Application of discrete choice experiments to estimate value of life: a national study protocol in Iran

• Main Authors: Negar Mirzaee, Amirhossein Takian, Farshad Farzadfar, Rajabali Daroudi, Ali Kazemi Karyani, Ali Akbari Sari
• Format: Article
• Language: English
• Published: BMC 2021-01-01
• Series: Cost Effectiveness and Resource Allocation
• Online Access: https://doi.org/10.1186/s12962-021-00259-7

Abstract Background Global concerns regarding the significant burden of non-communicable diseases and injuries (NCDIs) exist from both public health and economic perspectives. Our research focuses on the reduction of fatal risks due to NCDIs and the citizens’ preferences about health programs and intervention to reduce premature death due to NCDIs. Governments and health authorities need reliable evidence and information to prioritize the interests of their citizens. One crucial piece of evidence to justify the resources spent on NCDIs is the value derived from the interventions on prevention and NCDIs control. This concept is usually called “Value of Statistical Life” (VSL), meaning the monetary value that individuals place on changes in the risk levels of life- threatening events. To the best of our knowledge, for the first time, our study will estimate the statistical value of life for selected interventions for the prevention and control of NCDIs at both national and sub-national levels in the context of Iran. This paper reports the development of a national protocol through Discrete Choice Experiments (DCEs) method. Methods and designs Our study comprises several stages: (a) a literature review to identify the attributes and levels of the prevention programs and Willingness to Pay (WTP) for reducing the NCDI’s fatal risks; (b) experimental design to assessing, prioritizing, and finalizing the identified attributes and levels; (c) instrumental design to conduct face-to-face structured survey interviews of 3180 respondents aged 18–69 across the entire country; (d) statistical analysis to estimate the results through the Mixed Multinomial logit (MMNL) model. Discussion We anticipate that our findings will help build a stronger empirical basis for monetizing the value of small changes in selected fatality risks. It paves the way for other national or vast VSL estimates for NCDIs, as well as other major causes of morbidity and mortality in the context of Iran, and perhaps other low and middle-income countries (LMICs).