TY - JOUR T1 - Automatic extraction of quantitative data from ClinicalTrials.gov to conduct meta-analyses JF - BMJ Evidence-Based Medicine JO - BMJ EBM SP - 113 LP - 114 DO - 10.1136/bmjebm-2019-111206 VL - 25 IS - 3 AU - Thomas R Fanshawe AU - Rafael Perera Y1 - 2020/06/01 UR - http://ebm.bmj.com/content/25/3/113.abstract N2 - Increasing the speed for completing a systematic review is needed to keep up to date with the literature. Could automatic data extraction from ClinicalTrials.gov provide an important step in speeding up the process of evidence synthesis? How can we conduct systematic reviews more quickly? An assessment of information in the PROSPERO registry (International prospective register of systematic reviews) to 2014, Borah et al 1 estimated the average time to carry out a systematic review to be over a year. This time frame has remained broadly unchanged in comparison with an estimate published 18 years earlier.2 Because of the speed with which some clinical disciplines generate new evidence, there is a danger that new systematic reviews become out of date within the time taken for them to be completed and published, and as a consequence their findings appear too slowly to influence practice.Lifting data from electronic articles or data repositories automatically using computer software, rather than extracting it painstakingly by hand, has been gradually growing in popularity among systematic reviewers.3 The move to automation seems appealing and … ER -