Geographic information systems (GIS), a powerful tool for examining the spatial patterns of disease and health services and their underlying patterns and contributing factors, are critically important for understanding the social-spatial determinants of health. However, GIS methods have inherent limitations that are often ignored and can lead to misleading conclusions. Using several examples, this paper examines the promise and potential of GIS for the spatial analysis of disease and health care, and social determinants of health. It also highlights common methodological challenges, including autocorrelation, spatial support, and small data. We argue that robust and comprehensive surveillance data on the geography of economic stability, educational access, healthcare quality, built environments, community context, environmental conditions, disease agents, and health outcomes over time are indispensable if the full potential of GIS is to be achieved. Moreover, the role of power and vulnerability in explaining the spatial patterns of disease and healthcare must become more prominent to reflect the dynamic nature of health.