A modified Delphi study to identify the features of high quality measurement plans for healthcare improvement projects

BMC Medical Research Methodology. 2020;20(1):1-9 DOI 10.1186/s12874-019-0886-6

 

Journal Homepage

Journal Title: BMC Medical Research Methodology

ISSN: 1471-2288 (Online)

Publisher: BMC

LCC Subject Category: Medicine: Medicine (General)

Country of publisher: United Kingdom

Language of fulltext: English

Full-text formats available: PDF, HTML

 

AUTHORS


Thomas Woodcock (NIHR ARC Northwest London, Imperial College, Reynolds Building)

Yewande Adeleke (NIHR ARC Northwest London, Imperial College, Reynolds Building)

Christine Goeschel (Medstar Health, Institute for Quality and Safety)

Peter Pronovost (University Hospitals Management Services Center)

Mary Dixon-Woods (THIS Institute (The Healthcare Improvement Studies Institute), University of Cambridge)

EDITORIAL INFORMATION

Open peer review

Editorial Board

Instructions for authors

Time From Submission to Publication: 23 weeks

 

Abstract | Full Text

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.