Workshop W29

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The devil in the detail: data abstraction forms for systematic reviews of complex interventions.
Stephanie Taylor.
St Bartholomew's and The London Queen Mary's School of Medicine and Dentistry, London, UK.
Sonja Hood.
Program Evaluation Unit, School of Population Health, University of Melbourne, Australia.

s.j.c.taylor doesnotexist@cochrane.org qmul.ac.uk

Objectives:

To gain better understanding of the challenges of abstracting data from reports of trials, particularly from trials of complex interventions;
To share strategies and good practice around the approach to data abstraction and the design of data abstraction forms for trials, particularly for trials of complex interventions;
To collate the issues raised and the conclusions of the workshop into a brief report offering practical guidance to those working in this area (and which we hope to submit to the editors of the Cochrane Handbook for Systematic Reviews of Interventions for consideration for inclusion in the section on data abstraction).

Summary: Complex interventions in health care are non-pharmacological interventions "made up of various interconnecting parts" (Campbell 2000). Trials of complex interventions are increasingly becoming the subject of systematic reviews. Data abstraction is a key step in systematic reviewing and the content and structure of the data abstraction form (either electronic or paper) shape the completed systematic review. We have found that data abstraction may be particularly difficult where reports of complex interventions are concerned since published accounts of trials of complex interventions are often very dense and the multi-faceted nature of the interventions predisposes the reporting of a wide variety of endpoints and outcomes (not to mention the diverse elements of the intervention itself).

In our experience, the design of the data abstraction form is intimately linked to the overall quality of the completed review . A well designed data abstraction form can promote rigour, validity and efficiency. In this workshop we will discuss practical issues around data abstraction and share some of our ideas about the way data abstraction might be approached. We will also examine how other people's data abstraction tools have shaped their completed systematic reviews. The session will be very participatory and a real "work shop" with people bringing examples of their own data abstraction tools and sharing examples of good data abstraction tools and practice. Findings of the workshop will be compiled into a set of simple, practical guidance to help others working in the field.

Level of knowledge required to attend: basic (but experience of data abstraction and an understanding of complex interventions would be helpful).