Reviewing methodologically disparate data: a practical guide for the patient safety research field.

J Eval Clin Pract

Imperial Centre for Patient Safety and Service Quality and Division of Surgery, Department of Surgery and Cancer, Imperial College London, London, UK.

Published: February 2012

This article addresses key questions frequently asked by researchers conducting systematic reviews in patient safety. This discipline is relatively young, and asks complex questions about complex aspects of health care delivery and experience, therefore its studies are typically methodologically heterogeneous, non-randomized and complex; but content rich and highly relevant to practice. Systematic reviews are increasingly necessary to drive forward practice and research in this area, but the data do not always lend themselves to 'standard' review methodologies. This accessible 'how-to' article demonstrates that data diversity need not preclude high-quality systematic reviews. It draws together information from published guidelines and experience within our multidisciplinary patient safety research group to provide entry-level advice for the clinician-researcher new to systematic reviewing, to non-biomedical research data or to both. It offers entry-level advice, illustrated with detailed practical examples, on defining a research question, creating a comprehensive search strategy, selecting articles for inclusion, assessing study quality, extracting data, synthesizing data and evaluating the impact of your review. The article concludes with a comment on the vital role of robust systematic reviews in the continuing advancement of the patient safety field.

Download full-text PDF

Source
http://dx.doi.org/10.1111/j.1365-2753.2010.01519.xDOI Listing

Publication Analysis

Top Keywords

patient safety
16
systematic reviews
16
safety field
8
entry-level advice
8
data
6
systematic
5
reviewing methodologically
4
methodologically disparate
4
disparate data
4
data practical
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!