Minimizing Cost of Controlled Narcotics Drugs Consumption using Predictive Modelling
Journal of Population Therapeutics and Clinical Pharmacology · 2023
The prediction of controlled narcotic drugs consumption for cost minimization is a complex task that requires the use of multiple data sources and statistical techniques.In the pharmaceutical industry, forecasting is important since it informs drug procurement, budgeting, supply chain, and logistics planning.The pharmaceutical supply chain is characterized by high complexity and uncertainty, which are viewed as fundamental impediments to increasing pharmaceutical supply chain performance.Furthermore, the volatility of the international drug market and changes in drug prices, the country's economic situation, and unexpected supplier practices make it difficult for hospitals and pharmacies to obtain drugs.This study highlights the potential of using predictive modeling to optimize controlled narcotic drugs consumption and reduce costs.The objective of this research is to identify the optimal forecasting technique to improve forecasting accuracy while minimizing cost.A case study with five samples of controlled medicines (Narcotic drugs) been presented applying simple moving average, exponential smoothing, double exponential smoothing, and simple Linear Regression Model.In error measurement metrics, Mean Absolute Deviation, Mean Absolute Percentage Error, Root Mean Square Error, and Tracking Signal.The study recommends combining minimum cost with error measurement metrics to decide which forecasting method should be used.Future research in this area could focus on developing more sophisticated predictive models that incorporate a wider range of data sources and consider the complex interplay between various factors that influence drug usage.