Open Access Research Article

The Application of Artificial Intelligence in Decision-Making and Sensitivity Analysis for Predicting Shortages of Pharmaceuticals and Medical Equipment During Health Crises

Authors

  • Maryam Ghandehari * Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.
  • Seyed Esmaeil Najafi Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.
  • Seyed Ahmad Edalatpanah Department of Industrial Engineering, Ayandegan Institute of Higher Education, Tonokabon, Iran.

https://doi.org/10.22105/ahse.v2i2.35

Abstract

This study investigates the application of Artificial Intelligence (AI) and sensitivity analysis in predicting shortages of pharmaceuticals and medical equipment during health crises. The primary issue addressed in the research is the shortage of drug and medical equipment resources during crises, which can have a significant negative impact on hospital efficiency and mortality rates. This research aimed to develop an AI-based prediction model for simulating and forecasting resource shortages in crises, as well as to perform sensitivity analysis to identify factors affecting the accuracy of predictions. The research methodology employed AI models, including neural networks and linear regression, to predict shortages of pharmaceuticals and medical equipment. Additionally, sensitivity analysis was used to simulate various crisis scenarios. The findings revealed that factors such as transportation disruptions, demand fluctuations, and seasonal changes have a significant impact on the accuracy of predictions. The results of this study suggest that AI models and sensitivity analysis can effectively assist in improving the prediction and management of pharmaceutical and medical equipment resources during health crises.

Keywords

Artificial intelligence Drug shortage prediction Sensitivity analysis Health crises Decision-making models
References (29)
  1. [1] Filip, R., Gheorghita Puscaselu, R., Anchidin-Norocel, L., Dimian, M., & Savage, W. K. (2022). Global challenges to public health care systems during the COVID-19 pandemic: A review of pandemic measures and problems. Journal of personalized medicine, 12(8), 1295. https://doi.org/10.3390/jpm12081295

  2. [2] Cohen, J., & van der Meulen Rodgers, Y. (2020). Contributing factors to personal protective equipment shortages during the COVID-19 pandemic. Preventive medicine, 141, 106263. https://doi.org/10.1016/j.ypmed.2020.106263

  3. [3] 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 disease 2019 (COVID-19). Transportation research part e: Logistics and transportation review, 138, 101967. https://doi.org/10.1016/j.tre.2020.101967

  4. [4] Banji, A. F., Adekola, A. D., & Dada, S. A. (2024). Supply chain innovations to prevent pharmaceutical shortages during public health emergencies. International journal of engineering research and development, 20(11), 1242–1249. chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://ijerd.com/paper/vol20-issue11/201112421249.pdf

  5. [5] Rosenthal, U., & Kouzmin, A. (1997). Crises and crisis management: Toward comprehensive government decision making. Journal of public administration research and theory, 7(2), 277–304. https://doi.org/10.1093/oxfordjournals.jpart.a024349

Article Metrics

How to Cite

Ghandehari, M. ., Najafi, S. E. ., & Edalatpanah, S. A. . (2025). The Application of Artificial Intelligence in Decision-Making and Sensitivity Analysis for Predicting Shortages of Pharmaceuticals and Medical Equipment During Health Crises. Annals of Healthcare Systems Engineering, 2(2), 76-86. https://doi.org/10.22105/ahse.v2i2.35

Similar Articles

1-10 of 53

You may also start an advanced similarity search for this article.