Applying Iterative RE-AIM to Translate Evaluation Data Into Real-Time Adaptations

Abstract Iterative RE-AIM provides a novel approach to evaluating interventions in real-time and translating those insights into actionable adaptations. Using the principles of iterative RE-AIM, we conducted a midpoint survey with the members of the coaching intervention team and the implementation evaluation team for 40Winks, a nursing home-based sleep trial. We convened a facilitated meeting with these two teams to discuss results and priorities, evaluate existing adaptations, review the effectiveness of the current intervention plan, propose future adaptations, and formulate a plan for implementation. The aggregated survey data were displayed and discussed by the two teams together as part of this process. While iterative RE-AIM outlines a process for evaluating an intervention’s adherence to the RE-AIM model, we applied this framework to evaluate the intervention’s components rather than the RE-AIM dimensions. This modification allowed us to bring all levels of the intervention and evaluation teams together to have a combined voice in the direction and evaluation of the intervention, and to make critical, real-time adaptations to enhance the effectiveness and reach of the intervention. This presentation will provide a roadmap of the process our team developed, guided by the principles of iterative RE-AIM, to display the evaluation survey and data and discuss strategies for implementing the results of this survey to lead real-time adaptations. This novel methodology allows the teams to learn from and act upon their own data in real time, allowing for iterative and systematic improvements in an intervention as a trial progresses.

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Publication Details

Journal
Innovation in Aging
Published
2025-12-01
DOI
https://doi.org/10.1093/geroni/igaf122.2065
Primary Topic
Health Policy Implementation Science
Type
article
Field-Weighted Citation Impact
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article

Applying Iterative RE-AIM to Translate Evaluation Data Into Real-Time Adaptations

Amy Recker, Sophia Geisser, Vanessa Aguilar, Ellen McCreedy et al.
Innovation in Aging
Health Policy Implementation Science
article

Applying Iterative RE-AIM to Translate Evaluation Data Into Real-Time Adaptations

Amy Recker, Sophia Geisser, Vanessa Aguilar, Ellen McCreedy, Rosa Baier, GEN A SMITH, A Lynn Snow, Amanda Piechota
article en

Abstract

Abstract Iterative RE-AIM provides a novel approach to evaluating interventions in real-time and translating those insights into actionable adaptations. Using the principles of iterative RE-AIM, we conducted a midpoint survey with the members of the coaching intervention team and the implementation evaluation team for 40Winks, a nursing home-based sleep trial. We convened a facilitated meeting with these two teams to discuss results and priorities, evaluate existing adaptations, review the effectiveness of the current intervention plan, propose future adaptations, and formulate a plan for implementation. The aggregated survey data were displayed and discussed by the two teams together as part of this process. While iterative RE-AIM outlines a process for evaluating an intervention’s adherence to the RE-AIM model, we applied this framework to evaluate the intervention’s components rather than the RE-AIM dimensions. This modification allowed us to bring all levels of the intervention and evaluation teams together to have a combined voice in the direction and evaluation of the intervention, and to make critical, real-time adaptations to enhance the effectiveness and reach of the intervention. This presentation will provide a roadmap of the process our team developed, guided by the principles of iterative RE-AIM, to display the evaluation survey and data and discuss strategies for implementing the results of this survey to lead real-time adaptations. This novel methodology allows the teams to learn from and act upon their own data in real time, allowing for iterative and systematic improvements in an intervention as a trial progresses.

Innovation in AgingVol. 9(Supplement_2)
University of Alabama (US), Brown University (US)
Openalex Percentile: Top 21%
Health Policy Implementation Science
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