‘Naming and Framing’: The impact of labelling on health state values for multiple sclerosis
Medical Decision Making
Introduction: Health state valuation is a key input to many economic evaluations that inform resource allocation across competing health care interventions. Empirical evidence has shown that respondents to preference elicitation surveys may value a health state differently if aware of the condition causing it (‘labelling 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 labelled and unlabelled states are 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 labelled MS states versus unlabelled states. Data suggests 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 0.079-0.883 for unlabelled states, and 0.066-0.861 for labelled states. Conclusions: Differences reported in health state values, using labelled and unlabelled states, demonstrate that condition labels affect the results of valuation studies, and can have important implications in decision-analytic modelling and in economic evaluations.
Financial support for this study was provided in part by the Multiple Sclerosis Society of Great Britain and Northern Ireland. The funding agreement ensured the authors’ independence in designing the study, interpreting the data, writing, and publishing the report. C Green and A Hawton acknowledge partial funding from the UK NIHR Collaboration for Leadership in Applied Health Research and Care of the South West Peninsula (PenCLAHRC). The views expressed in this publication are those of the authors and not necessarily those of the Multiple Sclerosis Society, the UK NIHR or the Department of Health
This is the author accepted manuscript. The final version is available from SAGE Publications via the DOI in this record.
Article first published online: May 21, 2017