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Testing feedback message framing and comparators to address prescribing of high-risk medications in nursing homes: protocol for a pragmatic, factorial, cluster-randomized trial

Authors :
Noah M. Ivers
Laura Desveaux
Justin Presseau
Catherine Reis
Holly O. Witteman
Monica K. Taljaard
Nicola McCleary
Kednapa Thavorn
Jeremy M. Grimshaw
Source :
Implementation Science, Vol 12, Iss 1, Pp 1-11 (2017)
Publication Year :
2017
Publisher :
BMC, 2017.

Abstract

Abstract Background Audit and feedback (AF) interventions that leverage routine administrative data offer a scalable and relatively low-cost method to improve processes of care. AF interventions are usually designed to highlight discrepancies between desired and actual performance and to encourage recipients to act to address such discrepancies. Comparing to a regional average is a common approach, but more recipients would have a discrepancy if compared to a higher-than-average level of performance. In addition, how recipients perceive and respond to discrepancies may depend on how the feedback itself is framed. We aim to evaluate the effectiveness of different comparators and framing in feedback on high-risk prescribing in nursing homes. Methods This is a pragmatic, 2 × 2 factorial, cluster-randomized controlled trial testing variations in the comparator and framing on the effectiveness of quarterly AF in changing high-risk prescribing in nursing homes in Ontario, Canada. We grouped homes that share physicians into clusters and randomized these clusters into the four experimental conditions. Outcomes will be assessed after 6 months; all primary analyses will be by intention-to-treat. The primary outcome (monthly number of high-risk medications received by each patient) will be analysed using a general linear mixed effects regression model. We will present both four-arm and factorial analyses. With 160 clusters and an average of 350 beds per cluster, assuming no interaction and similar effects for each intervention, we anticipate 90% power to detect an absolute mean difference of 0.3 high-risk medications prescribed. A mixed-methods process evaluation will explore potential mechanisms underlying the observed effects, exploring targeted constructs including intention, self-efficacy, outcome expectations, descriptive norms, and goal prioritization. An economic analysis will examine cost-effectiveness analysis from the perspective of the publicly funded health care system. Discussion This protocol describes the rationale and methodology of a trial testing manipulations of theory-informed components of an audit and feedback intervention to determine how to improve an existing intervention and provide generalizable insights for implementation science. Trial registration NCT02979964

Details

Language :
English
ISSN :
17485908
Volume :
12
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Implementation Science
Publication Type :
Academic Journal
Accession number :
edsdoj.fa269e956ee469d999729b1360a995c
Document Type :
article
Full Text :
https://doi.org/10.1186/s13012-017-0615-7