Facilitating and Hindering Factors in the Implementation of a Care Transition Strategy: Mixed Methods Study

Objective: To identify facilitating and hindering factors for implementing a care transition strategy for adult patients undergoing elective colorectal cancer surgery, within a primary health care (PHC) context, addressing gaps in the literature on implementation challenges and contextual factors influencing such strategies. Methods: This complex mixed methods study combined a randomized clinical trial (RCT) and a qualitative component within an Implementation Research framework. The RCT enrolled adult patients with colorectal cancer, while the qualitative phase included a multilevel sample of participants. Iterative data integration occurred throughout the planning, implementation, and evaluation phases. The intervention was assessed using the RE-AIM (Reach, Efficacy, Adoption, Implementation, Maintenance) framework. Statistical analyses were conducted using IBM SPSS Statistics 22.0, applying descriptive and inferential methods. Results: Our findings revealed that the adoption of the intervention was satisfactory; however, Reach, Efficacy, and Implementation were not achieved. Facilitating factors included recognition of the potential of the care transition strategy to improve patient outcomes, and the intervention’s feasibility, replicability, and low cost. The main hindering factors identified included poor communication between care levels, inadequate material resources, and high workload. Integration of qualitative insights helped explain the limited quantitative impact, highlighting contextual challenges during the COVID-19 pandemic. Conclusions: The care transition strategy was well accepted by participants and health care providers, demonstrating potential to strengthen continuity of care between hospital and PHC services. Nonetheless, significant organizational and resource-related barriers hindered its effectiveness. Future studies are required to adapt transitional care models to overcome communication gaps, optimize resource allocation, and enhance implementation in similar settings.