Using latent class and quantum models to value equity in health care: a tale of 2 stories

Cost-effectiveness analysis (CEA) with quality-adjusted life-year (QALY) was introduced to address health equity concerns in value assessment. However, QALY fails capture patient preference. Stated preference methods (eg, discrete choice experiment [DCE]) have been increasingly used incorporate into the assessment framework care. Still, ones a moral dimension such as do not exist. The objective of this paper describe 2 stated approaches that can empirically equity. First, decision-maker perceptions prevalence dimensions DCE tasks are identified. A latent class model based on random utility theory is proposed derive from decision makers different dimensions. Second, attributes incorporated tasks, and quantum model, which stochasticity during process mind makers, These will improve existing adequately. DISCLOSURES: This study received no outside funding. Ngorsuraches has research grants Bristol Myers Squibb through University Utah PhRMA Foundation.