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Purpose This study aims to identify empirically proven strategies for reducing healthcare supply chain inventory costs. Design/methodology/approach The author conducted in-depth interviews in 80 hospitals covering different supply chains. The author treated the healthcare firm as the unit of analysis and examined Vrat's taxonomy of inventory models based on the static and dynamic complexity theories of inventory models to identify an appropriate approach. The author addressed 33 highly priced and moderately priced stock-keeping units from 1,432 items and test several inventory policies. Next, the author applied combinations of inventory models, testing probabilistic hybrid inventory models. Findings The study finds that medical supplies, equipment, and medications are indispensable for a quality healthcare system. Hence, healthcare supply chain management (SCM) professionals must adopt basic inventory cost-reduction strategies, implementing inventory software functionalities effectively and efficiently. This study shows that probabilistic hybrid inventory techniques in healthcare SCM effectively determine an optimal stocking level, significantly reducing costs. Research limitations/implications This study analyzes data from primary care and (to some extent) secondary care institutions. Although tertiary and quaternary care systems do not represent a large portion of the healthcare system, future research should also address these highly specialized organizations' needs. Practical implications This study proposes practical strategies to help continuously improve supply chain operations in healthcare organizations worldwide. Originality/value This study suggests probabilistic hybrid inventory models as empirically proven solutions for evaluating stock-keeping units in the healthcare sector. In doing so, the study provides a new healthcare supply chain approach, proposing a modified taxonomy of inventory models.
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