Cargando…

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

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Grant, Aileen, Dreischulte, Tobias, Treweek, Shaun, Guthrie, Bruce
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3502604/
https://www.ncbi.nlm.nih.gov/pubmed/22929598
http://dx.doi.org/10.1186/1745-6215-13-154
_version_ 1782250377974906880
author Grant, Aileen
Dreischulte, Tobias
Treweek, Shaun
Guthrie, Bruce
author_facet Grant, Aileen
Dreischulte, Tobias
Treweek, Shaun
Guthrie, Bruce
author_sort Grant, Aileen
collection PubMed
description 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
format Online
Article
Text
id pubmed-3502604
institution National Center for Biotechnology Information
language English
publishDate 2012
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-35026042012-11-22 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 Grant, Aileen Dreischulte, Tobias Treweek, Shaun Guthrie, Bruce Trials Study Protocol 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 BioMed Central 2012-08-28 /pmc/articles/PMC3502604/ /pubmed/22929598 http://dx.doi.org/10.1186/1745-6215-13-154 Text en Copyright ©2012 Grant et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Study Protocol
Grant, Aileen
Dreischulte, Tobias
Treweek, Shaun
Guthrie, Bruce
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
title 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
title_full 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
title_fullStr 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
title_full_unstemmed 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
title_short 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
title_sort 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
topic Study Protocol
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3502604/
https://www.ncbi.nlm.nih.gov/pubmed/22929598
http://dx.doi.org/10.1186/1745-6215-13-154
work_keys_str_mv AT grantaileen studyprotocolofamixedmethodsevaluationofaclusterrandomizedtrialtoimprovethesafetyofnsaidandantiplateletprescribingdatadrivenqualityimprovementinprimarycare
AT dreischultetobias studyprotocolofamixedmethodsevaluationofaclusterrandomizedtrialtoimprovethesafetyofnsaidandantiplateletprescribingdatadrivenqualityimprovementinprimarycare
AT treweekshaun studyprotocolofamixedmethodsevaluationofaclusterrandomizedtrialtoimprovethesafetyofnsaidandantiplateletprescribingdatadrivenqualityimprovementinprimarycare
AT guthriebruce studyprotocolofamixedmethodsevaluationofaclusterrandomizedtrialtoimprovethesafetyofnsaidandantiplateletprescribingdatadrivenqualityimprovementinprimarycare