A Review and Prospect of Data-driven Approaches in Blood Inventory Management

The rapid advancement of data technologies has broadened the application of data-driven approaches in blood inventory management. To elucidate the research landscape, identify key hotspots, and trace emerging trends, a comprehensive review of relevant literature was conducted. Based on a systematic search across multiple authoritative databases, 92 studies were selected and analyzed using bibliometric and knowledge mapping techniques. The analysis covers publication trends, journal distribution, author collaboration networks, and keyword co-occurrence patterns. Three critical operational areas are examined: blood demand forecasting, inventory level control, and inventory allocation and distribution. Applications of data-driven methods in these areas are systematically summarized. Building on the limitations of existing research and the practical needs of the industry, future research directions are proposed in four aspects: research problems, methodological systems, data foundations, and practical applications. Currently, there is a lack of systematic review research focusing on data-driven blood inventory management. Valuable insights into literature integration and structured analysis are provided in this paper. The findings offer theoretical and methodological support for the intelligent transformation of blood inventory systems.