OvidSP Medline-to-PubMed search filter translation: a methodology for extending search filter range to include PubMed's unique content

Background Information specialists frequently translate search filters from one interface to another. Publications advise that translation can be complex and should be undertaken carefully. Objectives To investigate the issues arising when translating the Cochrane Embase RCT search filter from one interface (Ovid) to another (http://Embase.com). Methods We drafted a translation of the Cochrane Ovid RCT filter to run in http://Embase.com. We compared the line‐by‐line results of the Ovid filter with the results of the translation. We revised the filter. We identified differences between database versions including records with different publication years and subject headings. Some records were in Embase in one interface but not in the other. We encountered expected interface differences relating to proximity operators. We also encountered unexpected interface issues around truncation and the use of the original title or original abstract field. Discussion Filter conversion is challenging and time consuming revealing unexpected differences in interfaces and databases. Careful planning can pre‐empt some issues, but others may only emerge during testing. We identified interface anomalies that have led database publishers to review aspects of the way their interfaces work. Conclusions Translators should be vigilant for known and unknown differences in both interfaces and database versions.

Background: The evidence base developed by, and relevant to, primary health care (PHC) is rapidly increasing. With the wealth of literature available, searchers trying to find PHCspecific citations can feel overwhelmed. Objectives: Flinders Filters and the Primary Health Care Research & Information Service collaborated to develop a search filter enabling efficient and effective retrieval of relevant PHC literature. Methods: Stage 1 involved developing a PHC Search Filter in the OvidSP Medline platform using a rigorous experimental methodology. The search filter was then translated for webbased 'one click searching' in PubMed during Stage 2. Stage 3 involved planning and implementing a mixed-methods evaluation. Results: The search filter sensitivity was 77.0% with a post hoc relevance assessment of 78.3%. Four months after its launch a mixed-methods study evaluated the PHC Search Filter. With 90 respondents, analysis of data from the online survey demonstrated overarching benefits and a positive response to the tool, and directions for further refinement of the PHC Search Filter. Discussion: Designing the PHC Search Filter followed an established method that ensures the tool offers a validated search strategy. Evaluation results suggest that the PHC Search Filter is a useful tool that is easy to navigate. Challenges for the Filter relate to access to full text articles, while challenges for the evaluation relate to the small sample size. Conclusions: The PHC Search Filter reduces the burden associated with literature searching, increases the value of the results that are received, and provides a useful resource to improve the likelihood of incorporating relevant evidence into policy and practice. KeywordsPrimary health care, information storage and retrieval, information management, evidencebased practice Key messages Promoting access to quality, relevant literature may help to encourage uptake of evidence to inform research, practice and policy development  Search filters based on validated development methods increase the likelihood of quality retrievals of citations  The PHC Search Filter retrieves citations from the unindexed and indexed sets of the PubMed database providing searchers with the emerging and established literature  The PHC Search Filter is able to facilitate easier access to relevant primary health care literature for overwhelmed, time poor researchers, policy makers and practitioners  Topic searches that are combined with a search filter should be regularly updated to ensure relevance to searchers' needs/interests are incorporated

Using text mining to aid the development of database search strings for topics described by diverse terminology has potential benefits for systematic reviews; however, methods and tools for accomplishing this are poorly covered in the research methods literature. We briefly review the literature on applications of text mining for search term development for systematic reviewing. We found that the tools can be used in five overarching ways: improving the precision of searches; identifying search terms to improve search sensitivity; aiding the translation of search strategies across databases; searching and screening within an integrated system; and developing objectively-derived search strategies. Using a case study and selected examples, we then reflect on the utility of certain technologies (TF-IDF and Termine, term frequency, and clustering) in improving the precision and sensitivity of searches. Challenges in using these tools are discussed. The utility of these tools is influenced by the different capabilities of the tools, the way the tools are used, and the text that is analysed. Increased awareness of how the tools perform facilitates the further development of methods for their use in systematic reviews.