Trials

, 16:P223 | Cite as

Matching trial design decisions to the needs of those you hope will use the results: the PRECIS-2 tool

  • Kirsty Loudon
  • Merrick Zwarenstein
  • Frank Sullivan
  • Peter Donnan
  • Shaun Treweek
Poster presentation

Keywords

Team Member Healthcare Professional Design Decision Potential User Routine Care 

Randomised trials are hard work. Like much that is hard, this toil is only worth it because of the prospect of a substantial reward. Sadly, the reward to potential users such as patients, healthcare professionals and policy makers is often smaller than it should be because trial design decisions reduced the relevance of the trial to them.

PRECIS-2 is a tool designed to help trialists match their design decisions to the information needs of those they hope will use the trial results. It is an update of the 2009 PRECIS tool, which though highly cited had some well-known weaknesses. PRECIS-2 was developed in collaboration with over 80 international trialists, methodologists and others to produce a tool that addressed those weaknesses but also supports improved design insight for trialists.

PRECIS-2 retains the wheel format of the original tool. It has nine design domains including Eligibility, Recruitment, Setting and Primary outcome. A new domain - Organisation - is explicitly aimed at making trialists consider the resource requirements their intervention will place on health care systems if it were to be rolled out into routine care, the intention being to think about implementation at the design stage. The highly visual presentation makes inconsistent decision-making immediately obvious; it also highlights differences of opinion between trial team members.

We will present the tool, explain how to use it and show examples of how it has been used already. This work is part of the Trial Forge initiative to improve trial efficiency.

Copyright information

© Loudon et al. 2015

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors and Affiliations

  • Kirsty Loudon
    • 1
  • Merrick Zwarenstein
    • 3
  • Frank Sullivan
    • 4
  • Peter Donnan
    • 2
  • Shaun Treweek
    • 1
  1. 1.University of AberdeenAberdeenUK
  2. 2.University of DundeeDundeeUK
  3. 3.Western UniversityLondonCanada
  4. 4.University of TorontoTorontoCanada

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