Why Health Preference Research Matters: From Economic Theory to Regulatory Decision-Making
DOI:
https://doi.org/10.64292/dsim.225Keywords:
Health preference research, random utility theory, discrete choice experiments, patient preference information, benefit–risk assessment, health technology assessment, regulatory decision-makingAbstract
Health Preference Research (HPR) has become increasingly important in regulatory and health technology assessment (HTA) contexts as healthcare decision-making is characterized by uncertainty, information asymmetries, and institutional constraints. In such settings, market data are often unavailable or distorted, and structured methods are needed to quantify patients' valuation of benefits, risks, and treatment trade-offs. This article examines how HPR has developed across theoretical foundations, methodological advances, and institutional uptake, and clarifies its contribution to healthcare decision-making. This narrative review draws on targeted literature searches and citation tracking to examine key theoretical, methodological, and institutional developments in HPR. It traces developments from stochastic utility theory and Random Utility Models to advances in microeconometrics and discrete choice methods, and examines regulatory and HTA initiatives. Theoretical developments, particularly Random Utility Theory, established a framework for analyzing preferences as latent constructs. Methodological advances enabled the empirical estimation of trade-offs through discrete choice models and experimental designs. These approaches have increasingly been translated into regulatory and HTA contexts, where preference-based evidence is used to inform benefit–risk assessment and reimbursement decisions. At the same time, methodological challenges remain, including questions of external validity, response consistency, and the temporal stability of elicited preferences. HPR represents a coherent extension of established economic and econometric principles and provides a structured framework for integrating patient preferences into healthcare decision-making. Its further institutionalization will depend on methodological rigor, transparent reporting, and alignment with regulatory and HTA requirements.
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