Toward a mixed-methods framework for evaluating digital health systems in low-resource settings: an infrastructure-aware perspective

Digital health technologies have become integral to health system strengthening, yet their implementation in low-resource settings continues to face persistent challenges related to unreliable infrastructure, limited technical capacity, and constrained financial resources. Although existing digital health evaluation frameworks have advanced understanding of technology adoption, implementation, and sustainability, they frequently treat infrastructure as a contextual factor rather than a core determinant of digital health system performance. This Perspective argues that future evaluation should move beyond technology-centered assessment toward infrastructure-aware evaluation that explicitly recognizes the interdependencies among technical, infrastructural, operational, and economic dimensions. We propose an infrastructure-aware framework for evaluating digital health systems that integrates mixed-methods evaluation and builds upon established implementation science by recognizing infrastructure as a core evaluation domain alongside technical, operational, and economic considerations. The framework positions infrastructure, including energy reliability, internet connectivity, hardware availability, maintenance capacity, and technical support, as a central determinant of implementation feasibility and long-term sustainability. It is informed by implementation science, socio-technical systems thinking, and practical insights from digital health implementation in resource-constrained settings and is illustrated using the Bright Health program in Kenya and Ethiopia. By providing a structured, infrastructure-aware perspective, the proposed framework complements existing implementation science approaches and offers a more comprehensive basis for evaluating digital health systems in low-resource environments. Future research should operationalize the proposed domains, develop standardized evaluation indicators, and empirically validate the framework across diverse technologies and implementation contexts to support more resilient, equitable, and sustainable digital health systems.