Abstract: The rapid development of data technologies has significantly expanded the application of data-driven approaches in blood inventory management. To elucidate the research evolution, identify key hotspots, and clarify future trends, a comprehensive review of existing research is conducted. Based on a systematic search across multiple authoritative databases, 92 relevant studies are selected and analyzed using bibliometric and knowledge graph techniques. The analysis provides a macro-level examination from multiple perspectives, including publication volume, journal distribution, author collaboration networks, and keyword co-occurrence patterns. Three critical areas are focused: blood demand forecasting, inventory level control, and inventory allocation and distribution, while applications of data-driven methods in these areas are systematically summarized. Based on the limitations of existing research and the practical needs of the industry, future research directions are proposed from four aspects: research problems, methodological frameworks, data foundations, and system-level applications. To the best of our knowledge, no comprehensive review has yet been conducted focusing on data-driven blood inventory management. This study fills this gap by providing valuable insights into literature integration and structured analysis. The findings contribute to a better understanding of the current research progress and offer theoretical and methodological support for the intelligent transformation of blood inventory management.