Tobias Dreischulte
Process evaluation of the Data-driven Quality Improvement in Primary Care (DQIP) trial: quantitative examination of variation between practices in recruitment, implementation and effectiveness.
Dreischulte, Tobias; Grant, Aileen; Hapca, Adrian; Guthrie, Bruce
Abstract
The cluster randomised trial of the Data-driven Quality Improvement in Primary Care (DQIP) intervention showed that education, informatics and financial incentives for general medical practices to review patients with ongoing high-risk prescribing of non-steroidal anti-inflammatory drugs and antiplatelets reduced the primary end point of high-risk prescribing by 37%, where both ongoing and new high-risk prescribing were significantly reduced. This quantitative process evaluation examined practice factors associated with (1) participation in the DQIP trial, (2) review activity (extent and nature of documented reviews) and (3) practice level effectiveness (relative reductions in the primary end point). Invited practices recruited (n=33) and not recruited (n=32) to the DQIP trial in Scotland, UK. (1) Characteristics of recruited versus non-recruited practices. Associations of (2) practice characteristics and 'adoption' (self-reported implementation work done by practices) with documented review activity and (3) of practice characteristics, DQIP adoption and review activity with effectiveness. Recruited practices had lower performance in the quality and outcomes framework than those declining participation. Not being an approved general practitioner training practice and higher self-reported adoption were significantly associated with higher review activity. Effectiveness ranged from a relative increase in high-risk prescribing of 24.1% to a relative reduction of 77.2%. High-risk prescribing and DQIP adoption (but not documented review activity) were significantly associated with greater effectiveness in the final multivariate model, explaining 64.0% of variation in effectiveness. Intervention implementation and effectiveness of the DQIP intervention varied substantially between practices. Although the DQIP intervention primarily targeted review of ongoing high-risk prescribing, the finding that self-reported DQIP adoption was a stronger predictor of effectiveness than documented review activity supports that reducing initiation and/or re-initiation of high-risk prescribing is key to its effectiveness.
Citation
DREISCHULTE, T., GRANT, A., HAPCA, A. and GUTHRIE, B. 2018. Process evaluation of the Data-driven Quality Improvement in Primary Care (DQIP) trial: quantitative examination of variation between practices in recruitment, implementation and effectiveness. BMJ open [online], 8(1), article ID e017133. Available from: https://doi.org/10.1136/bmjopen-2017-017133
Journal Article Type | Article |
---|---|
Acceptance Date | Nov 1, 2017 |
Online Publication Date | Jan 5, 2018 |
Publication Date | Jan 31, 2018 |
Deposit Date | Jan 9, 2018 |
Publicly Available Date | Jan 9, 2018 |
Journal | BMJ open |
Electronic ISSN | 2044-6055 |
Publisher | BMJ Publishing Group |
Peer Reviewed | Peer Reviewed |
Volume | 8 |
Issue | 1 |
Article Number | e017133 |
DOI | https://doi.org/10.1136/bmjopen-2017-017133 |
Keywords | Quality improvement; Primary care; DQIP; High-risk prescribing; Quantitative data |
Public URL | http://hdl.handle.net/10059/2653 |
Contract Date | Jan 9, 2018 |
Files
DREISCHULTE 2018 Process evaluation of the data
(2.1 Mb)
PDF
Publisher Licence URL
https://creativecommons.org/licenses/by-nc/4.0/
You might also like
Downloadable Citations
About OpenAIR@RGU
Administrator e-mail: publications@rgu.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2025
Advanced Search