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General medicine
Automatic extraction of quantitative data from to conduct meta-analyses
  1. Thomas R Fanshawe,
  2. Rafael Perera
  1. Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
  1. Correspondence to Dr Rafael Perera, NDPCHS, University of Oxford Department of Primary Care Health Sciences, Oxford OX2 6GG, UK; rafael.perera{at}

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Increasing the speed for completing a systematic review is needed to keep up to date with the literature. Could automatic data extraction from 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speed with which some clinical disciplines generate new evidence, there is a danger that new systematic reviews become out of date within the time taken for them to be completed and published, and as a consequence their findings appear too slowly to influence practice.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 …

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  • Contributors RP and TRF identified the paper of interest. TRF wrote the first draft. RP added the verdict. Both authors edited and approved the final version.

  • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

  • Competing interests Both TRF and RP are authors of several Systematic Reviews and have received research funding from the UK NIHR, the MRC, the BHF and Wellcome to carry out some of these reviews. RP has received grants from the UK NIHR, Cancer Research UK, BHF, NIHR School of Primary Care Research and support from the NIHR Oxford Biomedical Research Centre and the NIHR Community Healthcare MedTech and In Vitro Diagnostics Co-operative.

  • Provenance and peer review Not commissioned; internally peer reviewed.

  • Patient consent for publication Not required.