Integrating Data to Evaluate a Global Health Grand Challenge

Abstract

Th is article describes the integrated, mixed methods (MM) design used to evaluate the Saving Lives at Birth (SL@B) program. SL@B is a multi-stakeholder, donor-supported global health initiative to tackle maternal and neonatal mortality via innovation. Since SL@B’s launch in 2011, the program has supported 116 innovationsthrough 147 awards around the globe. The evaluation for this large and complex program included a largely retrospective MM design aligned with principles of evaluating complexity. This paper highlights these MM evaluation strategies and integration dimensions employed to complete the SL@B evaluation that could inform future evaluations of portfolio-level global health programs.