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

Noah M Ivers, Laura Desveaux, Justin Presseau, Catherine Reis, Holly O Witteman, Monica K Taljaard, Nicola McCleary, Kednapa Thavorn, Jeremy M Grimshaw, Noah M Ivers, Laura Desveaux, Justin Presseau, Catherine Reis, Holly O Witteman, Monica K Taljaard, Nicola McCleary, Kednapa Thavorn, Jeremy M Grimshaw

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.

Keywords: Audit and feedback; High-risk prescribing; Nursing homes; Randomized trial.

Conflict of interest statement

Ethics approval and consent to participate

Ethics approval has been received from the University of Toronto and Women’s College Hospital Research Ethics Boards (#2016-0122-E). The Ottawa Health Science Network Research Ethics Board approved the process evaluation and the economic evaluation (#20160934-01H).

Consent for publication

All authors have read and approved the final manuscript.

Competing interests

JP is an associate editor of implementation science. JG and NMI are members of the editorial board of implementation science.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures

Fig. 1
Fig. 1
Theory-informed logic model. APM antipsychotic medication, BCT behaviour change technique, BZD benzodiazepine, CNS central nervous system

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