Supply Chain Optimization in Healthcare and Pharmaceutical Management Systems

Abstract

In an increasingly complex and high-demand healthcare environment, the optimization of supply chain systems has emerged as a strategic necessity rather than a supporting function. This study investigates the structural challenges, performance inefficiencies, and potential technological solutions in healthcare and pharmaceutical supply chains, with a particular focus on the Indian context. Employing a mixed-methods approach, data were collected through surveys, interviews, and case studies, complemented by a rigorous review of secondary literature. The findings highlight critical issues such as lack of inventory visibility, poor IT integration, high logistics costs, and ineffective demand forecasting. Comparative performance analysis shows that India's supply chains significantly lag behind global benchmarks. However, the integration of emerging technologies—such as Artificial Intelligence (AI), Blockchain, Internet of Things (IoT), and automation—demonstrates significant improvements in key performance metrics, including stockout reduction, lead time efficiency, operational cost savings, and patient satisfaction. ANOVA analysis confirms the statistical significance of these improvements post-optimization. The study concludes that a data-driven, technology-enabled, and strategically integrated supply chain model can substantially enhance the efficiency, reliability, and responsiveness of healthcare delivery systems.