Optimizing inventory management for specialized medications: a case study of Thammasat University Hospital

This study developed and applied a continuous-review inventory model (EOQ–ROP–SS) to improve management of specialized pharmaceuticals at Thammasat University Hospital. The model was implemented in a spreadsheet and used historical transaction records to estimate demand parameters, compute optimal order quantities, safety stock, and reorder points, and simulate daily inventory under a fixed lead-time assumption. A 95% service level was used so observed shortages reflect the statistical allowance rather than model failure. The model was tested on three representative high-cost items with differing demand and lead-time characteristics. Compared with current hospital practice, the EOQ policy systematically reduced total annual inventory cost across the tested items while maintaining shortage incidence within the predefined service-level tolerance. The results conformed to inventory theory: average inventory declined, ordering frequency increased, and overall cost savings were achieved. The study delivers a practical decision-support spreadsheet, an implementation roadmap for hospital procurement, and recommendations for phased adoption and further research on lead-time variability and explicit shortage valuation.