A new SF-6Dv2 value set based on a hybrid model using SG, cTTO, and DCE data

Area of Science:

• Health Economics
• Psychometrics
• Societal Preferences

Background:

• Health state valuation is crucial for healthcare decision-making.
• Existing instruments require updates to reflect current societal values.
• Societal preferences are key to developing robust health outcome measures.

Purpose of the Study:

• To develop a Short-Form 6-Dimension version 2 (SF-6Dv2) value set.
• To integrate societal preferences from Standard Gamble (SG), composite Time Trade-Off (cTTO), and Discrete Choice Experiment (DCE) methods.
• To establish a reliable tool for health economic evaluations.

Main Methods:

• Collected data from the general population in Quebec, Canada.
• Employed standardized valuation protocols for cTTO, DCE, and SG tasks.
• Analyzed data using various statistical models including OLS, GLS, Tobit, conditional logit, and hybrid models, assessing model performance via MAE and logical consistency.

Main Results:

• Analyzed over 56,000 observations from SG, cTTO, and DCE.
• The heteroskedastic hybrid model showed the best fit, with statistically significant coefficients.
• Generated a value set ranging from -0.216 to 1, with pain having the largest impact on health state valuations.

Conclusions:

• The heteroskedastic hybrid model effectively integrates data from SG, cTTO, and DCE for SF-6Dv2 value set generation.
• This new value set is expected to be a valuable input for healthcare decision-making.
• The findings underscore the importance of using multiple methods to capture comprehensive societal preferences.