Abstract
Blood type substitution is an effective policy for improving the blood supply chain resilience in responding to shortages at hospitals. However, while compatibility of certain blood types provides an opportunity to better manage volatility in supply (donation) and demand (transfusion), in practice, it remains challenging to decide whether to use a compatible blood unit from the on-hand inventory (substitution) or to place an urgent or emergency order. Available evidence indicates that, in Australia, current practices for deciding on blood type substitution over emergency orders result in a significant imbalance in supply and demand for the most widely compatible units: O-negative blood units. This challenge is particularly critical in blood inventory management and represents a significant research opportunity for the operations management community. It can be addressed using state-of-the-art methodologies in data-driven decision making and perishable inventory under stochastic supply and demand. This study proposes a stochastic optimization model based on sample-average approximation (SAA) to aid the blood type substitution decisions at hospitals. We take into account the historical demand data, the type and age of blood units in the inventory, as well as the shelf-life variability of the units arriving at hospitals. We compare the SAA results with several policies, including a single-period myopic model, no-substitution, over-order practice, and an empirical guideline. Results indicate that the proposed SAA model outperforms all the above policies. It thus creates significant opportunities for improvement in the management of blood units, as it reduces the imbalance in the supply and demand of O-negative blood units, allowing practitioners to benefit from substitution while avoiding the over-ordering of O-negative units.
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