Eliciting Preferences for Health Insurance in Iran Using Discrete Choice Experiment Analysis Publisher Pubmed



Karyani AK^{1, 2} ; Sari AA² ; Woldemichael A^{2, 3}
Source: International Journal of Health Policy and Management Published:2019

Abstract

Background: The preferences of Iranians concerning the attributes of health insurance benefit packages are not well studied. This study aimed to elicit health insurance preferences among insured people in Iran during 2016. Methods: A mixed methods study using a discrete choice experiment (DCE) approach was conducted to elicit health insurance preferences on a total sample of 600 insured Iranians residing in Tehran. The final design of the DCE included 8 health insurance attributes. Data were analyzed using conditional logistic regression models. Results: The final model of this DCE study included 8 attributes, and the findings indicated statistically significant (P <.001) increase in the odds ratio (OR) of choosing health insurance at all levels of cost coverage except for the rehabilitation and para-clinical benefits, where at 70% cost coverage there was insignificant (P =.485) disutility (OR = 0.95). With the increase in cost coverage level, the probability of choosing health insurance was significantly (P <.001) the highest for the private hospitals’ benefits (OR = 2.82) followed by public hospitals’ benefits (OR = 2.02) and outpatient benefits (OR = 1.75), and the premium revealed statistically significant (P <.001) disutility (OR = 0.96). Conclusion: Our findings revealed that participants would be willing to choose health insurance plans with higher cost coverage of healthcare services and with lower premiums. However, the demographic characteristics, income, and health status of the insured individuals affected their health insurance preferences. The findings can contribute to the design of better health insurance policies, improve the participation of individuals in health insurance, and increase the insured individuals’ utility from the insurance benefits packages. © 2019 The Author(s); Published by Kerman University of Medical Sciences.