Novel methods in preference-based health outcome measurement: development, validation, application

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    Abstract

    Measuring subjective health outcomes (or patient-reported outcomes, well-being, health status, health-related quality of life) has gained substantial recognition, beyond traditional clinical indicators (e.g., survival, blood pressure). Distinct categories of health outcome measures have been developed to measure subjective health outcomes. They are constructed through diverse measurement frameworks, such as preference-based measures. Preference-based measures specially assign weights (importance) to health items and levels of items (attribute levels). These weights can be further computed to produce a single index that expresses the (social) value of a health state. Such values are meaningful in monitoring population’s health, assessing healthcare interventions, comparing health status across different populations. Especially, when normalized into utilities which range from 0.0 (dead) to 1.0 (full health), they are applicable to conduct cost-effectiveness analysis in health economic evaluations.
    Challenges remain in existing preference-based PROMs (e.g., no patient involvement in their development, limitations remain in preference-based methods). Trying to make some improvements to the current preference-based PROMs, we introduced a novel measurement framework (multi-attribute preference response, MAPR) for developing health outcome measures. The MAPR framework integrated a patient-centered, preference-based PROM (CS-Base), a novel and simpler preference-based method (Drop-Down), and user-friendly electronic mobile applications. In this thesis, we introduced two new preference-based methods developed within the MAPR framework and compared them head-to-head (Chapter 2); We parallelly compared the CS-Base with the widely-used EQ-5D-5L, to explore the effects of different measurement frameworks and descriptive systems (Chapter 3); We also reported the results of a preliminary application of CS-Base in comparing health status across various health conditions (Chapter 4); Finally, a first CS-Base utility set was generated for its application in health economic evaluations (Chapter 5).
    Original languageEnglish
    QualificationDoctor of Philosophy
    Awarding Institution
    • University of Groningen
    Supervisors/Advisors
    • Krabbe, Paul, Supervisor
    • Vermeulen, Karin, Co-supervisor
    Award date5-Feb-2024
    Place of Publication[Groningen]
    Publisher
    DOIs
    Publication statusPublished - 2024

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