- Celia Brown, research fellow,
- Richard Lilford, professor of clinical epidemiology
- 1Department of Public Health and Epidemiology, University of Birmingham, Edgbaston, Birmingham B15 2TT
- Correspondence to: C Brown c.a.brown{at}bham.ac.uk
- Accepted 7 October 2008
The quantity of research into patient safety has risen substantially over the past decade.1 Nevertheless, concerns remain over the quality of much of this research2 and there are disagreements about methods.3 As a result, the Medical Research Council sponsored a cross council research network in patient safety research to provide methodological guidance on evaluation of patient safety interventions. This resulted in publication of a series of articles in Quality and Safety in Health Care.4 5 6 7 Here we summarise two main themes developed in the series: study design and determining what observations should be made.
Summary points
The choice of study design and determining what observations should be made are important when evaluating quality and safety interventions
A controlled before and after design (including the stepped wedge design) should be considered when summative evaluations are required
A modified form of Donabedian’s causal chain (structure, process, and outcome) provides a framework for evaluation
Whenever possible, mixed methods (qualitative and quantitative) should be used to make observations at different levels across the causal chain
It is not possible to cleanly separate safety interventions from quality improvements.4 That said, the term safety is typically used in the context of rare incidents where there is a rapid and strong link between an error and its associated outcome. Our comments therefore apply to both safety and quality improvement but take into account the rarity of many safety incidents. Safety interventions are directed at the system in which care is delivered. They are thus service delivery interventions not new health technologies. Such interventions are often complex and should be evaluated before implementation (alpha testing), as advocated by both the …
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