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Year : 2019  |  Volume : 8  |  Issue : 1  |  Page : 117

Using discrete choice model to elicit preference for health-care priority setting

1 Department of Health Economics, School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran
2 Health Management and Economics Research Center, Iran University of Medical Sciences, Tehran, Iran
3 Department of Biostatistics, School of Public Health, Iran University of Medical Sciences, Tehran, Iran
4 Department of Economics, Faculty of Economics, University of Tehran, Tehran, Iran

Correspondence Address:
Dr. Mohammad Hadiyan
Building of Health Management and Information Sciences in Front of Khatam Al-Nabia Hospital, Rashid Yasemi Ave., Above Vanak Sq., Valiasr, Tehran
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/jehp.jehp_404_18

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BACKGROUND: Regarding lack of resources in the health-care sector, prioritization of these resources is inevitable. The objective of the current study was to elicit public preference in prioritizing and allocating health resources using a discrete choice experiment technique, which is currently the most commonly applied method in this field of researches. METHODS: In this discrete choice study, five attributes were selected through interview with 25 health experts to elicit people preferences in Tehran (Iran) in 2017. Eighteen choice tasks were arranged within 3 blocks, and this would be achieved with a sample size of 579. Choice data were modeled using generalized estimating equation method and STATA 14 software. RESULTS: Five attributes including level of emergency, severity of disease, communicable, benefit from treatment, and age are the most important attributes in the prioritizing health resources from the expert's point of view. As well as among these attributes, communicable (odds ratio = 2.81) is the most important attributes from the public's point of view. CONCLUSION: The results of this study could be very useful for prioritizing resources which is one of the most challenging measurements of the health system. By identifying the importance of each patient's characteristic, patients can be categorized in groups with different priorities, as well as the diagnosis-related group system, based on which resources are allocated.

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