Analysis of

Tracking adaptations during implementation can help assess and interpret outcomes. The framework for reporting adaptations and modifications-expanded (FRAME) provides a structured approach to characterize adaptations. We applied the FRAME across multiple health services projects, and developed an analytic approach to assess the impact of adaptations. Mixed methods analysis of research diaries from seven quality improvement (QI) and research projects during the early stages of the COVID-19 pandemic. Using the FRAME as a codebook, discrete adaptations were described and categorized. We then conducted a three-step analysis plan: (1) calculated the frequency of adaptations by FRAME categories across projects; (2) qualitatively assessed the impact of adaptations on project goals; and (3) qualitatively assessed relationships between adaptations within projects to thematically consolidate adaptations to generate more explanatory value on how adaptations influenced intervention progress and outcomes. Between March and July 2020, 42 adaptations were identified across seven health services projects. The majority of adaptations related to training or evaluation (52.4%) with the goal of maintaining the feasibility (66.7%) of executing projects during the pandemic. Five FRAME constructs offered the most explanatory benefit to assess the impact of adaptations on program and evaluation goals, providing the basis for creating an analytic approach dubbed the "A-FRAME," analysis of FRAME data. Using the A-FRAME, the 42 adaptations were consolidated into 17 succinct adaptations. Two QI projects discontinued altogether. Intervention adaptations related to staffing, training, or delivery, while evaluation adaptations included design, recruitment, and data collection adjustments. By sifting qualitative data about adaptations into the A-FRAME, implementers and researchers can succinctly describe how adaptations affect interventions and their evaluations. The simple and concise presentation of information using the A-FRAME matrix can help implementers and evaluators account for the influence of adaptations on program outcomes.

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© 2023 The Authors. Learning Health Systems published by Wiley Periodicals LLC on behalf of University of Michigan.

Déclaration de conflit d'intérêts

The authors have no competing interests to declare.