Trials | |
Study protocol of a mixed-methods evaluation of a cluster randomized trial to improve the safety of NSAID and antiplatelet prescribing: data-driven quality improvement in primary care | |
Bruce Guthrie2  Shaun Treweek2  Tobias Dreischulte1  Aileen Grant2  | |
[1] Medicines Management Unit, NHS Tayside, c/o University of Dundee, Mackenzie Building, Dundee, DD2 4BF, UK;Quality, Safety and Informatics Research Group, Population Health Sciences, University of Dundee, Mackenzie Building, Dundee, DD2 4BF, UK | |
关键词: Randomized controlled trial; Mixed methods; Protocol; Process evaluation; Complex intervention; | |
Others : 1095363 DOI : 10.1186/1745-6215-13-154 |
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received in 2012-05-04, accepted in 2012-07-26, 发布年份 2012 | |
【 摘 要 】
Background
Trials of complex interventions are criticized for being ‘black box’, so the UK Medical Research Council recommends carrying out a process evaluation to explain the trial findings. We believe it is good practice to pre-specify and publish process evaluation protocols to set standards and minimize bias. Unlike protocols for trials, little guidance or standards exist for the reporting of process evaluations. This paper presents the mixed-method process evaluation protocol of a cluster randomized trial, drawing on a framework designed by the authors.
Methods/design
This mixed-method evaluation is based on four research questions and maps data collection to a logic model of how the data-driven quality improvement in primary care (DQIP) intervention is expected to work. Data collection will be predominately by qualitative case studies in eight to ten of the trial practices, focus groups with patients affected by the intervention and quantitative analysis of routine practice data, trial outcome and questionnaire data and data from the DQIP intervention.
Discussion
We believe that pre-specifying the intentions of a process evaluation can help to minimize bias arising from potentially misleading post-hoc analysis. We recognize it is also important to retain flexibility to examine the unexpected and the unintended. From that perspective, a mixed-methods evaluation allows the combination of exploratory and flexible qualitative work, and more pre-specified quantitative analysis, with each method contributing to the design, implementation and interpretation of the other.
As well as strengthening the study the authors hope to stimulate discussion among their academic colleagues about publishing protocols for evaluations of randomized trials of complex interventions.
Data-driven quality improvement in primary care trial registration
ClinicalTrials.gov: NCT01425502
【 授权许可】
2012 Grant et al.; licensee BioMed Central Ltd.
【 预 览 】
Files | Size | Format | View |
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20150130183521414.pdf | 501KB | download | |
Figure 1. | 74KB | Image | download |
【 图 表 】
Figure 1.
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