Measuring Public Preferences for Health Outcomes and Expenditures in a Context of Healthcare Resource Re-Allocation
The final outcome of any resource allocation decision in healthcare cannot be determined in advance. Thus, decision makers, in deciding which new program to implement (or not), need to accommodate the uncertainty of different potential outcomes (i.e., change in both health and costs) that can occur, the size and nature (i.e., ‘bad’ or ‘good’) of these outcomes, and how they are being valued. Using the decision-making plane, which explicitly incorporates opportunity costs and relaxes the assumptions of perfect divisibility and constant returns to scale of the cost-effectiveness plane, all the potential outcomes of each resource allocation decision can be described.
In this study, we describe the development and testing of an instrument, using a discrete choice experiment methodology, allowing the measurement of public preferences for potential outcomes falling in different quadrants of the decision-making plane.
In a sample of 200 participants providing 4200 observations, we compared four versions of the preference-elicitation instrument using a range of indicators.
We identified one version that was well accepted by the participants and with good measurement properties.
This validated instrument can now be used in a larger representative sample to study the preferences of the public for potential outcomes stemming from re-allocation of healthcare resources.
We thank all participants in the study. We also thank the two anonymous reviewers for their comments, which helped us to improve the quality of this article.
Nicolas Krucien, Nathalie Pelletier-Fleury, and Amiram Gafni were involved in the design of the study and the writing of the article. Nicolas Krucien was in charge of the data analysis.
Compliance with Ethical Standards
Financial support for this study was provided by the French National Institute of Health and Medical Research (INSERM). The funding agreement ensured the authors’ independence in designing the study, interpreting the data, and writing and publishing the article.
Conflict of interest
Nicolas Krucien; Nathalie Pelletier-Fleury, and Amiram Gafni have no conflicts of interest that are directly relevant to the contents of this study.
The datasets generated during and/or analyzed during the current study are available from the corresponding author on request.
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