Operating room inventories typically involve hundreds of surgical items. Managers require very high service levels since the cost of shortages can be excessive up to and including cancelling surgery. From our experience, many inventory managers rely on manual approaches and intuition to set inventory control parameters. Although there are classical theoretical methods available for deriving "optimal" inventory policies, these classical methods rely on assumptions that do not accurately represent typical operating room inventories. Using 5 years of data from a large Canadian hospital, we use simulation and a simple search heuristic to find the optimal (s, S) ordering policy and show that 1) current hospital methods dramatically underperform with respect to service level and 2) there are significant savings to be realised over the best available classical theoretical models. An example case testing potential lead time changes is discussed.
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Carter et al. (2024) studied this question.
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