Pharmaceutical Supply Chain Optimization in Healthcare: Insights from Recent Literature
DOI:
https://doi.org/10.55642/phasij.v5i01.1115Kata Kunci:
pharmaceutical supply chain, healthcare, optimization, digital technology, resilience, systematic literature reviewAbstrak
This study aims to review and synthesize recent literature on the optimization of pharmaceutical supply chains in the healthcare sector. Using a Systematic Literature Review (SLR) approach based on PRISMA guidelines, six peer-reviewed articles published between 2020 and 2025 were analyzed in depth. The findings reveal that optimization models such as Mixed Integer Linear Programming (MILP), and the integration of digital technologies—including Artificial Intelligence (AI), blockchain, and the Internet of Things (IoT)—have significantly improved operational efficiency, transparency, and resilience in pharmaceutical logistics. Additionally, lean-digital strategies and resilience-oriented approaches such as supplier diversification and scenario planning have proven effective in addressing supply chain disruptions. The study also highlights research gaps in real-world implementation and calls for the development of integrated frameworks that are adaptive to the dynamics of global healthcare systems. These findings provide strategic insights for practitioners and researchers aiming to design robust and sustainable pharmaceutical supply chains.
Referensi
Aung, M. M., & Chang, Y. S. (2021). A review of digital technologies and sustainable supply chain management in the pharmaceutical industry. Journal of Cleaner Production, 296, 126630. https://doi.org/10.1016/j.jclepro.2021.126630
Bag, S., Wood, L. C., Xu, L., & Dhamija, P. (2021). Big data analytics as an operational excellence approach to enhance sustainable supply chain performance. Resources, Conservation and Recycling, 164, 105119. https://doi.org/10.1016/j.resconrec.2020.105119
Govindan, K., Mina, H., & Alavi, B. (2020). A decision support system for demand management in healthcare supply chains considering the epidemic outbreaks: A case study of coronavirus (COVID-19). Transportation Research Part E: Logistics and Transportation Review, 138, 101967. https://doi.org/10.1016/j.tre.2020.101967
Kamble, S. S., Gunasekaran, A., & Dhone, N. C. (2020). Industry 4.0 and lean manufacturing practices for sustainable organizational performance in Indian manufacturing companies. International Journal of Production Research, 58(5), 1319–1337. https://doi.org/10.1080/00207543.2019.1660826
Kumar, A., & Goudar, R. H. (2020). Supply chain management in pharmaceutical industry: An insight into optimization models. Materials Today: Proceedings, 33, 4704–4708. https://doi.org/10.1016/j.matpr.2020.06.154
Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & The PRISMA Group. (2009). Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement. PLoS Medicine, 6(7), e1000097. https://doi.org/10.1371/journal.pmed.1000097
Patel, R., Sharma, A., & Agarwal, S. (2023). AI-powered predictive analytics for pharmaceutical inventory optimization: A post-pandemic perspective. Computers & Industrial Engineering, 179, 109100. https://doi.org/10.1016/j.cie.2023.109100
Torabi, S. A., Soufi, H. R., & Sahebjamnia, N. (2021). A novel integrated approach for resilient pharmaceutical supply chain network design under uncertainty. Omega, 101, 102263. https://doi.org/10.1016/j.omega.2020.102263
