Insights from Triangulation of Two Purchase Choice Elicitation Methods to Predict Social Decision Making in Healthcare
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Background: Discrete choice experiments (DCEs) and the Juster scale are accepted methods for the prediction of individual purchase probabilities. Nevertheless, these methods have seldom been applied to a social decision-making context. Objective: To gain an overview of social decisions for a decision-making population through data triangulation, these two methods were used to understand purchase probability in a social decision-making context. Methods: We report an exploratory social decision-making study of pharmaceutical subsidy in Australia. A DCE and selected Juster scale profiles were presented to current and past members of the Australian Pharmaceutical Benefits Advisory Committee and its Economic Subcommittee. Results: Across 66 observations derived from 11 respondents for 6 different pharmaceutical profiles, there was a small overall median difference of 0.024 in the predicted probability of public subsidy (p?=?0.003), with the Juster scale predicting the higher likelihood. While consistency was observed at the extremes of the probability scale, the funding probability differed over the mid-range of profiles. There was larger variability in the DCE than Juster predictions within each individual respondent, suggesting the DCE is better able to discriminate between profiles. However, large variation was observed between individuals in the Juster scale but not DCE predictions. Conclusions: It is important to use multiple methods to obtain a complete picture of the probability of purchase or public subsidy in a social decision-making context until further research can elaborate on our findings. This exploratory analysis supports the suggestion that the mixed logit model, which was used for the DCE analysis, may fail to adequately account for preference heterogeneity in some contexts.
Applied Health Economics and Health Policy
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Medical and Health Sciences not elsewhere classified