Inventory management is a vital section of a supply chain system. In a hospital setting, where delivering high quality patient care is a prime concern, inventory management is often overlooked. With the ever increasing demand for products, it becomes challenging to manage inventory in a dynamic facility such as a hospital. Although there is abundant research in supply chain, seldom have the proposed methods found their way into execution in actual hospital settings. Additionally, much of the literature focuses on particular aspects of the supply chain. Current methods used in practice lead to system performance that is suboptimal, resulting in too much or too short inventory in stock, overtime work to manage supplies, expedited shipments and potentially substandard quality of care delivered to patients. Having the right products available at the point-of-use is important to the efficient and effective treatment of patients. With cost and budget constraints, merely managing demand is not sufficient. There is a need to develop a system design which enables hospitals and healthcare institutions to implement and benefit from methods that have been developed or are being developed for optimal inventory management systems. In this research, we study the hospital supply chain from manufacturers/distribution centers to the point-of-use within a hospital unit, taking into account the integration and implementation of the various echelon of the supply chain system. In particular, we design and develop a sim-heuristic methodology using operations research to evaluate inventory and operational decision variables based on service level and operational costs, subject to variability in demand and lead-time. In addition, we demonstrate the capabilities and limitations of the methodology and compare alternate system configurations including a (Q, r) inventory system and Kanban system.
Industrial and Systems Engineering (MS)
Department, Program, or Center
Industrial and Systems Engineering (KGCOE)
Michael E. Kuhl
Garg, Siddharth, "Efficient Inventory Management of Hospital Supply Chains Using a Sim-Heuristic Approach" (2018). Thesis. Rochester Institute of Technology. Accessed from
RIT – Main Campus