Reduction of Drug Inventory Value Using Theory of Normal Probability Distribution for Demand Forecasting

Abstract

Background: Keeping drug inventory at an appropriate level can ensure the efficient budget management. This study uses the Normal Probability Distribution theory to forecast drug demand, which is expected to be more accurate than the current practice using the Moving Average Method.

Objectives: To increase the efficiency of drug inventory management by reducing the inventory value and reserve rate.

Methods: Quantitative predictive research was performed. The study was divided into two phases. Phase 1: Derivation Phase, collecting data on the drug use rate of Group A drugs using the ABC analysis method in fiscal year 2023. The average drug use rate per week and the standard deviation were analyzed. The theory of normal probability distribution was used to forecast demand to determine the re-order points, the re-order quantity and to adjust the drug use trends allowance quantity. Phase 2: Testing Phase, using the new information obtained, to implement the drug procurement from January to June 2024. The drug inventory value and stock reserve rate were compared with the previous data in the same month of 2023.

Results: After the implementation, the value of drug inventory was reduced by 13.11 million baht (23.34%), and the inventory reserve rate decreased by 22 days (31.43%), leading to reduce the number of inventory reserve days remaining at only 48 days.

Conclusion: Demand forecasting using the theory of normal probability distribution could reduce the value of drug inventory and stock reserve rate without affecting the availability of drug stocks.