Health Technology Assessment in Action (Apr 2022)

Simulation of Supply Chain Resilience Model of the Pharmaceutical Industry in the Country in the Supply of Remdesivir Using System Dynamics Approach

  • Yousef Nooshiravani,
  • Qasem Ali Bazai,
  • Mansoureh Aligholi

DOI
https://doi.org/10.18502/htaa.v5i3.9352
Journal volume & issue
Vol. 5, no. 3

Abstract

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Background: In the event of a crisis and epidemic of an infectious disease, ensuring the proper and timely supply of necessary medicine is one of the main priorities of the health care system in any country. Therefore, the present study investigates the resilience of the Iranian medicine supply chain using the system dynamics simulation method in increasing the level of access to Remdesivir. Methods and Materials: This is a development-applied study to provide a model using the system dynamics approach, which first presents a rich image that is the based on the model, and then cause-effect models appropriate to the observations made. It was structured on the behavior of the system and also inspired by valid theories. The effect of key factors affecting the supply chain resilience of the country's pharmaceutical industry was designed and analyzed using a system dynamics approach using decision support system (DSS) Vensim software. The time horizon considered for this research was a 5-year period from 2019 to 2023. In order to predict and simulate the system dynamics model, the data collected from the questionnaires and the interviews with experts in this field were used. Results: Based on the scenarios presented in this study, it can be expected that by reducing the schedule pressure by 1 and 3% during the time of the study, the resilience of the supply chain of Remedesvir in the country upgraded to about 32% and 47%. Conclusion: According to the complexity of health care systems, it is difficult to recognize the interaction of different variables, therefore the effect of interventions is not immediately recognizable and requires the passage of time. In addition, majority of the factors influencing health care outcomes are nonlinear. Therefore, the use of simulation models can help to clarify the indirect behavior of complex health care problems.

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