With the deepening of population aging, primary elderly health governance is facing the dual dilemma of resource shortage and insufficient service accuracy. Big data technology provides a new way to solve the problem. However, the existing reviews have mainly focused on the macro policy framework and have lacked systematic reviews at the county levels and city levels. Taking Chenzhou city as a sample, this paper systematically reviewed the multi-dimensional application of big data in primary elderly health governance in the city for the first time, covering multi-source health data collection and integration, real-time monitoring and early warning, data-driven decision-making model, chronic disease management, personalized intervention, health assessment and risk prediction. The supporting technology system (data mining, integration of artificial intelligence and machine learning, platform construction and optimization) and the historical evolution of governance mode from manual management to informatization and then to big data empowerment are summarized. The panorama analysis summarizes the key challenges such as data privacy security, technological equity, result reliability and algorithm interpretability, and proposes a sustainable development path from three aspects: interdisciplinary integration, technology potential release and policy and technology collaboration. This review fills the gap in the systematic review of digital elderly health governance at county and city level, provides an empirical paradigm and decision-making reference for similar regions, and lays a theoretical foundation for subsequent empirical research and policy optimization.