The Use of Implementation Science Tools to Design, Implement, and Monitor a Community-Based mHealth Intervention for Child Health in the Amazon

It is essential to analyze the local context and implementation components to effectively deliver evidence-based solutions to public health problems. Tools provided by the field of implementation science can guide practitioners through a comprehensive implementation process, making innovations more adaptable, efficient, and sustainable. It is equally important to report on the design and implementation process so others can analyze, replicate, and improve on the progress made from an intervention. The current study reports on the design and implementation of an mHealth intervention to improve child health in the Amazon of Peru. The study aims to provide insight into how an implementation science tool can be used to improve implementation and reporting of an evidence-based intervention in a global health setting. Methods: Implementation of a community-based mHealth intervention is analyzed and reported through the lens of the Active Implementation Frameworks (AIF). The AIF is used to analyze the design, implementation, adaptation, and monitoring of the intervention. The implementation process is categorized in the four stages of implementation. The results of the analysis and subsequent implementation activities are reported. Results: The exploration stage was used to learn about the local context in the Amazonian communities and identify an evidence-based solution to address poor child health. Several potential solutions were combined to create an innovative mHealth tool. During the installation stage, the stakeholders worked together to improve the intervention and plan for implementation through human-centered design. The providers in the field were trained and data was gathered to monitor implementation. During initial implementation stage, electronic tablets were distributed to community health agents and continuous quality improvement activities allowed for rapid improvements to be implemented. The intervention moved on to full implementation stage as acceptance and fidelity approached 100%. Conclusion: The AIF highlighted several potential barriers to implementation that may have been overlooked without the guidance of a science-based implementation tool. Reporting on the implementation process shows how implementation science tools can be used to foresee and address potential threats to successful implementation. The results of this study provide insight into the components of implementation in Amazonian communities, as well as the process of using implementation science tools in any global health setting.