Volume 11, Issue 43 (5-2021)                   jemr 2021, 11(43): 207-236 | Back to browse issues page

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Ghasemian N, Raghfar H, Ekhteraei F. Simulation of Demand for Orphan Drugs in Iran with the Approach of Agent-based Modeling (2018-2019). jemr. 2021; 11 (43) :207-236
URL: http://jemr.khu.ac.ir/article-1-2149-en.html
Abstract:   (240 Views)
Drugs as a strategic and subsidized commodity and an urgent need for patients have been constantly of particular importance, specially, in the health-care system of a society. On the other hand, one of the parameters concerning the assessment of the family welfare is the amount spent for satisfaction of divergent needs. The more a family spends on essential necessities such as food, housing, clothing and higher education, the less is expected to be devoted to health care. Concerning drugs, the demand for different drugs may vary depending on the patients' attitudes, the type of illnesses and their income elasticity. The objective of the present research is to investigate the demand for orphan drugs for refractory diseases regarding various income groups in Iran applying Agent-based Models (ABMs). In this research, the behavior dynamics of the orphan drugs applicants and the diversity of their demands in miscellaneous price scenarios resulting from inflation and fluctuations in the exchange rate have been scrutinized in accordance with ABM. To this end, one thousand family applicants for orphan drugs, extracted from Iran's statistics center, were categorized in five different income ventiles. Their reactions towards the increase of the price of the aforementioned drugs are predicted based on Net Logo simulation software. The results indicate that the average of price elasticity of demand for generic and branded drugs has been -0.39 and -0.05 percent, respectively; similarly, the demand for these two drug groups has been decreased by the same amount. In the lowest income ventile as the price of generic and branded orphan drugs deceases, for the lowest income ventile families, the allocated expenses for these drugs has been decreased by 3.3 percent and 31.85 percent, respectively. The main reason for the aforementioned problem is assigned to the low budget of the patients' family and its allocation to essential necessities of life such as food and housing. The severity of the cost reduction in branded drugs is due to the fact that it can be replaced by generic drugs.
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Type of Study: Applicable | Subject: بخش عمومی
Received: 2021/02/17 | Accepted: 2021/06/21 | Published: 2021/09/12

1. Auchincloss, A.H. & Diez Roux, A, V., (2008), A New Tool for Epidemiology: The Usefulness of Dynamic-Agent Models in Understanding Place Effects on Health. American Journal of Epidemiology, 168(1): 1-8. [DOI:10.1093/aje/kwn118]
2. Akbarpour. M, Torabi. A. & Ghavamifar. A., (2020), Designing an Integrated Pharmaceutical Relief Chain Network Under Demand Uncertainty, Transportation Research Part E Journal, 136: 1366-5545. [DOI:10.1016/j.tre.2020.101867]
3. Bayati. M, Ahadinejad. B, Mathematics. F. & Beigi, N., (2018), Estimation of Household Pharmaceutical Expenditure in Iran, Jahad University Scientific Information Center, 17(2) :128-121. (in Persian)
4. Boero.R. (2015), Behavioral Computational Social Science, Los Alamos National Laboratory, New Mexioco, USA. [DOI:10.1002/9781119106173]
5. Chin. A.T., (2010), Consumer Learning and Heterogeneity: Dynamics of Demand for Prescription Drugs after Patent Expiration, International Journal of Industrial Organization, 28(6): 619-638. [DOI:10.1016/j.ijindorg.2010.02.004]
6. Divino. V, DeKoven. M, Kleinrock. M, Wade. R.L & Kaura,S., (2016), Orphan Drug Expenditures In The United States: A Historical And Prospective Analysis 2007-18, Journal of Health Affairs, 35(9). [DOI:10.1377/hlthaff.2016.0030]
7. Dorri. A, Jurdak. R, Kanhere. S., (2018), Multi Agent System: A survey, IEEE journal, 6: 2167-3536. [DOI:10.1109/ACCESS.2018.2831228]
8. Einav, L., Finkelstein, A., & Tebaldi, P., (2018). Market Design in Regulated Health Insurance Markets: Risk Adjustment VS. Subsidies. MIT Working Paper.
9. Emadzadeh. M, Samadpour. N, Ranjbar. H. & Azizi. F., (2013), The Effect of Education on Health in Iran: Production Function Approach, Journal of Economic Modeling Research Kharazmi University, 4(15):147-178. (in Persian)
10. Food and Drug Administration of Iran (IFDA). (in Persian)
11. Hamill. L. & Gilbert. N., (2016), Agent-Based Modeling in Economics, Center for Research in Social Simulation (CRESS), University of Surrey UK. [DOI:10.1002/9781118945520]
12. Hernandez I. C, Gonzales lopez. B, Morris. S, Melnychuk. M & Aba'solo Alesso'n. I., (2019), The Effect of a Change in Co-Payment on Prescription Drug Demand in a National Health System: The Case of 15 Drug Families by Price Elasticity of Demand, PloS One journal, 14(3). [DOI:10.1371/journal.pone.0213403]
13. Hosseini-Jebli. S, Arian-Khasal. A, Baroni. Mohsen, Heidari-Arjloo. P, & Khakian. M., (2013), Estimation of Drug Demand Function for Specific Diseases in Iran through Household Budget, Journal of Health and Development of Kerman University of Medical Sciences, 2 (2) 0-89. (in Persian)
14. Marshal. B, Galea. S., (2015), Formalizing the Role of Agent-Based Modeling in Causal Inference and Epidemiology, American Journalof Epidemiology, 181: 92-99. [DOI:10.1093/aje/kwu274]
15. Meshcheriakova. E, Goodall. S, Street. D, & Viney, R., (2020), PNS55 The Effect of Pharmaceutical Policy on Demand for Branded Medicines: A Discrete Choice Experiment from Australia, Value in Health Regional Issues Journal, 22: 591. [DOI:10.1016/j.vhri.2020.07.474]
16. Mestre Ferrandiz. J, Palaska. Ch, Kelly. T, Hutchings. A & Parnaby. A., (2019), An analysis of orphan medicineexpenditure in Europe, Orphanet Journal of Rare Diseases, 14:287. [DOI:10.1186/s13023-019-1246-7]
17. Models for Medicines through Wireless Sensor Networks Data and Topic Trend Analysis, International Journal of Distributed Sensor Network, No.1.
18. Panahi. H, Sojoudi. S & Marandian, M., (2016), Estimation of Price and Income Elasticities of Drug Import Demand in Iran, Journal of Economic Research, University of Tehran, 51(4): 799-777. (in Persian)
19. Panahi. H, Fallahi. F, Imani. A, & Nasib parast. S., (2018), Investigating The Induced Demand of Psychiatrists in East Azerbaijan Province: A Hierarchical Linear Modeling Approach (HLM), Journal of Economic Modeling Research Kharazmi University, 8(31): 165-196. (in Persian) [DOI:10.29252/jemr.8.31.165]
20. Pharmaceutical Statistics of the Iran., (2017), Food and Drug Administration, Ministry of Health, Treatment and Medical Education. (in Persian)
21. Quintiles IMS Institute., (2017), Orphan Drugs in the United States: Providing Context for Use and Cost.
22. Sobhanian. M.H, MehrAra. M, & Ebadi. J., (2016), Investigating the Effective Components of General Practitioners' Outcome for Entering the Family Physician Plan, Case Study: Tehran, Journal of Economic Modeling Research Kharazmi University, 7(26): 7-40. (in Persian) [DOI:10.18869/acadpub.jemr.7.26.7]

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