Authors and affiliation (s):
Sheetal Singh1,*, Himanshu Sharma1, Vijay Aggarwal2
1Department of Hospital Administration, AIIMS, New Delhi, INDIA.
2Director Medical (Medical Administration) Services, Apollo Health and Lifestyle, Hyderabad, Telangana, INDIA.
ABSTRACT
Introduction: Inventory management in hospital stores presents complex challenges, particularly in cancer care settings where high-cost medications and irregular demand patterns exist. Hospital administrators must maintain equilibrium between medication availability and budget constraints. Ineffective inventory practices lead to either stockouts that compromise patient care or overstocking, which results in medication wastage. The study is conducted because of frequent stockouts at the hospital’s medical store. It will identify medications with high costs and high variation, high costs with little variation, and low costs with high variation using ABC and XYX analysis. This will help the institute develop procurement strategies to reduce stockouts and medication waste. Materials and Methods: This cross-sectional, descriptive, retrospective study was conducted at a tertiary care government cancer hospital in North India from March to May 2025. It included 286 medications regularly procured by the hospital’s medical store. The data from July 2023 to June 2024 was analyzed for ABC and XYZ analysis. ABC analysis was conducted based on the Annual Consumption Value (ACV), dividing medications into three groups: Category A (top 70%), B (next 20%), and C (bottom 10%). XYZ analysis classified medicines according to monthly demand variability using the Coefficient of Variation (CV): X (CV<0.5), Y (CV 0.5-1.0), and Z (CV>1.0). Combining both methods created a 3×3 matrix for inventory management. Since the research used anonymized routine stock data, ethical approval was not needed. Data was analyzed using SPSS. Results: The study classified 286 drugs into nine segments based on purchasing value and demand variability to guide procurement planning. ABC analysis showed 29 expensive drugs (10.1%) accounted for 70% of the drug bill (₹8.95 crore of ₹12.71 crore), supporting the Pareto principle. XYZ analysis placed 65 drugs in Class X, 112 in Class Y, and 109 in Class Z. The ABC-XYZ matrix results in an efficient inventory system by integrating demand predictability. The study emphasized dynamic procurement strategies for 45 high and medium-value drugs in AZ, BZ, AY, and BY categories. Limitations included using monthly data that may miss daily variability and the need for multi-centre studies to validate the model. Despite these, ABC-XYZ integration can create efficiencies, reduce stockouts, and minimize wastage. Conclusion: Stable-demand, high-value medications (AX/BX) can be handled through programmed bulk purchasing, while erratic-demand, high-value drugs (AZ/BZ) require dynamic tracking and flexible procurement. Implementing ABC-XYZ techniques can reduce stockouts and wastage, enhancing medication availability and resource utilization. Recommendation: Future projects should propose real-time inventory tracking systems like barcode scanning, RFID, or IoT-based tools to reflect daily demand fluctuations
Keywords: ABC-XYZ Analysis, Inventory Optimization, Pharmaceutical Management, Cancer Care.