Systematic Review Automation Tools for End-to-End Query Formulation

2020 | Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '20)
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Systematic reviews are used widely in the biomedical and healthcare domains. Systematic reviews aim to provide a complete and exhaustive overview of the medical literature for a specific research question. Core to the construction of a systematic review is the search strategy. The main component of a search strategy is a complex Boolean query. Search strategies are typically methodically developed by expert searchers (e.g., librarians).

The aim of the search strategy is to retrieve relevant studies that will contribute to the outcomes of the systematic review. One problem that has arisen, however, is the enormous amount of medical literature that exists in the databases that the search strategies target. This vast number of studies means that the searches often suffer from biases (e.g., lack of expertise, overconfidence, limited knowledge of the domain) and for searches to be incomplete, or retrieve far too many studies (possibly as a result of the biases, but also due to the tools used to develop search strategies). Retrieving too many studies impacts the time and financial costs of the review, and retrieving too few studies may impact the outcomes of the review. Therefore, it is vital that search strategies be developed with as much support as necessary.

In this paper, we present a novel end-to-end set of advanced tools for information specialists. These tools are tightly integrated into an existing Open Source search strategy refining package (searchrefiner). These tools aim to address the problems associated with search strategy development by providing a complete framework from query development, to refinement, to documentation. The implementation of these tools also offers a glimpse at the ease at which related tools may be implemented within the searchrefiner ecosystem. More information about the tools including installation, documentation, screenshots, and a link to a demo is made available on the searchrefiner website: