A Quantitative Analysis of Inventory Optimization Practices in the Hospital Sector

Efficient inventory management plays a pivotal role in the healthcare sector, influencing both cost efficiency and quality of patient care. This study presents a comprehensive quantitative analysis of inventory optimization practices across public and private hospitals using structured primary data. A total of 38 hospital staff members, including pharmacists, inventory managers, and store in-charges, participated in a structured questionnaire survey conducted in Gautam Buddh Nagar, Uttar Pradesh, India. The data were analyzed using descriptive statistics and correlation analysis through IBM SPSS to evaluate stock-out rates, expiry losses, holding costs, procurement frequency, and adoption of inventory control techniques. Key findings reveal that public hospitals reported higher stock-out rates and holding costs compared to private hospitals. Hospitals with fully automated systems consistently performed better, showing lower expiry losses and more efficient inventory control. Among inventory techniques, FIFO/FEFO and ABC/VED analysis were more widely used, whereas advanced models like EOQ and JIT had lower adoption rates. Additionally, the correlation between stock-out and expiry loss was weak, indicating the need for distinct mitigation strategies. This study fills a notable gap in existing literature by offering empirical, multi-institutional insights into realworld hospital inventory practices through primary data. The findings underscore the importance of digital integration, staff training, and structured methodologies to improve inventory performance, reduce waste, and ensure critical supply availability in healthcare institutions.