improve and streamline search strategy development.
To compare the costs and benefits of searches with and without TMT. Specific questions include: (1) Do TMT decrease the time spent developing strategies?; (2) Does use of TMT improve search performance?; (3) How does the performance of TMT for developing strategies compare for simple or complex review topics?
General Proposed Approach
In this prospective study, we plan to include ten systematic review projects, classified by topic as simple or complex. Each project's information specialist will use conventional methods to create the search strategy, and a paired information specialist will independently create a MEDLINE search strategy for the same review project using text-mining tools. All text-mining searches will be created using freely available TMT to ensure our research methods may be replicated across diverse settings and our findings may be relevant to all review producers. We will collect search results from both MEDLINE strategies, code and remove duplicates, and send the citations to the review team for screening. When the draft report is submitted, we will use its final list of included studies to calculate the sensitivity, specificity, precision, and Number Needed to Read (NNR) for both MEDLINE strategies. We will also track the time spent by information specialists to conduct each task in their search development process. Simple and complex topics will be analyzed separately to allow comparison.
Improvements to searching techniques positively affect the quality and efficiency of systematic review production, thereby providing better and more timely products on which consumers can base their healthcare decisions.