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Development and Test of a New Method for Preference Measurement for Multistate Health Profiles

This dissertation was aimed at developing and testing a new method that can better capture preferences for multistate health profiles. The motivation arose from the failure of the QALY (Quality-Adjusted Life Year) model in adequately capturing preferences in multistate health profiles. The QALY-based technique at the time of the study captured preferences for multistate health profiles by evaluating each health state in the profile independently of other states. As past literature showed, this additive independence condition does not hold in practice, and hence, such an approach is inadequate.

To address this issue, the study proposed a novel approach to measure preferences for multistate health profiles by looking at two consecutive health states at a time. It hypothesized that an evaluation of the future health state is dependent or "conditioned" on the level of the preceding, or current, health state. Characteristics of the current health state that were suspected to impact the resulting conditional preference scores for future health state were systematically explored in a carefully designed empirical study. The interested factors included duration of the current health state and direction of change and amplitude of change between the current and future health states. A 23 full factorial design with three replications was used to explore main effects and their interactions. In a subsequent experiment, the study tested whether the proposed technique, which assesses "conditional preference scores" for discrete health states, could better predict preference scores for an entire health profile than the current unconditional QALY-based technique. In this subsequent study, duration-weighted conditional preference scores, duration-weighted unconditional preference scores, and duration-weighted holistic preference scores were compared for 10 hypothetical health profiles. Visual analog scale is used as an elicitation technique throughout the experiment. The ultimate goal of the study was to enable more accurate cost-effectiveness analyses, which sequentially will lead to better healthcare resource allocation decisions. The dissertation concluded with the results and discussions of the effects of the current health state characteristics on the preference evaluation of future health state as well as the potential of the proposed technique in capturing preferences for multistate health profiles. Implications for other related fields and future research were also discussed.

Committee Members:
François Sainfort, Ph.D. (Advisor)
Julie Jacko, Ph.D. (Co-Advisor)
Brani Vidakovic, Ph.D.
Ann Bostrom, Ph.D.
Christopher Flowers, M.D.

Principal Investigator: Thitima Kongnakorn, Ph.D.

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