Date Published: February 1, 2019
Publisher: Public Library of Science
Author(s): Alireza Mahboub-Ahari, Abolghasem Pourreza, Ali Akbari Sari, Trevor A. Sheldon, Maryam Moeeni, Valerio Capraro.
Despite the recent increase in economic evaluations of health care programs in low and middle income countries, there is still a surprising gap in evidence on the appropriate discount rate and the discounting of health outcomes such as quality adjusted life years (QALYs). Our study aimed to calculate the implied time preference rate for health outcomes in Iran and its key determinants. Data were gathered from one family member from each of the 650 households randomly selected in Tehran. The respondents’ private and social preferences for health outcomes were calculated using the time trade-off (TTO) technique based on the discounted utility model. We investigated the main assumptions of the discounted utility model through equality of mean comparison, and the association between private time preference and key socio-economic determinants using multilevel regression analysis. The mean and median implied rates were 5.8% and 4.9% for private time preference and 25.6% and 20% for social time preference respectively. Our study confirmed that magnitude, framing and time effects have a significant impact on implied discount rates, which means that the conventional discounted utility model’s main assumptions are violated in the Iranian general population. Other models of discounting which apply lower rates for far health outcomes might provide a more sensible solution to discounting health interventions with long-term impacts.
The choice of discount rate as well as the practice of discounting health outcomes influences the decision-making process when informed by an economic evaluation [1, 2]. Despite the relative abundance of published studies about discount rate estimation and discounting practice in high income countries (HICs),  there is a significant paucity of literature in this regard in low and middle income countries (LMICs), particularly with respect to health outcomes. However, growing attention has been paid to social preferences and investment cases. For example studies have found that people in India are in general more likely than Americans to be classified as spiteful and less likely to be classified as altruistic, cooperative and socially efficient than US residents [4–6]. The choice of appropriate discount rates for LMICs is particularly challenging due to greater market imperfections, varying inter-generational weighting and values, political instability and cultural factors [7, 8].
We conducted a cross sectional structured interview survey during 2014–2015 with a random sample of general population in the capital city of Tehran (the most populous city of Iran, with a population of 8.8 million), using a stratified multistage cluster sampling design. We classified 21 municipal districts of the city into five social classes reported as: high, upper-middle, middle, lower-middle and low. Each of these classes represented a sampling stratum covering several districts with similar socio-economic characteristics. In the first stage, one district was selected from each stratum (five in total) through a simple random selection. In the second stage, the identity code and postal address of all the dwellings in each selected district were acquired from the Statistical Center of Iran, and 130 households were systematically drawn from each district. Finally, one family member aged over 18 who was able to respond to the questions from each of the 650 households, was selected as study participant. In order to increase sample representativeness, age and gender of the respondents were adjusted according to their distribution in the target population.
There was an overall 93% response rate, which varied by question; a total of 606 completed questionnaires were analyzed. The age and gender distribution in the study samples was similar to that of the whole population, according to the last census of the Iranian households in 2011. Characteristics of the sample are summarized in Table 3.
This population-based study is the first in Iran to estimate time preference rates for private and social health outcomes. All private rates pertain to loss scenarios but social rates pertain to both loss and gain scenarios. We used a stated preference approach, the mean time preference rates for all the questions were calculated by using common discount function. In order to test the main assumptions of the discounted utility model, we used the mean comparison test for different magnitudes and time delays. The key influential factors affecting private time preferences were examined using a multilevel regression analysis, in which two ill health states (losses), wide range of delay (2–13 years), and two start points were adopted to facilitate the experiment.
Our study confirmed that the main assumptions of the conventional discounted utility model were violated. Other models of discounting, which apply lower rates for far health outcomes, might provide a more sensible solution to discounting health interventions with long-term impacts. The Health Technology Assessment, Standardization and Tariffs Office at the Iranian Ministry of Health needs to officially announce its policies about appropriate discount rate and discounting practice, as many studies conducted in the Iranian context need discounting as one of the main parts of their analyses.