Triple A: How Analytics, AI, and Algorithms Are Improving Inventory Management in Healthcare

Background: Healthcare inventory management is critical for ensuring timely access to supplies and reducing stockouts. As supply chains grow more complex, algorithms, AI, and analytics techniques have emerged as tools for forecasting, tracking, classification, and procurement. Yet empirical validation across diverse contexts remains inadequate, and existing reviews treat these approaches as separate streams rather than an integrated system. Methods: To evaluate these capabilities, a systematic review of 64 peer-reviewed articles published between 2011 and 2025 was conducted using a descriptive and content analysis approach on the use of Triple A (Analytics, AI, and Algorithms) techniques in inventory frameworks across various healthcare contexts, such as hospitals, pharmaceutical supply chains, and humanitarian supply chains. Results: Integrating multiple Triple A approaches consistently outperforms single-method strategies, particularly with RFID and IoT tools. Key findings often overlooked are: emergency procurement and classification, which remain neglected despite the highest patient safety stakes, and key procurement drivers—organizational conditions, supplier reliability, and team capacity. Data quality, interoperability, and cybersecurity further constrain generalizability. Conclusions: Bridging these gaps requires integrated Triple A approaches rather than single methods. Phased implementation, cloud-based platforms, and privacy-by-design offer practical pathways for building resilience under real-world constraints.