Background: One of the three principle aims of the Guidelines International Network (G-I-N) is to assist in “reducing duplication of effort and improving the efficiency and effectiveness of evidence-based guideline development, adaptation, dissemination and implementation (http://www.g-i-n.net/about-g-i-n/introduction). This is also an important issue for triallists, journal editors and other evidence-based medicine researchers, Much progress has been made in this area with the availability of statistical data from Cochrane reviews to support re-use, and the number of evidence table templates that are freely available.
However, harnessing all this work to enable quick and easy sharing of all extracted data is still a challenge. Indeed, one of the challenges NICE has faced in updating its own guidelines is that advances in methodology for example GRADE means that evidence tables from original guidelines are no longer fit for purpose. As a result of this NICE, in 2016, adopted EPPI-Reviewer (https://eppi.ioe.ac.uk/CMS/) as its preferred tool for use while carrying out systematic reviewing task including data extraction. This provides a unique opportunity to build on existing data-sharing functionality to develop and ontology for extracted data with particular attention on baseline characteristics.

Objectives: To develop an ontology for extracted data based on commonly extracted data in national guidelines to facilitate re-use of all extracted data.

Methods:We will 1) perform a retrospective analysis of all 28 public health, social care and clinical guidelines published by NICE in 2016 with a view to identifying a minimum dataset extracted, how it is reported (text or numeric), units used if numeric and related qualifiers; and,
2) develop an ontology for data extraction for use in EPPI-Reviewer for all extracted data.

Results: To be presented and shared at the Summit.

Conclusions: To be presented and shared at the Summit.