Using a longitudinal multi-method approach to document, assess, and understand adaptations in the Veterans Health Administration Advanced Care Coordination program

Abstract

Background: Understanding adaptations supports iterative refinement of the implementation process and informs scale out of programs. Systematic documentation of adaptations across the life course of programs is not routinely done, and efficient capture of adaptations in real world studies is not well understood. Methods: We used a multi-method longitudinal approach to systematically document adaptations during pre-implementation, implementation, and sustainment for the Veteran Health Administration (VA) Advanced Care Coordination program. This approach included documenting adaptations through a real-time tracking instrument, process maps, Implementation and Evaluation (I&E) team meeting minutes, and adaptation interviews. Data collection was guided by the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) enhanced framework for reporting adaptations and modifications to evidence-based interventions (FRAME) model. Adaptations were evaluated across 9 categories, and analytic team consensus and member-checking were used to validate the results. Results: A total of 144 individual adaptations were identified across two implementation sites and the four data sources; analytic team consensus and member-checking processes resulted in 50 unique adaptations. Most adaptations took place during the early implementation and mid-implementation phases and were: 1) planned; 2) made to address changes in program delivery; 3) made to extend a component; 4) related to the core component of the intervention concerning notification of the community emergency department visit; 5) initiated by the entire or most of the I&E team; 6) made on the basis of: pragmatic/practical considerations; 7) made with an intent to improve implementation domain (to make the intervention delivered more consistently; to better fit the local practice, patient flow or Electronic Health Record (EHR) and/or for practical reasons); 8) a result of internal influences; 9) perceived to impact the RE-AIM implementation dimension (consistent delivery of quality care or costs). I&E team meeting minutes and process maps captured the highest numbers of unique adaptations (n = 19 and n = 13, respectively). Conclusion: Our longitudinal, multi-method approach provided a feasible way to collect adaptations data through engagement of multiple I&E team members, allowing and a broader understanding of adaptations that took place. Recommendations for future research include pragmatic assessment of the impact of adaptations and meaningful data collection without overburdening the implementing teams and front-line staff.