Evidence synthesis software

BMJ Evid Based Med. 2018 Aug;23(4):140-141. doi: 10.1136/bmjebm-2018-110962. Epub 2018 Jun 7.

Abstract

It can be challenging to decide which evidence synthesis software to choose when doing a systematic review. This article discusses some of the important questions to consider in relation to the chosen method and synthesis approach. Software can support researchers in a range of ways. Here, a range of review conditions and software solutions. For example, facilitating contemporaneous collaboration across time and geographical space; in-built bias assessment tools; and line-by-line coding for qualitative textual analysis. EPPI-Reviewer is a review software for research synthesis managed by the EPPI-centre, UCL Institute of Education. EPPI-Reviewer has text mining automation technologies. Version 5 supports data sharing and re-use across the systematic review community. Open source software will soon be released. EPPI-Centre will continue to offer the software as a cloud-based service. The software is offered via a subscription with a one-month (extendible) trial available and volume discounts for 'site licences'. It is free to use for Cochrane and Campbell reviews. The next EPPI-Reviewer version is being built in collaboration with National Institute for Health and Care Excellence using 'surveillance' of newly published research to support 'living' iterative reviews. This is achieved using a combination of machine learning and traditional information retrieval technologies to identify the type of research each new publication describes and determine its relevance for a particular review, domain or guideline. While the amount of available knowledge and research is constantly increasing, the ways in which software can support the focus and relevance of data identification are also developing fast. Software advances are maximising the opportunities for the production of relevant and timely reviews.

Keywords: information management; world wide web technology.

MeSH terms

  • Data Mining
  • Humans
  • Information Storage and Retrieval / methods*
  • Machine Learning
  • Software*
  • Systematic Reviews as Topic*