Related Experiment Video
Updated: Mar 17, 2026

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
Published on: September 19, 2012
What, who and when? Incorporating a discrete choice experiment into an economic evaluation
Michela Tinelli1, Mandy Ryan2, Christine Bond3
1LSE Health and Social Care, the London School of Economics and Political Science, Houghton Street, London, WC2A 2AE, UK. m.tinelli@lse.ac.uk.
Background:
Economic evaluation focuses on Quality-Adjusted-Life-Years (QALYs) as the main valuation method. However, it is well known that factors beyond health related quality of life are important to patients and the public. Whilst discrete-choice-experiments (DCE) have been extensively used to value such factors, their incorporation within an economic evaluation framework is limited. This study is the first to incorporate patient preferences for factors beyond QALYs into an economic evaluation and compare results with the standard cost-per-QALY approach, using randomised-controlled-trial (RCT) participants.
Methods:
Costings, clinical-effectiveness (appropriateness-of-treatment), QALYs and patient satisfaction data were collected at baseline and 12-month follow-up for a new pharmacy-service within a randomised-controlled-trial. Trial participants who replied to the follow-up survey and had not subsequently withdrawn from the study were mailed a DCE questionnaire at 24-months. WTP for the standard and new service was derived from the DCE. Results from QALYs and the DCE were compared.
Results:
At 12 months, costs, clinical-effectiveness and QALYs did not differ between the intervention and control; however there was a significant increase in satisfaction in the intervention. The DCE valued this increased satisfaction in the intervention (positive net-benefit). The longer the time patients experienced the new service the greater the reported net-benefit.
Conclusion:
When incorporating a DCE into an economic evaluation a number of questions are raised: what factors should be valued, whose values (trial-groups vs. all-trial-population) and when should they be elicited (still-receiving-the-intervention or afterwards). Consideration should also be given to status quo bias.
More Related Videos
08:24The Joint Effect of Social Comparison and Social Distance on Evaluation of Intertemporal Choice Outcomes in Event-related Potential Studies
Published on: August 25, 2023
11:51Combining Behavioral Endocrinology and Experimental Economics: Testosterone and Social Decision Making
Published on: March 2, 2011
Related Concept Videos
Decision Making: P-value Method
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim is also stated. These statements can act as null and alternative hypotheses: a null hypothesis would be a neutral statement while the alternative hypothesis can...
Randomized Experiments
Simple randomization
Simple...
Econometric Views (EViews)
Experimental Designs
Factorial Design
Decision Making: Traditional Method
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...