Simulation of Supply Chain Resilience Model of the Pharmaceutical Industry in the Country in the Supply of Remdesivir Using System Dynamics Approach
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Abstract
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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14. Faezipour M, Ferreira S. A System Dynamics Approach for Sustainable Water Management in Hospitals. IEEE Systems Journal. 2018;12:1278-85.
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18. Homer JB, Hirsch GB. System dynamics modeling for public health: background and opportunities. Am J Public Health. 2006;96(3):452-8.
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25. Tirivangani T, Alpo B, Kibuule D, Gaeseb J, Adenuga BA. Impact of COVID-19 pandemic on pharmaceutical systems and supply chain - a phenomenological study. Explor Res Clin Soc Pharm. 2021;2:100037.
26. Sedighpour A, Zandieh M, Alem Tabriz A, Dori B. Resilient Supply Chain Model in Iran Pharmaceutical Industries. Ind Manag Stud. 2018;16(51):55-106.
27. Golan MS, Jernegan LH, Linkov I. Trends and applications of resilience analytics in supply chain modeling: systematic literature review in the context of the COVID-19 pandemic. Environ SystDecis. 2020;40(2):222-43.
28. National Institutes of Health. COVID-19 treatment guidelines: National Institutes of Health; 2021 [Available from: https://www.covid19treatmentguidelines.nih.gov/therapies/antiviral-therapy/remdesivir/.
29. Davahli MR, Karwowski W, Taiar R. A System Dynamics Simulation Applied to Healthcare: A Systematic Review. Int J Environ Res Public Health. 2020;17(16).
30. Heijkoop G, Cunningham S, editors. Using system dynamics for modeling benefit realization in the adoption of new business software. International Conference of the SD Society; 2007: Citeseer.
31. Hekimoğlu M, Barlas Y, Luna-Reyes L. Sensitivity analysis for models with multiple behavior modes: a method based on behavior pattern measures. Syst Dyn Rev. 2016;32(3-4):332-62.
32. Willmott CJ, Matsuura K. Advantages of the mean absolute error (MAE) over the root mean square error (RMSE) in assessing average model performance. Clim Res. 2005;30:79-82.
33. Cagliano R, Caniato F, Spina G. The linkage between supply chain integration and manufacturing improvement programmes. Int J Oper Prod Manag. 2006;26(3):282-99.
34. Mahmoodi E, Naimi SA, Chaharsoughi S, Eskandari H. Impact of information system flow on make-to-order manufacturer supply chain network: systems dynamics approach. J Model Eng.2010;8(22).
35. Sterman JD. Systems dynamics modeling: tools for learning in a complex world. IEEE Eng Manag Rev 2002;30(1):42-.
36. Faezipour M, Ferreira S. A System Dynamics Approach for Sustainable Water Management in Hospitals. IEEE Sys J. 2018;12(2):1278-85.
37. Torbati A, Arsanjany MA, Mehryar Irdimosa H. Creating supply
chain management strategy map with using causal loop diagram and balanced scorecard. J Model Eng. 2015;13(42):15165. 38. Schwaninger M, Groesser S. System Dynamics Modeling: Validation for Quality Assurance. In: Meyers R, editor. Complex Systems in Finance and Econometrics. New York, USA: Springer 2009. p.
767-81.
39. Chowdhury P, Paul SK, Kaisar S, Moktadir MA. COVID-19 pandemic related supply chain studies: A systematic review. Transp Res E Logist Transp Rev. 2021;148:102271.
40. Homer JB, Hirsch GB. System dynamics modeling for public health: background and opportunities. Am J Public Health. 2006;96(3):452-8.
41. Fone D, Hollinghurst S, Temple M, Round A, Lester N, Weightman A, et al. Systematic review of the use and value of computer simulation modelling in population health and health care delivery. J Public Health Med. 2003;25(4):325-35.
42. Tracy M, Cerda M, Keyes KM. Agent-Based Modeling in Public Health: Current Applications and Future Directions. Annu Rev Public Health. 2018;39:77-94.
43. Wang JN, Chiu YL, Yu H, Hsu YT. Understanding a Nonlinear Causal Relationship Between Rewards and Physicians’ Contributions in Online Health Care Communities: Longitudinal Study. J Med Internet Res. 2017;19(12):e427.
44. Papalexi M, Bamford D, Breen L. Key sources of operational inefficiency in the pharmaceutical supply chain. Int J Supply Chain Manag. 2020;25(6):617-35.
1. Miller FA, Young SB, Dobrow M, Shojania KG. Vulnerability of the medical product supply chain: the wake-up call of COVID-19. BMJ Quality & Safety. 2021;30(4):331-5.
2. Jahanbani E, Shakoori R, Bagheri-Kahkesh M. Drug Supply Chain Management and Implementation of Health Reform Plan in Teaching Hospital Pharmacies of Ahvaz, Iran. Hospital Practices and Research. 2016;1(4):141-5.
3. Tirivangani T, Alpo B, Kibuule D, Gaeseb J, Adenuga BA. Impact of COVID-19 pandemic on pharmaceutical systems and supply chain – a phenomenological study. Exploratory Research in Clini-cal and Social Pharmacy. 2021;2:100037.
4. Sedighpour A, Zandieh M, Alem Tabriz A, dori b. Resilient Supply Chain Model in Iran Pharmaceutical Industries. Industrial Management Studies. 2018;16(51):55-106.
5. Golan MS, Jernegan LH, Linkov I. Trends and applications of resilience analytics in supply chain modeling: systematic literature review in the context of the COVID-19 pandemic. Environment Systems and Decisions. 2020;40(2):222-43.
6. (NIH) NIoH. COVID-19 Treatment Guidelines: Remdesivir 2021 [Available from: https://www.covid19treatmentguidelines.nih. gov/therapies/antiviral-therapy/remdesivir/.
7. Davahli MR, Karwowski W, Taiar R. A System Dynamics Simulation Applied to Healthcare: A Systematic Review. International Journal of Environmental Research and Public Health. 2020;17(16):5741.
8. Heijkoop G, Cunningham S. Using System Dynamics for Modeling Benefit Realization in the Adoption of New Business Software. 2007.
9. Hekimoğlu M, Barlas Y. Sensitivity analysis for models with multiple behavior modes: a method based on behavior pattern measures. System Dynamics Review. 2016;32(3-4):332-62. 10. Willmott CJ, Matsuura K. Advantages of the mean absolute error (MAE) over the root mean square error (RMSE) in assessing average model performance. Climate Research. 2005;30(1):79-82.
11. Cagliano R, Caniato F, Spina G. The Linkage Between Supply Chain Integration and Manufacturing Improvement Programmes. International Journal of Operations & Production Management. 2006;26:282-99.
12. MAHMOODI E, NAIMI SADIGH A, CHAHARSOUGHI SK, ESKANDARI H. IMPACT OF INFORMATION SYSTEM FLOW ON MAKE-TOORDER MANUFACTURER SUPPLY CHAIN NETWORK: SYSTEMS DYNAMICS APPROACH. JOURNAL OF MODELING IN ENGINEERING. 2010;8(22):-.
13. Sterman J. System dynamics modeling: Tools for learning in a complex world. Engineering Management Review, IEEE.
2002;43:42-.
14. Faezipour M, Ferreira S. A System Dynamics Approach for Sustainable Water Management in Hospitals. IEEE Systems Journal. 2018;12:1278-85.
15. TORBATI A, ARSANJANY MA, FIROZ SHAHI M. CREATING SUPPLY CHAIN MANAGEMENT STRATEGY MAP WITH USING CAUSAL LOOP DIAGRAM AND BALANCED SCORECARD. JOURNAL OF MODELING IN ENGINEERING. 2015;13(42):-.
16. Schwaninger M, Groesser S. System Dynamics Modeling: Validation for Quality Assurance. In: Meyers RA, editor. Complex Systems in Finance and Econometrics. New York, NY: Springer New York; 2011. p. 767-81.
17. Chowdhury P, Paul SK, Kaisar S, Moktadir MA. COVID-19 pandemic related supply chain studies: A systematic review. Transp Res E Logist Transp Rev. 2021;148:102271.
18. Homer JB, Hirsch GB. System dynamics modeling for public health: background and opportunities. Am J Public Health. 2006;96(3):452-8.
19. Fone D, Hollinghurst S, Temple M, Round A, Lester N, Weightman
A, et al. Systematic review of the use and value of computer simulation modelling in population health and health care delivery. J Public Health Med. 2003;25(4):325-35.
20. Tracy M, Cerda M, Keyes KM. Agent-Based Modeling in Public Health: Current Applications and Future Directions. Annu Rev Public Health. 2018;39:77-94.
21. Wang JN, Chiu YL, Yu H, Hsu YT. Understanding a Nonlinear Causal Relationship Between Rewards and Physicians’ Contributions in Online Health Care Communities: Longitudinal Study. J Med Internet Res. 2017;19(12):e427.
22. Papalexi M, Bamford D, Breen L. Key sources of operational inefficiency in the pharmaceutical supply chain. Supply Chain Management: An International Journal. 2020;25(6):617-35. 23. Miller FA, Young SB, Dobrow M, Shojania KG. Vulnerability of the medical product supply chain: the wake-up call of COVID-19. BMJ
Qual Saf. 2021;30(4):331-5.
24. Shakoori R, Bagheri-Kahkesh M. Drug Supply Chain Management and Implementation of Health Reform Plan in Teaching Hospital Pharmacies of Ahvaz, Iran. Hosp Pract Res. 2016;1(4):141-5.
25. Tirivangani T, Alpo B, Kibuule D, Gaeseb J, Adenuga BA. Impact of COVID-19 pandemic on pharmaceutical systems and supply chain - a phenomenological study. Explor Res Clin Soc Pharm. 2021;2:100037.
26. Sedighpour A, Zandieh M, Alem Tabriz A, Dori B. Resilient Supply Chain Model in Iran Pharmaceutical Industries. Ind Manag Stud. 2018;16(51):55-106.
27. Golan MS, Jernegan LH, Linkov I. Trends and applications of resilience analytics in supply chain modeling: systematic literature review in the context of the COVID-19 pandemic. Environ SystDecis. 2020;40(2):222-43.
28. National Institutes of Health. COVID-19 treatment guidelines: National Institutes of Health; 2021 [Available from: https://www.covid19treatmentguidelines.nih.gov/therapies/antiviral-therapy/remdesivir/.
29. Davahli MR, Karwowski W, Taiar R. A System Dynamics Simulation Applied to Healthcare: A Systematic Review. Int J Environ Res Public Health. 2020;17(16).
30. Heijkoop G, Cunningham S, editors. Using system dynamics for modeling benefit realization in the adoption of new business software. International Conference of the SD Society; 2007: Citeseer.
31. Hekimoğlu M, Barlas Y, Luna-Reyes L. Sensitivity analysis for models with multiple behavior modes: a method based on behavior pattern measures. Syst Dyn Rev. 2016;32(3-4):332-62.
32. Willmott CJ, Matsuura K. Advantages of the mean absolute error (MAE) over the root mean square error (RMSE) in assessing average model performance. Clim Res. 2005;30:79-82.
33. Cagliano R, Caniato F, Spina G. The linkage between supply chain integration and manufacturing improvement programmes. Int J Oper Prod Manag. 2006;26(3):282-99.
34. Mahmoodi E, Naimi SA, Chaharsoughi S, Eskandari H. Impact of information system flow on make-to-order manufacturer supply chain network: systems dynamics approach. J Model Eng.2010;8(22).
35. Sterman JD. Systems dynamics modeling: tools for learning in a complex world. IEEE Eng Manag Rev 2002;30(1):42-.
36. Faezipour M, Ferreira S. A System Dynamics Approach for Sustainable Water Management in Hospitals. IEEE Sys J. 2018;12(2):1278-85.
37. Torbati A, Arsanjany MA, Mehryar Irdimosa H. Creating supply
chain management strategy map with using causal loop diagram and balanced scorecard. J Model Eng. 2015;13(42):15165. 38. Schwaninger M, Groesser S. System Dynamics Modeling: Validation for Quality Assurance. In: Meyers R, editor. Complex Systems in Finance and Econometrics. New York, USA: Springer 2009. p.
767-81.
39. Chowdhury P, Paul SK, Kaisar S, Moktadir MA. COVID-19 pandemic related supply chain studies: A systematic review. Transp Res E Logist Transp Rev. 2021;148:102271.
40. Homer JB, Hirsch GB. System dynamics modeling for public health: background and opportunities. Am J Public Health. 2006;96(3):452-8.
41. Fone D, Hollinghurst S, Temple M, Round A, Lester N, Weightman A, et al. Systematic review of the use and value of computer simulation modelling in population health and health care delivery. J Public Health Med. 2003;25(4):325-35.
42. Tracy M, Cerda M, Keyes KM. Agent-Based Modeling in Public Health: Current Applications and Future Directions. Annu Rev Public Health. 2018;39:77-94.
43. Wang JN, Chiu YL, Yu H, Hsu YT. Understanding a Nonlinear Causal Relationship Between Rewards and Physicians’ Contributions in Online Health Care Communities: Longitudinal Study. J Med Internet Res. 2017;19(12):e427.
44. Papalexi M, Bamford D, Breen L. Key sources of operational inefficiency in the pharmaceutical supply chain. Int J Supply Chain Manag. 2020;25(6):617-35.
| Files | ||
| Issue | Vol 5, No 3 (2021) | |
| Section | Articles | |
| DOI | https://doi.org/10.18502/htaa.v5i3.9352 | |
| Keywords | ||
| Simulation chain resilience pharmaceutical industry Remdesivir resilience system dynamics approach | ||
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How to Cite
1.
Nooshiravani Y, Bazai QA, Aligholi M. Simulation of Supply Chain Resilience Model of the Pharmaceutical Industry in the Country in the Supply of Remdesivir Using System Dynamics Approach. Health Tech Ass Act. 2022;5(3).
