Browsing by Author "Wagner, Daniel"

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    Enhancing the Reproducibility of Health Technology Assessments
    (2021-12) Wagner, Daniel; Spackman, Eldon; Hazlewood, Glen; Beall, Reed; Bojke, Laura
    Health systems around the world depend on Health Technology Assessment (HTA) programs to provide policy guidance on many factors, including value-for-money. To ensure decisions are made with current information, methods of evidence synthesis and economic evaluation are used to inform a continuous process of evidence gathering and decision making. While computers are used in almost every part of this process, the act of updating an existing HTA often involves a duplication of the original effort. The experience of other scientific fields suggests this is attributable to a lack of reproducibility. This refers to the ability to obtain consistent computational results, using the same set of files and processes. The objective of this thesis was to explore how an emphasis on reproducibility can support the effective development and maintenance of HTAs. Satisfaction of this objective required the identification and implementation of computing strategies to enhance the reproducibility of HTAs. A literature review was used to identify techniques for reproducibility which had proven successful in other fields. The identified strategies encouraged the creation of an accurate and complete record of the research process in human and machine-readable formats. These findings were subsequently applied to a case study which redeveloped an existing appraisal of biologic treatment for psoriatic arthritis. The first part of the case study summarized the development and execution of an automated workflow. The second part explored how the computing strategies affected the programming of the economic model. Outcomes from the case study included improved quality control, more efficient updating, and the elimination of barriers to the characterization of uncertainty. With enough investment, enhancing the reproducibility of HTAs will enable improved transparency, better decision making, and ultimately population health gains.