Healthcare Cost-Effectiveness Analysis for Older Patients

Using Cataract Surgery and Breast Cancer Treatment Data

by Arash Naeim

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This dissertation is divided into two sections. The cataract surgery section has two subcomponents: A methodological subsection focuses on strategies for imputing responses among older patients to questions not answered on the vision section of the Heath Utilities Index Mark 3 questionnaire. The cost-effectiveness analysis is based on a randomized clinical trial of older patients with cataracts, comparing up-front surgery versus watchful waiting in patients who have relatively good visual functioning. The use of a preoperative tool, the Cataract Surgery Index, was shown to discriminate between those with high and low probability for improvement from surgery and those for whom surgery was cost-effective. The breast cancer section focuses on an evidence-based decision analysis for patients older than 65 who have newly diagnosed early-stage breast cancer. The uncertainty associated with treatment decision in older breast cancer patients can be mapped using a decision analysis framework. In both 65- and 75-year-old patients, there were scenarios for which combined hormone and chemotherapy could be considered cost-effective. Sensitivity testing taking into account higher discount rates in older patients and different baseline quality-of-life states altered the cost-effectiveness of most adjuvant therapy strategies.

Table of Contents

  • Summary

  • All Prefatory Materials

  • Chapter One


  • Chapter Two

    Handling Missing Data in the Health Utilities Index Mark3 (HUI3)

  • Chapter Three

    Cost-Effectiveness of Cataract Surgery Versus Watchful Waiting: A Randomized Trial of Patients with Good Visual Functioning

  • Chapter Four

    Clinical Trial in Older Cancer Patients: An Overview of Obstacles in Generating Evidence-Based Data

  • Chapter Five

    Decision Analysis Modeling of the Adjuvant Treatment of Older Patients with Breast Cancer

  • Chapter Six

    Current Issues and Future Work

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