Eliciting the public preferences for pharmaceutical subsidy in Iran: a discrete choice experiment study

Abstract

Abstract Background Deciding on pharmaceutical subsidy is regarded as a challenging issue for healthcare policymakers in Iran in most times. Public preferences, rarely attended in Iran, could be invaluable for including a particular drug in the list of subsidized medications. Objectives The current study aims to elicit the public preferences to develop an evidence-based decision-making framework for entering a drug into the list of subsidies in Iran. Methods Discrete Choice Experiment (DCE) was employed to elicit the public preferences. Around 34 attributes were identified based on the systematic review and interview with 51 experts. By holding an expert panel, 7 attributes were finalized, namely: the survival after treatment, quality of life after treatment (QoL), alternative treatment, age group of the target population, cost burden for the government, disease severity, and drug manufacturer country. Next, 1224 households were selected for the survey in the city of Tehran, using random cluster sampling. Data were analyzed using conditional logit model. Results The survival after treatment (β = 1.245; SE = 0.053) and cost burden for the government (β = − 0.140; SE = 0.050) had the highest and lowest priority, respectively, in the preferences for allocating subsidy to a drug. In developed region, unlike the other two regions, the level of domestic drug production (β =− 0.302; SE = 0.073) was inversely associated with preferences toward allocating subsidy to a drug. In contrast to other districts, those living in district number one (β = 2.053; SE = 0.138) gave the highest value to promoting the QoL after treatment. Conclusions It is suggested that policymakers pay more attention to attributes such as effectiveness and alternative treatment when developing an evidence-based framework for entering a drug into the list of subsidies. This study highlighted the public belief in the government’s subsidy for medicines, provided that, this results in an increased survival and QoL.