A modified Delphi study to identify the features of high quality measurement plans for healthcare improvement projects
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Published version
Author(s)
Woodcock, Thomas
Adeleke, Yewande
Goeschel, Christine
Pronovost, Peter
Dixon-Woods, Mary
Type
Journal Article
Abstract
Background
The design and execution of measurement in quality improvement (QI) initiatives is often poor. Better guidance on “what good looks like” might help to mitigate some of the problems. We report a consensus-building process that sought to identify which features are important to include in QI measurement plans.
Methods
We conducted a three-stage consensus-building approach: (1) identifying the list of features of measurement plans that were potential candidates for inclusion based on literature review and the study team’s experience; (2) a two-round modified Delphi exercise with a panel of experts to establish consensus on the importance of these features; and (3) a small in-person consensus group meeting to finalise the list of features.
Results
A list of 104 candidate questions was generated. A panel of 19 experts in the Delphi reviewed these questions and produced consensus on retaining 46 questions in the first round and on a further 22 in the second round. Thematic analysis of open text responses from the panellists suggested a number of areas of debate that were explicitly considered by the consensus group. The exercise yielded 74 questions (71% of 104) on which there was consensus in five categories of measurement relating to: design, data collection and management, analysis, action, and embedding.
Conclusions
This study offers a consensus-based view on the features of a good measurement plan for a QI project in healthcare. The results may be of use to QI teams, funders and evaluators, but are likely to require further development and testing to ensure feasibility and usefulness.
Key words: Measurement; Quality improvement; Quality measurement; Delphi technique.
The design and execution of measurement in quality improvement (QI) initiatives is often poor. Better guidance on “what good looks like” might help to mitigate some of the problems. We report a consensus-building process that sought to identify which features are important to include in QI measurement plans.
Methods
We conducted a three-stage consensus-building approach: (1) identifying the list of features of measurement plans that were potential candidates for inclusion based on literature review and the study team’s experience; (2) a two-round modified Delphi exercise with a panel of experts to establish consensus on the importance of these features; and (3) a small in-person consensus group meeting to finalise the list of features.
Results
A list of 104 candidate questions was generated. A panel of 19 experts in the Delphi reviewed these questions and produced consensus on retaining 46 questions in the first round and on a further 22 in the second round. Thematic analysis of open text responses from the panellists suggested a number of areas of debate that were explicitly considered by the consensus group. The exercise yielded 74 questions (71% of 104) on which there was consensus in five categories of measurement relating to: design, data collection and management, analysis, action, and embedding.
Conclusions
This study offers a consensus-based view on the features of a good measurement plan for a QI project in healthcare. The results may be of use to QI teams, funders and evaluators, but are likely to require further development and testing to ensure feasibility and usefulness.
Key words: Measurement; Quality improvement; Quality measurement; Delphi technique.
Date Issued
2020-01-14
Date Acceptance
2019-12-13
Citation
BMC Medical Research Methodology, 2020, 20 (1)
ISSN
1471-2288
Publisher
BioMed Central
Journal / Book Title
BMC Medical Research Methodology
Volume
20
Issue
1
Copyright Statement
© The Author(s) 2020. Open Access. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Sponsor
The Health Foundation
The Health Foundation
The Health Foundation
Grant Number
7343
7768
7174
Subjects
Measurement
Quality Improvement
Quality measurement
Delphi Technique
Publication Status
Published
Article Number
8