- Poster presentation
- Open Access
Feasibility work to inform trial design: using collaborative methods for efficient real-time data collection in the operating theatre
© Blencowe et al. 2015
Published: 16 November 2015
RCTs in surgery can be difficult to design, meaning pre-trial feasibility work is necessary. This may involve surveying views of surgeons; however, response rates can be poor and findings unrepresentative. An alternative - real-time data collection - may be challenging in the operating theatre environment. Recently, trainee surgeons have formed ‘research collaboratives’ to undertake multi-centre studies. This study established collaborative methods for efficient real-time operating theatre data collection to inform the design of an RCT.
150 surgical trainees from 25 hospitals within two collaborative networks were invited to collect prospective data about wound dressings in abdominal surgery, over a two week period. Data could be uploaded directly from operating theatre onto a central server. Participation was encouraged by releasing each centre's data for local presentation and rapid publication using a collaborative authorship model.
21 hospitals expressed interest and 20(80%) participated. 60 trainees collected data from 726 patients, providing 1791 wounds for analysis. Complete datasets were submitted for 677(93%) patients. Findings have informed design of the main study by identifying a) frequent use of tissue adhesive which was not previously recognised as a dressing (indicating that an RCT should include this as a comparator), and b) use of similar dressing types for elective and unplanned surgery (indicating that the planned inclusion criteria could be widened).
Trainee-led collaboratives offer a novel approach to developing, managing, and delivering research studies in challenging settings. We recommend that trials teams consider working with trainees to efficiently generate high quality data that can inform trial design.
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.