Digital Health is a multi-disciplinary science connecting medicine, technology, and implementation science. A growing evidence base highlights increasing recognition for its potential to strengthen overall health system performance. However, historically, the majority of evidence focuses on improvements of care processes rather than health outcomes. This thesis investigated aspects of evaluating health outcomes of digital health on different levels and proposes approaches to overcome some of the associated challenges. First, on micro level, what to measure by identifying meaningful proxy-indicators for maternal/neonatal outcomes. Second, on meso level, understanding how researchers approach digital health impact evaluations and providing a pedagogical overview on methods. Finally, on macro level, an approach to connecting disparate knowledge, experience, and evidence. Together, these articles provide a multi-level toolkit for evaluating and aggregating outcomes of digital health interventions to establish a comprehensive picture of the digital health landscape and increase the understanding for determinants influencing success and failure.