UNSTRUCTURED
Electronic data capture systems are critical to sustaining, evaluating, and improving population health. Globally, some Low-and-Middle Income Countries face barriers to implementing data systems related to limited data infrastructure, human resources, or financial capital. This paper presents two case examples on the initial development of electronic data capture systems to improve population health from two global contexts– Ethiopia and Myanmar. We analyze these cases using Sittig and Singh’s Socio-technical Model for Studying Health Information Technology in Complex Adaptive Healthcare Systems. Both cases also describe how the electronic data capture systems facilitated continued population health research under dual crises—both civil unrest and the COVID-19 pandemic. Notably, the sociotechnical model highlights how critical social and cultural considerations are in technically designing electronic data capture systems to improve population health and surveillance. These applied cases offer practical lessons to inform data system efforts for similar global contexts.