Objectives: The principal aim of this study was to illustrate applying discrete-choice methods for eliciting preferences for technology adoption criteria, including threshold values for cost-effectiveness ratios. A secondary objective was to compare the criteria weights of a sample of industry stakeholders with the results obtained from a study of National Institute for Health and Clinical Excellence (NICE) recommendations.
Methods: We administered a two-stage stated-preference (SP) question format to a sample of respondents who have expertise in applying economic analysis to technology adoption decisions. We elicited paired comparisons and recommendation judgments for similar criteria from a sample of International Society for Pharmacoeconomics and Outcomes Research members. Respondents evaluated nine pairs of hypothetical drugs, first indicating which drug was "better," then indicating what they would recommend to a reimbursement authority such as the National Health Service. Stated-choice studies often obtain only paired-comparison judgments.
Results: Parameter estimates from the initial paired-comparison question indicate only incremental cost-effectiveness ratio and number of affected patients influence evaluations. These two factors have identical weights in the second recommendation question, but all four factors were considered in determining the recommendation threshold. Our sample was more willing than NICE to accept trade-offs between cost-effectiveness and other drug features and was less concerned about cost-effectiveness ratios and information uncertainty. Nevertheless, our sample was in agreement with NICE about the importance of the number of patients who would benefit as a criterion for influencing adoption recommendations.
Conclusion: This study demonstrates that including a question allowing respondents the opportunity to reject both alternatives in a forced-choice paired comparison can be important for obtaining accurate preference estimates. Our results demonstrate that SP methods offer a feasible means of quantifying a broad set of valuations that incorporate the preferences of patient, citizen, payer, and other stakeholder groups.