Volume 4, Issue 4 (12-2020)
EBHPME 2020, 4(4): 212-216 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Arman H, Mohamadi E, Mobinizadeh M. A Model for Determining the Number of Health Technologies in the Health Systems: An Approach Combining Multiple Attributes Decision Making and Goal Programming. EBHPME 2020; 4 (4) :212-216
URL: http://jebhpme.ssu.ac.ir/article-1-301-en.html
URL: http://jebhpme.ssu.ac.ir/article-1-301-en.html
National Institute for Health Research, Tehran University of Medical Sciences, Tehran, Iran , mr.mobini1986@gmail.com
Abstract: (1986 Views)
In recent years, health technology policy-making science has gone beyond just a health technology assessment or systematic review or economic evaluation study and the science of operational research in decision making, i.e. multi-attributes and multi-objective decision-making has been included. Hence, currently, health technology policy-making follows a seven-step process. After a technology undergoes these steps and is proven that it is useful for the health system, it must be determined how many of it is needed in the health system. Determining the required number of health technologies is a challenge that remains to be considered. Therefore, this study
was designed to overcome this problem. The authors intend to introduce a multi-objective decision-making methodology considering the limited budget, to determine the number of technologies required to complete for the health technology policymaking cycle.
was designed to overcome this problem. The authors intend to introduce a multi-objective decision-making methodology considering the limited budget, to determine the number of technologies required to complete for the health technology policymaking cycle.
Type of Study: Applicable |
Subject:
Health Policy
Received: 2020/07/11 | Accepted: 2020/12/20 | Published: 2020/12/20
Received: 2020/07/11 | Accepted: 2020/12/20 | Published: 2020/12/20
References
1. Sabik LM, Lie RK. Priority setting in health care: Lessons from the experiences of eight countries. International Journal for Equity in Health. 2008; 7(1): 4. [DOI:10.1186/1475-9276-7-4]
2. Harris C, Allen K, King R, Ramsey W, Kelly C, Thiagarajan M. Sustainability in Health care by Allocating Resources Effectively (SHARE) 2: Identifying opportunities for disinvestment in a local healthcare setting. BMC Health Services Research. 2017; 17(1): 328. [DOI:10.1186/s12913-017-2211-6]
3. Ghijben P, Gu Y, Lancsar E, Zavarsek S. Revealed and stated preferences of decision makers for priority setting in health technology assessment: a systematic review. Pharmaco Economics. 2018; 36(3): 323-40. [DOI:10.1007/s40273-017-0586-1]
4. Mohamadi E, Tabatabaei SM, Olyaeemanesh A, Sagha SF, Zanganeh M, Davari M, et al. Coverage Decision-Making for Orthopedics Interventions in the Health Transformation Program in Iran: A Multiple Criteria Decision Analysis (MCDA). Shiraz E-Medical Journal. 2016; 17(12): 1-9. doi: 10.17795/semj40920. [DOI:10.17795/semj40920]
5. Dehnavieh R, Rahimi H. Basic health insurance package in Iran: revision challenges. Iranian Journal of Public Health. 2017; 46(5): 719-20.
6. Sari AA, Ravaghi H, Mobinizadeh M, Sarvari S. The cost-utility analysis of PET-scan in diagnosis and treatment of non-small cell lung carcinoma in Iran. Iranian Journal of Radiology. 2013; 10(2): 61. [DOI:10.5812/iranjradiol.8559]
7. Mitton C, Seixas BV, Peacock S, Burgess M, Bryan S. Health Technology Assessment as Part of a Broader Process for Priority Setting and Resource Allocation. Applied Health Economics and Health Policy. 2019: 17(5): 573-6. doi: 10. 1007/ s40258-019-00488-1. [DOI:10.1007/s40258-019-00488-1]
8. Kazimieras Zavadskas E, Antucheviciene J, Kar S. Multi-Objective and Multi- Attribute Optimization for Sustainable Development Decision Aiding. 2019. [DOI:10.3390/su11113069]
9. Oortwijn W, Jansen M, Baltussen R. Evidence-informed deliberative processes. A practical guide for HTA agencies to enhance legitimate decision-making. Version 1.0. Nijmegen, Radboud university medical centre, Radboud Institute for Health Sciences, 2019.
10. Husereau D, Boucher M, Noorani H. Priority setting for health technology assessment at CADTH. Int J Technol Assess Health Care. 2010; 26(3): 341-7. doi:10.1017/ S0266462310000383. [DOI:10.1017/S0266462310000383]
11. Baltussen R, Marsh K, Thokala P, Diaby V, Castro H, Cleemput I, et al. Multicriteria decision analysis to support health technology assessment agencies: benefits, limitations, and the way forward. Value in Health. 2019; 22(11): 1283-8. [DOI:10.1016/j.jval.2019.06.014]
Send email to the article author
| Rights and permissions | |
 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
