Introduction: Health state valuation is a key input in many economic evaluations that inform resource allocation across competing healthcare interventions. Empirical evidence has shown that, in preference elicitation surveys, respondents may value a health state differently if they are aware of the condition causing it ('labeling effects'). This study investigates the impact of including a multiple sclerosis (MS) label for valuation of MS health states.
Methods: Health state values for MS were elicited using two internet-based surveys in representative samples of the UK population ( n = 1702; n = 1788). In one survey respondents were not informed that health states were caused by MS. The second survey included a condition label for MS. Surveys were identical in all other ways. Health states were described using a MS-specific eight-dimensional classification system (MSIS-8D), and the time trade-off valuation technique was used. Differences between values for labeled and unlabeled states were assessed using descriptive statistics and multivariate regression methods.
Results: Adding a MS condition label had a statistically significant effect on mean health state values, resulting in lower values for labeled MS states v. unlabeled states. The data suggest that the MS label had a more significant effect on values for less severe states, and no significant effect on values for the most severe states. The inclusion of the MS label had a differential impact across the dimensions of the MSIS-8D. Across the MSIS-8D, predicted values ranged from 0.079 to 0.883 for unlabeled states, and 0.066 to 0.861 for labeled states.
Conclusion: Differences reported in health state values, using labeled and unlabeled states, demonstrate that condition labels affect the results of valuation studies, and can have important implications in decision-analytic modelling and in economic evaluations.
Keywords: QALY; labeling; multiple sclerosis; preference-based measures; preferences; valuation.