Background In a multidisciplinary hospital, inventory management involves a difficult balance between the risk of running out of stock and the cost of stock. We therefore implemented a new inventory management method in December 2017, taking into account the Pareto law.¹

Purpose The purpose of this economic study was to determine which inventory management model is the most economical.

Material and methods Drug orders previously placed when the safety threshold was reached were grouped by laboratory. A monthly schedule of laboratory orders had been published so that high-cost drugs were processed at the beginning of the month. Quantities ordered made it possible to obtain a stock equivalent to 1 month of consumption. Stock’s value was evaluated with MAGH2 management software retrospectively over the first 5 months of the years 2017 and 2018. During the same period, monthly orders made were evaluated. We performed a statistical test comparing stock value averages before and after management change. We compared the overall cost of placing orders before and after this management change.

Results The average decrease in the stock’s value observed after modification of inventory management mode is 38%. The difference between the averages observed before and after this change is significant at alpha risk=5% and the assumption that the value of the stock is significantly lower when the Pareto law is taken into account is verified. Order’s cost was evaluated at €60 per order. Before implementation of the monthly calendar, grouping specialties of the same laboratory in a single day, the average number of monthly orders was 258. Then the average number of monthly orders decreased to 202. The average monthly cost of placing an order has been reduced by €3360 thanks to the monthly order calendar.

Conclusion This inventory management method has enabled our domestic pharmacy to reduce the cost of holding stock, limit the number of stockouts at the pharmacy and reduce the overall cost of placing orders. It would be interesting to complete this study by accounting for the reduction in billing time resulting from the reduction in the number of invoices.

Reference and/or acknowledgements

1. Jurado L, et al. Stock management in hospital pharmacy using chance-constrained model predictive control. Comput Biol Med 2016;72:248–55.

Reference and/or acknowledgementsNo conflict of interest.