In this research, a pharmacy inventory consolidation model has been studied in a multi-hospital system setting. The objectives of this model are to reduce inventory levels, enhance systematic control over arbitrary demands, and eventually improve patient satisfaction. Optimal inventory levels for pharmaceutical items have been analyzed at different hospital pharmacies and nursing units under different inventory models (i.e., decentralized or centralized inventory model). The degree of pharmacy inventory consolidation has also been discussed in this research based on various cost criteria, demand patterns, and dimensions of hospitals. A Multi-echelon Newsvendor Inventory Model (MNIM) is applied to compare decentralized and centralized inventory distribution models. A greedy heuristic algorithm is developed to find optimal hospital pharmacy inventory levels and central inventory level. The experimental results indicate that a centralized hospital inventory distribution system leads to a lower total inventory cost while maintaining the desired quality of care. It is also noticed that the percentage of cost savings in a pharmacy consolidation model is positively correlated with coefficient of demand variation and the degree of consolidations. The validity and impacts of the pharmacy inventory consolidation model are illustrated through a case study with the support from a major U.S. hospital in the state of New Jersey.