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. 2022 Oct 17;2:959565. doi: 10.3389/frhs.2022.959565

Table 4.

Key crosscutting issues in applying Iterative RE-AIM.

Issue Description
Implementation partner engagement Advantageous to get persons that will be impacted from different perspectives involved- e.g., organizational decision makers, clinicians, front line delivery staff, recipients (patients); however, getting a large number and variety of people to consistently attend meetings can be challenging
Data for decision making It is challenging to get rapid reliable data rather than perceptions on RE-AIM outcomes and then to display results in ways that are clear and actionable. Project records can be designed and automated to make it easier to obtain data for issues such as reach, and implementation issues such as fidelity and adaptations
Discussion of progress and priorities The core issue and “secret to success” of Iterative RE-AIM is sharing and discussing both the objective and subjective data and perceptions; discussing similarities and differences of opinion (and reasons why); and coming up with consensus strategies for action
Evaluating impact While not unique to Iterative RE-AIM, in most projects it is difficult to attribute changes in intermediate outcomes to action plans and Iterative RE-AIM based adaptations implemented due to many changing variables, lack of experimental design, and miscellaneous uncontrolled factors,
Time and resources required One needs to decide how much time and resources to devote to Iterative RE-AIM. This can range from minimal- doing it once at middle of program, using whatever staff are available, and relying solely on staff perceptions for goal setting/strategy selection- to several systematic iterations involving comprehensive data collection and detailed adaptation tracking
Balancing standardization and adaptation It is necessary to strike a balance between accomplishing the key functions of Iterative RE-AIM in Table 1 and making appropriate adaptation to the forms needed in different settings and contexts having different data sources, resources, and priorities